%0 Journal Article %@ 1929-0748 %I JMIR Publications %V 14 %N %P e58567 %T Patient-Related Metadata Reported in Sequencing Studies of SARS-CoV-2: Protocol for a Scoping Review and Bibliometric Analysis %A O'Connor,Karen %A Weissenbacher,Davy %A Elyaderani,Amir %A Lautenbach,Ebbing %A Scotch,Matthew %A Gonzalez-Hernandez,Graciela %+ Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Blvd, Pacific Design Center Suite G549F, Los Angeles, CA, 90069, United States, 1 310 423 3521, graciela.gonzalezhernandez@cshs.org %K SARS-CoV-2 %K COVID-19 %K genomic epidemiology %K GISAID %K GenBank %K sequence records %K patient-related metadata %K scoping review %K protocol %D 2025 %7 22.4.2025 %9 Protocol %J JMIR Res Protoc %G English %X Background: There has been an unprecedented effort to sequence the SARS-CoV-2 virus and examine its molecular evolution. This has been facilitated by the availability of publicly accessible databases, such as the GISAID (Global Initiative on Sharing All Influenza Data) and GenBank, which collectively hold millions of SARS-CoV-2 sequence records. Genomic epidemiology, however, seeks to go beyond phylogenetic (the study of evolutionary relationships among biological entities) analysis by linking genetic information to patient characteristics and disease outcomes, enabling a comprehensive understanding of transmission dynamics and disease impact. While these repositories include fields reflecting patient-related metadata for a given sequence, the inclusion of these demographic and clinical details is scarce. The current understanding of patient-related metadata in published sequencing studies and its quality remains unexplored. Objective: Our review aims to quantitatively assess the extent and quality of patient-reported metadata in papers reporting original whole genome sequencing of the SARS-CoV-2 virus and analyze publication patterns using bibliometric analysis. Finally, we will evaluate the efficacy and reliability of a machine learning classifier in accurately identifying relevant papers for inclusion in the scoping review. Methods: The National Institutes of Health’s LitCovid collection will be used for the automated classification of papers reporting having deposited SARS-CoV-2 sequences in public repositories, while an independent search will be conducted in MEDLINE and PubMed Central for validation. Data extraction will be conducted using Covidence (Veritas Health Innovation Ltd). The extracted data will be synthesized and summarized to quantify the availability of patient metadata in the published literature of SARS-CoV-2 sequencing studies. For the bibliometric analysis, relevant data points, such as author affiliations, citation metrics, author keywords, and Medical Subject Headings terms will be extracted. Results: This study is expected to be completed in early 2025. Our classification model has been developed and we have classified publications in LitCovid published through February 2023. As of September 2024, papers through August 2024 are being prepared for processing. Screening is underway for validated papers from the classifier. Direct literature searches and screening of the results began in October 2024. We will summarize and narratively describe our findings using tables, graphs, and charts where applicable. Conclusions: This scoping review will report findings on the extent and types of patient-related metadata reported in genomic viral sequencing studies of SARS-CoV-2, identify gaps in the reporting of patient metadata, and make recommendations for improving the quality and consistency of reporting in this area. The bibliometric analysis will uncover trends and patterns in the reporting of patient-related metadata, including differences in reporting based on study types or geographic regions. The insights gained from this study may help improve the quality and consistency of reporting patient metadata, enhancing the utility of sequence metadata and facilitating future research on infectious diseases. Trial Registration: OSF Registries osf.io/wrh95; https://doi.org/10.17605/OSF.IO/WRH95 International Registered Report Identifier (IRRID): DERR1-10.2196/58567 %M 40262134 %R 10.2196/58567 %U https://www.researchprotocols.org/2025/1/e58567 %U https://doi.org/10.2196/58567 %U http://www.ncbi.nlm.nih.gov/pubmed/40262134 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e63754 %T Ensuring General Data Protection Regulation Compliance and Security in a Clinical Data Warehouse From a University Hospital: Implementation Study %A Riou,Christine %A El Azzouzi,Mohamed %A Hespel,Anne %A Guillou,Emeric %A Coatrieux,Gouenou %A Cuggia,Marc %K clinical data warehouse %K privacy %K personal data protection %K legislation %K security %K compliance %K personal data %K applicability %K experiential analysis %K university hospitals %K French %K France %K data hub %K operational challenge %D 2025 %7 17.4.2025 %9 %J JMIR Med Inform %G English %X Background: The European Union’s General Data Protection Regulation (GDPR) has profoundly influenced health data management, with significant implications for clinical data warehouses (CDWs). In 2021, France pioneered a national framework for GDPR-compliant CDW implementation, established by its data protection authority (Commission Nationale de l’Informatique et des Libertés). This framework provides detailed guidelines for health care institutions, offering a unique opportunity to assess practical GDPR implementation in health data management. Objective: This study evaluates the real-world applicability of France’s CDW framework through its implementation at a major university hospital. It identifies practical challenges for its implementation by health institutions and proposes adaptations relevant to regulatory authorities in order to facilitate research in secondary use data domains. Methods: A systematic assessment was conducted in May 2023 at the University Hospital of Rennes, which manages data for over 2 million patients through the eHOP CDW system. The evaluation examined 116 criteria across 13 categories using a dual-assessment approach validated by information security and data protection officers. Compliance was rated as met, unmet, or not applicable, with criteria classified as software-related (n=25) or institution-related (n=91). Results: Software-related criteria showed 60% (n=15) compliance, with 28% (n=7) noncompliant or partially compliant and 12% (n=3) not applicable. Institution-related criteria achieved 72% (n=28) compliance for security requirements. Key challenges included managing genetic data, implementing automated archiving, and controlling data exports. The findings revealed effective privacy protection measures but also highlighted areas requiring regulatory adjustments to better support research. Conclusions: This first empirical assessment of a national CDW compliance framework offers valuable insights for health care institutions implementing GDPR requirements. While the framework establishes robust privacy protections, certain provisions may overly constrain research activities. The study identifies opportunities for framework evolution, balancing data protection with research imperatives. %R 10.2196/63754 %U https://medinform.jmir.org/2025/1/e63754 %U https://doi.org/10.2196/63754 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 14 %N %P e65576 %T Estimating the Burden of Common Mental Disorders Attributable to Lifestyle Factors: Protocol for the Global Burden of Disease Lifestyle and Mental Disorder (GLAD) Project %A Ashtree,Deborah N %A Orr,Rebecca %A Lane,Melissa M %A Akbaraly,Tasnime N %A Bonaccio,Marialaura %A Costanzo,Simona %A Gialluisi,Alessandro %A Grosso,Giuseppe %A Lassale,Camille %A Martini,Daniela %A Monasta,Lorenzo %A Santomauro,Damian %A Stanaway,Jeffrey %A Jacka,Felice N %A O'Neil,Adrienne %+ IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Deakin University, Level 2, Health Education & Research Building (HERB), Barwon Health Rear, Kitchener House, 299 Ryrie St, Geelong, 3220, Australia, 61 352278361, debbie.ashtree@deakin.edu.au %K mental health %K depression %K anxiety %K diet %K lifestyle %K mental disorders %K epidemiology %K burden of disease %D 2025 %7 14.3.2025 %9 Protocol %J JMIR Res Protoc %G English %X Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) collects and calculates risk-outcome data for modifiable lifestyle exposures (eg, dietary intake) and physical health outcomes (eg, cancers). These estimates form a critical digital resource tool, the GBD VizHub data visualization tool, for governments and policy makers to guide local, regional, and global health decisions. Despite evidence showing the contributions of lifestyle exposures to common mental disorders (CMDs), such as depression and anxiety, GBD does not currently generate these lifestyle exposure-mental disorder outcome pairings. This gap is due to a lack of uniformly collected and analyzed data about these exposures as they relate to CMDs. Such data are required to quantify whether, and to what degree, the global burden of CMDs could be reduced by targeting lifestyle factors at regional and global levels. We have established the Global burden of disease Lifestyle And mental Disorder (GLAD) Taskforce to address this gap. Objective: This study aims to generate the necessary estimates to afford the inclusion of lifestyle exposures as risk factors for CMDs in the GBD study and the GBD digital visualization tools, initially focusing on the relationship between dietary intake and CMDs. Methods: The GLAD project is a multicenter, collaborative effort to integrate lifestyle exposures as risk factors for CMDs in the GBD study. To achieve this aim, global epidemiological studies will be recruited to conduct harmonized data analyses estimating the risk, odds, or hazards of lifestyle exposures with CMD outcomes. Initially, these models will focus on the relationship between dietary intake, as defined by the GBD, and anxiety and depression. Results: As of August 2024, 18 longitudinal cohort studies from 9 countries (Australia: n=4; Brazil: n=1; France: n=1; Italy: n=3; The Netherlands: n=3; New Zealand: n=1; South Africa: n=1; Spain: n=1; and United Kingdom: n=3) have agreed to participate in the GLAD project. Conclusions: Our comprehensive, collaborative approach allows for the concurrent execution of a harmonized statistical analysis protocol across multiple, internationally renowned epidemiological cohorts. These results will be used to inform the GBD study and incorporate lifestyle risk factors for CMD in the GBD digital platform. Consequently, given the worldwide influence of the GBD study, findings from the GLAD project can offer valuable insights to policy makers worldwide around lifestyle-based mental health care. International Registered Report Identifier (IRRID): DERR1-10.2196/65576 %M 40085831 %R 10.2196/65576 %U https://www.researchprotocols.org/2025/1/e65576 %U https://doi.org/10.2196/65576 %U http://www.ncbi.nlm.nih.gov/pubmed/40085831 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e64705 %T Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study %A Mast,Nicholas H %A Oeste,Clara L. %A Hens,Dries %K total hip arthroplasty %K THA %K direct anterior approach %K electronic health records %K EHR %K natural language processing %K NLP %K complication rate %K single-surgeon registry %K hip arthroplasty %K orthopedic %K validation %K surgeon %K outpatient visits %K hospitalizations %K surgery %D 2025 %7 12.3.2025 %9 %J JMIR Med Inform %G English %X Background: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. However, most private data systems prevent obtaining usable insights for clinical practice. Objective: This study aims to create an automated natural language processing (NLP) pipeline for extracting clinical concepts from EHRs related to orthopedic outpatient visits, hospitalizations, and surgeries in a multicenter, single-surgeon practice. The pipeline was also used to assess therapies and complications after total hip arthroplasty (THA). Methods: EHRs of 1290 patients undergoing primary THA from January 1, 2012 to December 31, 2019 (operated and followed by the same surgeon) were processed using artificial intelligence (AI)–based models (NLP and machine learning). In addition, 3 independent medical reviewers generated a gold standard using 100 randomly selected EHRs. The algorithm processed the entire database from different EHR systems, generating an aggregated clinical data warehouse. An additional manual control arm was used for data quality control. Results: The algorithm was as accurate as human reviewers (0.95 vs 0.94; P=.01), achieving a database-wide average F1-score of 0.92 (SD 0.09; range 0.67‐0.99), validating its use as an automated data extraction tool. During the first year after direct anterior THA, 92.1% (1188/1290) of our population had a complication-free recovery. In 7.9% (102/1290) of cases where surgery or recovery was not uneventful, lateral femoral cutaneous nerve sensitivity (47/1290, 3.6%), intraoperative fractures (13/1290, 1%), and hematoma (9/1290, 0.7%) were the most common complications. Conclusions: Algorithm evaluation of this dataset accurately represented key clinical information swiftly, compared with human reviewers. This technology may provide substantial value for future surgeon practice and patient counseling. Furthermore, the low early complication rate of direct anterior THA in this surgeon’s hands was supported by the dataset, which included data from all treated patients in a multicenter practice. %R 10.2196/64705 %U https://medinform.jmir.org/2025/1/e64705 %U https://doi.org/10.2196/64705 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e65590 %T Data Interoperability in COVID-19 Vaccine Trials: Methodological Approach in the VACCELERATE Project %A Malik,Salma %A Dorothea,Zoi Pana %A Argyropoulos,Christos D %A Themistocleous,Sophia %A Macken,Alan J %A Valdenmaiier,Olena %A Scheckenbach,Frank %A Bardach,Elena %A Pfeiffer,Andrea %A Loens,Katherine %A Ochando,Jordi Cano %A Cornely,Oliver A %A Demotes-Mainard,Jacques %A Contrino,Sergio %A Felder,Gerd %+ European Clinical Research Infrastructure Network, 30 Bd Saint-Jacques, Paris, 75014, France, 33 01 80 05 86 29, salma.malik@ecrin.org %K interoperability %K metadata %K data management %K clinical trials %K protocol %K harmonization %K adult %K pediatric %K systems %K standards %D 2025 %7 7.3.2025 %9 Original Paper %J JMIR Med Inform %G English %X Background: Data standards are not only key to making data processing efficient but also fundamental to ensuring data interoperability. When clinical trial data are structured according to international standards, they become significantly easier to analyze, reducing the efforts required for data cleaning, preprocessing, and secondary use. A common language and a shared set of expectations facilitate interoperability between systems and devices. Objective: The main objectives of this study were to identify commonalities and differences in clinical trial metadata, protocols, and data collection systems/items within the VACCELERATE project. Methods: To assess the degree of interoperability achieved in the project and suggest methodological improvements, interoperable points were identified based on the core outcome areas—immunogenicity, safety, and efficacy (clinical/physiological). These points were emphasized in the development of the master protocol template and were manually compared in the following ways: (1) summaries, objectives, and end points in the protocols of 3 VACCELERATE clinical trials (EU-COVAT-1_AGED, EU-COVAT-2_BOOSTAVAC, and EU-COVPT-1_CoVacc) against the master protocol template; (2) metadata of all 3 clinical trials; and (3) evaluations from a questionnaire survey regarding differences in data management systems and structures that enabled data exchange within the VACCELERATE network. Results: The noncommonalities identified in the protocols and metadata were attributed to differences in populations, variations in protocol design, and vaccination patterns. The detailed metadata released for all 3 vaccine trials were clearly structured using internal standards, terminology, and the general approach of Clinical Data Acquisition Standards Harmonisation (CDASH) for data collection (eg, on electronic case report forms). VACCELERATE benefited significantly from the selection of the Clinical Trials Centre Cologne as the sole data management provider. With system database development coordinated by a single individual and no need for coordination among different trial units, a high degree of uniformity was achieved automatically. The harmonized transfer of data to all sites, using well-established methods, enabled quick exchanges and provided a relatively secure means of data transfer. Conclusions: This study demonstrated that using master protocols can significantly enhance trial operational efficiency and data interoperability, provided that similar infrastructure and data management procedures are adopted across multiple trials. To further improve data interoperability and facilitate interpretation and analysis, shared data should be structured, described, formatted, and stored using widely recognized data and metadata standards. Trial Registration: EudraCT 2021-004526-29; https://www.clinicaltrialsregister.eu/ctr-search/trial/2021-004526-29/DE/; 2021-004889-35; https://www.clinicaltrialsregister.eu/ctr-search/search?query=eudract_number:2021-004889-35; and 2021-004526-29; https://www.clinicaltrialsregister.eu/ctr-search/search?query=eudract_number:2021-004526-29 %M 40056469 %R 10.2196/65590 %U https://medinform.jmir.org/2025/1/e65590 %U https://doi.org/10.2196/65590 %U http://www.ncbi.nlm.nih.gov/pubmed/40056469 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e67984 %T A Validation Tool (VaPCE) for Postcoordinated SNOMED CT Expressions: Development and Usability Study %A Ohlsen,Tessa %A Hofer,Viola %A Ingenerf,Josef %K SNOMED CT %K PCE %K postcoordination %K FHIR %K validation %K postcoordinated expression %K Fast Healthcare Interoperability Resource %D 2025 %7 28.2.2025 %9 %J JMIR Med Inform %G English %X Background: The digitalization of health care has increased the demand for efficient data exchange, emphasizing semantic interoperability. SNOMED Clinical Terms (SNOMED CT), a comprehensive terminology with over 360,000 medical concepts, supports this need. However, it cannot cover all medical scenarios, particularly in complex cases. To address this, SNOMED CT allows postcoordination, where users combine precoordinated concepts with new expressions. Despite SNOMED CT’s potential, the creation and validation of postcoordinated expressions (PCEs) remain challenging due to complex syntactic and semantic rules. Objective: This work aims to develop a tool that validates postcoordinated SNOMED CT expressions, focusing on providing users with detailed, automated correction instructions for syntactic and semantic errors. The goal is not just validation, but also offering user-friendly, actionable suggestions for improving PCEs. Methods: A tool was created using the Fast Healthcare Interoperability Resource (FHIR) service $validate-code and the terminology server Ontoserver to check the correctness of PCEs. When errors are detected, the tool processes the SNOMED CT Concept Model in JSON format and applies predefined error categories. For each error type, specific correction suggestions are generated and displayed to users. The key added value of the tool is in generating specific correction suggestions for each identified error, which are displayed to the users. The tool was integrated into a web application, where users can validate individual PCEs or bulk-upload files. The tool was tested with real existing PCEs, which were used as input and validated. In the event of errors, appropriate error messages were generated as output. Results: In the validation of 136 PCEs from 304 FHIR Questionnaires, 18 (13.2%) PCEs were invalid, with the most common errors being invalid attribute values. Additionally, 868 OncoTree codes were evaluated, resulting in 161 (20.9%) PCEs containing inactive concepts, which were successfully replaced with valid alternatives. A user survey reflects a favorable evaluation of the tool’s functionality. Participants found the error categorization and correction suggestions to be precise, offering clear guidance for addressing issues. However, there is potential for enhancement, particularly regarding the level of detail in the error messages. Conclusions: The validation tool significantly improves the accuracy of postcoordinated SNOMED CT expressions by not only identifying errors but also offering detailed correction instructions. This approach supports health care professionals in ensuring that their PCEs are syntactically and semantically valid, enhancing data quality and interoperability across systems. %R 10.2196/67984 %U https://medinform.jmir.org/2025/1/e67984 %U https://doi.org/10.2196/67984 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e58509 %T Effectiveness of the Facility for Elderly Surveillance System (FESSy) in Two Public Health Center Jurisdictions in Japan: Prospective Observational Study %A Kurita,Junko %A Hori,Motomi %A Yamaguchi,Sumiyo %A Ogiwara,Aiko %A Saito,Yurina %A Sugiyama,Minako %A Sunadori,Asami %A Hayashi,Tomoko %A Hara,Akane %A Kawana,Yukari %A Itoi,Youichi %A Sugawara,Tamie %A Sugishita,Yoshiyuki %A Irie,Fujiko %A Sakurai,Naomi %K early detection %K facility for older people %K outbreak %K public health center %K syndromic surveillance %K Japan %K older adults %D 2025 %7 10.1.2025 %9 %J JMIR Med Inform %G English %X Background: Residents of facilities for older people are vulnerable to COVID-19 outbreaks. Nevertheless, timely recognition of outbreaks at facilities for older people at public health centers has been impossible in Japan since May 8, 2023, when the Japanese government discontinued aggressive countermeasures against COVID-19 because of the waning severity of the dominant Omicron strain. The Facility for Elderly Surveillance System (FESSy) has been developed to improve information collection. Objective: This study examined FESSy experiences and effectiveness in two public health center jurisdictions in Japan. Methods: This study assessed the use by public health centers of the detection mode of an automated AI detection system (ie, FESSy AI), as well as manual detection by the public health centers’ staff (ie, FESSy staff) and direct reporting by facilities to the public health centers. We considered the following aspects: (1) diagnoses or symptoms, (2) numbers of patients as of their detection date, and (3) ultimate numbers of patients involved in incidents. Subsequently, effectiveness was assessed and compared based on detection modes. The study lasted from June 1, 2023, through January 2024. Results: In both areas, this study examined 31 facilities at which 87 incidents were detected. FESSy (AI or staff) detected significantly fewer patients than non-FESSy methods, that is, direct reporting to the public health center of the detection date and ultimate number of patients. Conclusions: FESSy was superior to direct reporting from facilities for the number of patients as of the detection date and for the ultimate outbreak size. %R 10.2196/58509 %U https://medinform.jmir.org/2025/1/e58509 %U https://doi.org/10.2196/58509 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60017 %T Visualizing Patient Pathways and Identifying Data Repositories in a UK Neurosciences Center: Exploratory Study %A Knight,Jo %A Chandrabalan,Vishnu Vardhan %A Emsley,Hedley C A %K health data %K business process monitoring notation %K neurology %K process monitoring %K patient pathway %K clinical pathway %K patient care %K EHR %K electronic health record %K dataset %K questionnaire %K patient data %K NHS %K National Health Service %D 2024 %7 24.12.2024 %9 %J JMIR Med Inform %G English %X Background: Health and clinical activity data are a vital resource for research, improving patient care and service efficiency. Health care data are inherently complex, and their acquisition, storage, retrieval, and subsequent analysis require a thorough understanding of the clinical pathways underpinning such data. Better use of health care data could lead to improvements in patient care and service delivery. However, this depends on the identification of relevant datasets. Objective: We aimed to demonstrate the application of business process modeling notation (BPMN) to represent clinical pathways at a UK neurosciences center and map the clinical activity to corresponding data flows into electronic health records and other nonstandard data repositories. Methods: We used BPMN to map and visualize a patient journey and the subsequent movement and storage of patient data. After identifying several datasets that were being held outside of the standard applications, we collected information about these datasets using a questionnaire. Results: We identified 13 standard applications where neurology clinical activity was captured as part of the patient’s electronic health record including applications and databases for managing referrals, outpatient activity, laboratory data, imaging data, and clinic letters. We also identified 22 distinct datasets not within standard applications that were created and managed within the neurosciences department, either by individuals or teams. These were being used to deliver direct patient care and included datasets for tracking patient blood results, recording home visits, and tracking triage status. Conclusions: Mapping patient data flows and repositories allowed us to identify areas wherein the current electronic health record does not fulfill the needs of day-to-day patient care. Data that are being stored outside of standard applications represent a potential duplication in the effort and risks being overlooked. Future work should identify unmet data needs to inform correct data capture and centralization within appropriate data architectures. %R 10.2196/60017 %U https://medinform.jmir.org/2024/1/e60017 %U https://doi.org/10.2196/60017 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60244 %T Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium %A Declerck,Jens %A Vandenberk,Bert %A Deschepper,Mieke %A Colpaert,Kirsten %A Cool,Lieselot %A Goemaere,Jens %A Bové,Mona %A Staelens,Frank %A De Meester,Koen %A Verbeke,Eva %A Smits,Elke %A De Decker,Cami %A Van Der Vekens,Nicky %A Pauwels,Elin %A Vander Stichele,Robert %A Kalra,Dipak %A Coorevits,Pascal %K EHR %K electronic health records %K health data %K data quality dimensions %K data quality assessment %K secondary use %K data quality framework %K fit for purpose %K Belgium %K data quality %K framework %K case study %K hospital %K variability %D 2024 %7 20.12.2024 %9 %J JMIR Med Inform %G English %X Background: Data quality is fundamental to maintaining the trust and reliability of health data for both primary and secondary purposes. However, before the secondary use of health data, it is essential to assess the quality at the source and to develop systematic methods for the assessment of important data quality dimensions. Objective: This case study aims to offer a dual aim—to assess the data quality of height and weight measurements across 7 Belgian hospitals, focusing on the dimensions of completeness and consistency, and to outline the obstacles these hospitals face in sharing and improving data quality standards. Methods: Focusing on data quality dimensions completeness and consistency, this study examined height and weight data collected from 2021 to 2022 within 3 distinct departments—surgical, geriatrics, and pediatrics—in each of the 7 hospitals. Results: Variability was observed in the completeness scores for height across hospitals and departments, especially within surgical and geriatric wards. In contrast, weight data uniformly achieved high completeness scores. Notably, the consistency of height and weight data recording was uniformly high across all departments. Conclusions: A collective collaboration among Belgian hospitals, transcending network affiliations, was formed to conduct this data quality assessment. This study demonstrates the potential for improving data quality across health care organizations by sharing knowledge and good practices, establishing a foundation for future, similar research. %R 10.2196/60244 %U https://medinform.jmir.org/2024/1/e60244 %U https://doi.org/10.2196/60244 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e60504 %T Improving Participant Recruitment in Clinical Trials: Comparative Analysis of Innovative Digital Platforms %A Bikou,Alexia Georgia %A Deligianni,Elena %A Dermiki-Gkana,Foteini %A Liappas,Nikolaos %A Teriús-Padrón,José Gabriel %A Beltrán Jaunsarás,Maria Eugenia %A Cabrera-Umpiérrez,Maria Fernanda %A Kontogiorgis,Christos %+ Department of Medicine, Democritus University of Thrace, 6th kilometer Dragana, Alexandroupolis, 68100, Greece, 30 2551030601, ckontogi@med.duth.gr %K clinical research %K e-recruitment %K patient matching %K clinical trials %K digital platforms %K enrollment %K electronic consent %D 2024 %7 18.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Pharmaceutical product development relies on thorough and costly clinical trials. Participant recruitment and monitoring can be challenging. The incorporation of cutting-edge technologies such as blockchain and artificial intelligence has revolutionized clinical research (particularly in the recruitment stage), enhanced secure data storage and analysis, and facilitated participant monitoring while protecting their personal information. Objective: This study aims to investigate the use of novel digital platforms and their features, such as e-recruitment, e-consent, and matching, aiming to optimize and expedite clinical research. Methods: A review with a systematic approach was conducted encompassing literature from January 2000 to October 2024. The MEDLINE, ScienceDirect, Scopus, and Google Scholar databases were examined thoroughly using a customized search string. Inclusion criteria focused on digital platforms involving clinical trial recruitment phases that were in English and had international presence, scientific validation, regulatory approval, and no geographic limitations. Literature reviews and unvalidated digital platforms were excluded. The selected studies underwent meticulous screening by the research team, ensuring a thorough analysis of novel digital platforms and their use and features for clinical trials. Results: A total of 24 digital platforms were identified that supported clinical trial recruitment phases. In general, most of them (n=22, 80%) are headquartered and operating in the United States, providing a range of functionalities including electronic consent (n=14, 60% of the platforms), participant matching, and monitoring of patients’ health status. These supplementary features enhance the overall effectiveness of the platforms in facilitating the recruitment process for clinical trials. The analysis and digital platform findings refer to a specific time frame when the investigation took place, and a notable surge was observed in the adoption of these novel digital tools, particularly following the COVID-19 outbreak. Conclusions: This study underscores the vital role of the identified digital platforms in clinical trials, aiding in recruitment, enhancing patient engagement, accelerating procedures, and personalizing vital sign monitoring. Despite their impact, challenges in accessibility, compatibility, and transparency require careful consideration. Addressing these challenges is crucial for optimizing digital tool integration into clinical research, allowing researchers to harness the benefits while managing the associated risks effectively. %M 39693619 %R 10.2196/60504 %U https://www.jmir.org/2024/1/e60504 %U https://doi.org/10.2196/60504 %U http://www.ncbi.nlm.nih.gov/pubmed/39693619 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e65646 %T Information Mode–Dependent Success Rates of Obtaining German Medical Informatics Initiative–Compliant Broad Consent in the Emergency Department: Single-Center Prospective Observational Study %A Hans,Felix Patricius %A Kleinekort,Jan %A Boerries,Melanie %A Nieters,Alexandra %A Kindle,Gerhard %A Rautenberg,Micha %A Bühler,Laura %A Weiser,Gerda %A Röttger,Michael Clemens %A Neufischer,Carolin %A Kühn,Matthias %A Wehrle,Julius %A Slagman,Anna %A Fischer-Rosinsky,Antje %A Eienbröker,Larissa %A Hanses,Frank %A Teepe,Gisbert Wilhelm %A Busch,Hans-Jörg %A Benning,Leo %+ University Emergency Department, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Sir-Hans-A.-Krebs-Strasse 1, Freiburg, 79106, Germany, 49 76127033266, felix.hans@uniklinik-freiburg.de %K biomedical research %K delivery of health care %K informed consent %K medical informatics %K digital health %K emergency medical services %K routinely collected health data %K data science %K secondary data analysis %K data analysis %K biomedical %K emergency %K Germany %K Europe %K prospective observational study %K broad consent %K inpatient stay %K logistic regression analysis %K health care delivery %K inpatients %D 2024 %7 17.12.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: The broad consent (BC) developed by the German Medical Informatics Initiative is a pivotal national strategy for obtaining patient consent to use routinely collected data from electronic health records, insurance companies, contact information, and biomaterials for research. Emergency departments (EDs) are ideal for enrolling diverse patient populations in research activities. Despite regulatory and ethical challenges, obtaining BC from patients in ED with varying demographic, socioeconomic, and disease characteristics presents a promising opportunity to expand the availability of ED data. Objective: This study aimed to evaluate the success rate of obtaining BC through different consenting approaches in a tertiary ED and to explore factors influencing consent and dropout rates. Methods: A single-center prospective observational study was conducted in a German tertiary ED from September to December 2022. Every 30th patient was screened for eligibility. Eligible patients were informed via one of three modalities: (1) directly in the ED, (2) during their inpatient stay on the ward, or (3) via telephone after discharge. The primary outcome was the success rate of obtaining BC within 30 days of ED presentation. Secondary outcomes included analyzing potential influences on the success and dropout rates based on patient characteristics, information mode, and the interaction time required for patients to make an informed decision. Results: Of 11,842 ED visits, 419 patients were screened for BC eligibility, with 151 meeting the inclusion criteria. Of these, 68 (45%) consented to at least 1 BC module, while 24 (15.9%) refused participation. The dropout rate was 39.1% (n=59) and was highest in the telephone-based group (57/109, 52.3%) and lowest in the ED group (1/14, 7.1%). Patients informed face-to-face during their inpatient stay following the ED treatment had the highest consent rate (23/27, 85.2%), while those approached in the ED or by telephone had consent rates of 69.2% (9/13 and 36/52). Logistic regression analysis indicated that longer interaction time significantly improved consent rates (P=.03), while female sex was associated with higher dropout rates (P=.02). Age, triage category, billing details (inpatient treatment), or diagnosis did not significantly influence the primary outcome (all P>.05). Conclusions: Obtaining BC in an ED environment is feasible, enabling representative inclusion of ED populations. However, discharge from the ED and female sex negatively affected consent rates to the BC. Face-to-face interaction proved most effective, particularly for inpatients, while telephone-based approaches resulted in higher dropout rates despite comparable consent rates to direct consenting in the ED. The findings underscore the importance of tailored consent strategies and maintaining consenting staff in EDs and on the wards to enhance BC information delivery and consent processes for eligible patients. Trial Registration: German Clinical Trials Register DRKS00028753; https://drks.de/search/de/trial/DRKS00028753 %M 39626089 %R 10.2196/65646 %U https://medinform.jmir.org/2024/1/e65646 %U https://doi.org/10.2196/65646 %U http://www.ncbi.nlm.nih.gov/pubmed/39626089 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e55880 %T The COSMOS Registry of CytoSorb Hemoadsorption Therapy in Critically Ill Patients: Protocol for an International, Prospective Registry %A Taccone,Fabio Silvio %A Brunkhorst,Frank Martin %A Bottari,Gabriella %A Hidalgo,Jorge %A Kribben,Andreas %A Teboul,Jean-Louis %A Tomescu,Dana %A Klaus,Teresa %A Scheier,Joerg %A Deliargyris,Efthymios %A Ferrer,Ricard %+ Intensive Care Department, Vall d'Hebron University Hospital, Shock, Organ Dysfunction and Resuscitation Research Group (SODIR), Pg. de la Vall d'Hebron, 119, Horta-Guinardó, Barcelona, 08035, Spain, 34 934893000, ricard.ferrer@vallhebron.cat %K extracorporeal blood purification %K CytoSorb %K hemoadsorption %K hemoperfusion %K adsorption %K hyperinflammation %K sepsis %K septic shock %K liver failure %K rhabdomyolysis %K hospital care %K mortality %D 2024 %7 5.11.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Extracorporeal blood purification with CytoSorb has been increasingly used as an adjunctive therapy in several hyperinflammatory critical care conditions, as well as to remove elevated levels of myoglobin or bilirubin in patients with rhabdomyolysis or liver failure. Despite the increasing worldwide use of hemoadsorption, data from large international multicenter studies are still lacking. Objective: The COSMOS (CytoSorb Treatment Of Critically Ill Patients) registry is a company-sponsored registry by CytoSorbents Corporation and CytoSorbents Medical Inc. and will provide a data repository and reporting infrastructure for the surveillance of CytoSorb use in real-world critical care settings in an unselected, critically ill patient population. The gathered data will serve as a comprehensive resource to assess the effects of such therapy on patients’ management. Methods: The international COSMOS registry is collecting prospective data for patients treated with CytoSorb during routine care in various critical care indications, based on the decision of the treating physicians. Data are collected at baseline, during CytoSorb therapy, 24 hours thereafter, at discharge from the intensive care unit and the hospital, and on day 90. Key outcomes assessed include change in inflammatory biomarkers, vasopressor requirements, fluid balance, organ function and organ support, length of intensive care unit and hospital stay, occurrence of adverse events, and mortality. Results: The COSMOS registry started with the inclusion of the first patient on July 15, 2022, and is now actively enrolling in 4 countries (Germany, Spain, Portugal, and Italy), with plans to expand to other countries outside of Europe. An initial readout is planned for presentation at an international Critical Care conference in 2024. Conclusions: The COSMOS registry is intended to provide comprehensive real-world data on patient outcomes with CytoSorb in various critical care indications, thereby contributing to optimization of patient selection, timing of initiation, and dosing of hemoadsorption treatment. Trial Registration: ClinicalTrials.gov NCT05146336; https://clinicaltrials.gov/study/NCT05146336 International Registered Report Identifier (IRRID): DERR1-10.2196/55880 %M 39500494 %R 10.2196/55880 %U https://www.researchprotocols.org/2024/1/e55880 %U https://doi.org/10.2196/55880 %U http://www.ncbi.nlm.nih.gov/pubmed/39500494 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e55029 %T Effects of Injury Registry Data on Policy Making, Hospitalizations, and Mortality: Protocol for a Systematic Review and Meta-Analysis %A Medeiros-de-Souza,Ana Cláudia %A Lopes,Luana Emanuelly Sinhori %A de Oliveira,Bruno Zocca %A Rother,Edna Terezinha %A Correia,Lucas Reis %+ Hospital Israelita Albert Einstein, 755 Comendador Elias Jafet Street, L1 Floor, Room 134, Sao Paulo, 05653-000, Brazil, 55 11989249946, ana.cms@einstein.br %K injury registry %K trauma registry %K policy making %K health policy %K wounds and injuries %K outcome assessments, health surveillance %K hospitalizations %K mortality %D 2024 %7 30.10.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Initiated in 2021, a Brazilian project aims to establish a national injury registry, compiling comprehensive data on events and individuals across the country, irrespective of injury severity. The registry integrates information from prehospital and hospital care, diverse health systems lacking interoperability, and sectors such as firefighters and the police. Its primary goal is to enhance health surveillance by providing timely, high-quality information, guiding prevention strategies, and informing policy making. The project still aims to reduce long-term morbidity and mortality associated with injuries. Objective: A knowledge gap remains regarding the effects of injury registries in relation to policies and injury outcomes. This protocol outlines a systematic review and meta-analysis to answer “What is the effect of implementation and use of injury registry data on policy making, hospitalization, and mortality?” Methods: The systematic review follows PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, focusing on studies reporting results related to the implementation and use of injury registries, including trauma registries. Outcomes of interest include policy making, hospitalization rates or duration, and mortality. Registries within well-defined administrative boundaries will be included. Data will be collected from PubMed, Embase, Scopus, Web of Science, Lilacs, and references. Records will be independently screened by 2 reviewers, with any disagreements resolved through arbitration by a third reviewer. Homogeneous studies, with 3 or more evaluating the same outcome, may undergo meta-analysis. Subgroup analyses by registry type, injury groups, and other selected variables of interest will be conducted. Sensitivity analysis, risk of bias assessment, publication bias evaluation, and quality appraisal will also be performed. Results: This systematic review will run from November 2023 to June 2024. No identical review was found. Search strategies were finalized, the bibliographic search started, duplicates were eliminated, and title and abstract screening began. Of 35 studies retrieved, 85 were excluded due to duplication, leaving 50 for selection. Conclusions: This study is timely, aligning with ongoing national efforts to implement an injury registry. By synthesizing available evidence, we will identify the potential of injury registries to guide the decisions of Brazilian policy makers. Trial Registration: PROSPERO CRD42023481528; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=481528 International Registered Report Identifier (IRRID): PRR1-10.2196/55029 %M 39475822 %R 10.2196/55029 %U https://www.researchprotocols.org/2024/1/e55029 %U https://doi.org/10.2196/55029 %U http://www.ncbi.nlm.nih.gov/pubmed/39475822 %0 Journal Article %@ 2561-7605 %I JMIR Publications %V 7 %N %P e54839 %T Using Existing Clinical Data to Measure Older Adult Inpatients’ Frailty at Admission and Discharge: Hospital Patient Register Study %A Wernli,Boris %A Verloo,Henk %A von Gunten,Armin %A Pereira,Filipa %+ University of Applied Sciences and Arts Western Switzerland (HES-SO), 5 Chemin de l'Agasse, Sion, 1950, Switzerland, 41 0787698990, henk.verloo@hevs.ch %K frailty %K frailty assessment %K electronic patient records %K functional independence measure %K routinely collected data %K hospital register %K patient records %K medical records %K clinical data %K older adults %K cluster analysis %K hierarchical clustering %D 2024 %7 28.10.2024 %9 Original Paper %J JMIR Aging %G English %X Background: Frailty is a widespread geriatric syndrome among older adults, including hospitalized older inpatients. Some countries use electronic frailty measurement tools to identify frailty at the primary care level, but this method has rarely been investigated during hospitalization in acute care hospitals. An electronic frailty measurement instrument based on population-based hospital electronic health records could effectively detect frailty, frailty-related problems, and complications as well be a clinical alert. Identifying frailty among older adults using existing patient health data would greatly aid the management and support of frailty identification and could provide a valuable public health instrument without additional costs. Objective: We aim to explore a data-driven frailty measurement instrument for older adult inpatients using data routinely collected at hospital admission and discharge. Methods: A retrospective electronic patient register study included inpatients aged ≥65 years admitted to and discharged from a public hospital between 2015 and 2017. A dataset of 53,690 hospitalizations was used to customize this data-driven frailty measurement instrument inspired by the Edmonton Frailty Scale developed by Rolfson et al. A 2-step hierarchical cluster procedure was applied to compute e-Frail-CH (Switzerland) scores at hospital admission and discharge. Prevalence, central tendency, comparative, and validation statistics were computed. Results: Mean patient age at admission was 78.4 (SD 7.9) years, with more women admitted (28,018/53,690, 52.18%) than men (25,672/53,690, 47.81%). Our 2-step hierarchical clustering approach computed 46,743 inputs of hospital admissions and 47,361 for discharges. Clustering solutions scored from 0.5 to 0.8 on a scale from 0 to 1. Patients considered frail comprised 42.02% (n=19,643) of admissions and 48.23% (n=22,845) of discharges. Within e-Frail-CH’s 0-12 range, a score ≥6 indicated frailty. We found a statistically significant mean e-Frail-CH score change between hospital admission (5.3, SD 2.6) and discharge (5.75, SD 2.7; P<.001). Sensitivity and specificity cut point values were 0.82 and 0.88, respectively. The area under the receiver operating characteristic curve was 0.85. Comparing the e-Frail-CH instrument to the existing Functional Independence Measure (FIM) instrument, FIM scores indicating severe dependence equated to e-Frail-CH scores of ≥9, with a sensitivity and specificity of 0.97 and 0.88, respectively. The area under the receiver operating characteristic curve was 0.92. There was a strong negative association between e-Frail-CH scores at hospital discharge and FIM scores (rs=–0.844; P<.001). Conclusions: An electronic frailty measurement instrument was constructed and validated using patient data routinely collected during hospitalization, especially at admission and discharge. The mean e-Frail-CH score was higher at discharge than at admission. The routine calculation of e-Frail-CH scores during hospitalization could provide very useful clinical alerts on the health trajectories of older adults and help select interventions for preventing or mitigating frailty. %M 39467281 %R 10.2196/54839 %U https://aging.jmir.org/2024/1/e54839 %U https://doi.org/10.2196/54839 %U http://www.ncbi.nlm.nih.gov/pubmed/39467281 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58541 %T Bridging Data Models in Health Care With a Novel Intermediate Query Format for Feasibility Queries: Mixed Methods Study %A Rosenau,Lorenz %A Gruendner,Julian %A Kiel,Alexander %A Köhler,Thomas %A Schaffer,Bastian %A Majeed,Raphael W %K feasibility %K FHIR %K CQL %K eligibility criteria %K clinical research %K intermediate query format %K healthcare interoperability %K cohort definition %K query %K queries %K interoperability %K interoperable %K informatics %K portal %K portals %K implementation %K develop %K development %K ontology %K ontologies %K JSON %D 2024 %7 14.10.2024 %9 %J JMIR Med Inform %G English %X Background: To advance research with clinical data, it is essential to make access to the available data as fast and easy as possible for researchers, which is especially challenging for data from different source systems within and across institutions. Over the years, many research repositories and data standards have been created. One of these is the Fast Healthcare Interoperability Resources (FHIR) standard, used by the German Medical Informatics Initiative (MII) to harmonize and standardize data across university hospitals in Germany. One of the first steps to make these data available is to allow researchers to create feasibility queries to determine the data availability for a specific research question. Given the heterogeneity of different query languages to access different data across and even within standards such as FHIR (eg, CQL and FHIR Search), creating an intermediate query syntax for feasibility queries reduces the complexity of query translation and improves interoperability across different research repositories and query languages. Objective: This study describes the creation and implementation of an intermediate query syntax for feasibility queries and how it integrates into the federated German health research portal (Forschungsdatenportal Gesundheit) and the MII. Methods: We analyzed the requirements for feasibility queries and the feasibility tools that are currently available in research repositories. Based on this analysis, we developed an intermediate query syntax that can be easily translated into different research repository–specific query languages. Results: The resulting Clinical Cohort Definition Language (CCDL) for feasibility queries combines inclusion criteria in a conjunctive normal form and exclusion criteria in a disjunctive normal form, allowing for additional filters like time or numerical restrictions. The inclusion and exclusion results are combined via an expression to specify feasibility queries. We defined a JSON schema for the CCDL, generated an ontology, and demonstrated the use and translatability of the CCDL across multiple studies and real-world use cases. Conclusions: We developed and evaluated a structured query syntax for feasibility queries and demonstrated its use in a real-world example as part of a research platform across 39 German university hospitals. %R 10.2196/58541 %U https://medinform.jmir.org/2024/1/e58541 %U https://doi.org/10.2196/58541 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e56263 %T Health Care Worker Usage of Large-Scale Health Information Exchanges in Japan: User-Level Audit Log Analysis Study %A Suzumoto,Jun %A Mori,Yukiko %A Kuroda,Tomohiro %K health information exchange %K audit log %K Japan %K HIE %K audit %K logs %K usage %K medical informatics %K rate %K hospitals %K electronic health record %D 2024 %7 9.10.2024 %9 %J JMIR Med Inform %G English %X Background: Over 200 health information exchanges (HIEs) are currently operational in Japan. The most common feature of HIEs is remote on-demand viewing or searching of aggregated patient health data from multiple institutions. However, the usage of this feature by individual users and institutions remains unknown. Objective: This study aims to understand usage of the on-demand patient data viewing feature of large-scale HIEs by individual health care workers and institutions in Japan. Methods: We conducted audit log analyses of large-scale HIEs. The research subjects were HIEs connected to over 100 institutions and with over 10,000 patients. Each health care worker’s profile and audit log data for HIEs were collected. We conducted four types of analyses on the extracted audit log. First, we calculated the ratio of the number of days of active HIE use for each hospital-affiliated doctor account. Second, we calculated cumulative monthly usage days of HIEs by each institution in financial year (FY) 2021/22. Third, we calculated each facility type’s monthly active institution ratio in FY2021/22. Fourth, we compared the monthly active institution ratio by medical institution for each HIE and the proportion of cumulative usage days by user type for each HIE. Results: We identified 24 HIEs as candidates for data collection and we analyzed data from 7 HIEs. Among hospital doctors, 93.5% (7326/7833) had never used HIEs during the available period in FY2021/22, while 19 doctors used them at least 30% of days. The median (IQR) monthly active institution ratios were 0.482 (0.470‐0.487) for hospitals, 0.243 (0.230‐0.247) for medical clinics, and 0.030 (0.024‐0.048) for dental clinics. In 51.9% (1781/3434) of hospitals, the cumulative monthly usage days of HIEs was 0, while in 26.8% (921/3434) of hospitals, it was between 1 and 10, and in 3% (103/3434) of hospitals, it was 100 or more. The median (IQR) monthly active institution ratio in medical institutions was 0.511 (0.487‐0.529) for the most used HIE and 0.109 (0.0927‐0.117) for the least used. The proportion of cumulative usage days of HIE by user type was complex for each HIE, and no consistent trends could be discerned. Conclusions: In the large-scale HIEs surveyed in this study, the overall usage of the on-demand patient data viewing feature was low, consistent with past official reports. User-level analyses of audit logs revealed large disparities in the number of days of HIE use among health care workers and institutions. There were also large disparities in HIE use by facility type or HIE; the percentage of cumulative HIE usage days by user type also differed by HIE. This study indicates the need for further research into why there are large disparities in demand for HIEs in Japan as well as the need to design comprehensive audit logs that can be matched with other official datasets. %R 10.2196/56263 %U https://medinform.jmir.org/2024/1/e56263 %U https://doi.org/10.2196/56263 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e57183 %T Outcomes of Patients With Early and Locally Advanced Lung Cancer: Protocol for the Italian Lung Cancer Observational Study (LUCENT) %A Bertolaccini,Luca %A Ciani,Oriana %A Lucchi,Marco %A Zaraca,Francesco %A Bertani,Alessandro %A Crisci,Roberto %A Spaggiari,Lorenzo %A , %+ Department of Thoracic Surgery, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, Milan, 20141, Italy, 39 0257489665, luca.bertolaccini@gmail.com %K lung cancer %K quality of life %K observational study %K economic aspects %K multicenter study %D 2024 %7 8.10.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Lung cancer, predominantly non-small cell lung cancer (NSCLC), remains a formidable challenge, necessitating an in-depth understanding of evolving treatment paradigms. The Italian Lung Cancer Observational Study (LUCENT) addresses this need by investigating the outcomes of patients with early and locally advanced lung cancer in Italy. Objective: With a focus on real-world data and patient registries, this study aims to provide comprehensive insights into clinical, psychosocial, and economic impacts, contributing to informed decision-making in health care. Methods: LUCENT is a prospective observational multicenter cohort study enrolling patients eligible for minimally invasive manual, robot-assisted, or traditional open surgery. The study will develop a web-based registry to collect longitudinal surgical, oncological, and socioeconomic outcome data. The primary objectives include performance assessment through the establishment of national benchmarks based on risk-adjusted outcomes and processes of care indicators. The secondary objectives encompass economic and psychosocial impact assessments of innovative technologies and treatment pathways. The multicenter design ensures a diverse and representative study population. Results: The evolving landscape of NSCLC treatment necessitates a nuanced approach with consideration of the dynamic shifts in therapeutic strategies. LUCENT strives to fill existing knowledge gaps by providing a platform for collecting and analyzing real-world data, emphasizing the importance of patient-reported outcomes in enhancing the understanding of the disease. By developing a web-based registry, the study not only facilitates efficient data collection but also addresses the limitations of traditional methods, such as suboptimal response rates and costs associated with paper-and-pencil questionnaires. Recruitment will be conducted from January 01, 2024, to December 31, 2026. Follow-up will be performed for a minimum of 2 years. The study will be completed in the year 2028. Conclusions: LUCENT’s potential implications are substantial. Establishing national benchmarks will enable a thorough evaluation of outcomes and care processes, guiding clinicians and policymakers in optimizing patient management. Furthermore, the study’s secondary objectives, focusing on economic and psychosocial impacts, align with the contemporary emphasis on holistic cancer care. Insights gained from this study may influence treatment strategies, resource utilization, and patient well-being, thereby contributing to the ongoing refinement of lung cancer management. Trial Registration: ClinicalTrials.gov NCT05851755; https://clinicaltrials.gov/study/NCT05851755. ISRCTN 67197140; https://www.isrctn.com/ISRCTN67197140 International Registered Report Identifier (IRRID): PRR1-10.2196/57183 %R 10.2196/57183 %U https://www.researchprotocols.org/2024/1/e57183 %U https://doi.org/10.2196/57183 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 13 %N %P e51563 %T Unlocking the Potential of Secondary Data for Public Health Research: Retrospective Study With a Novel Clinical Platform %A Gundler,Christopher %A Gottfried,Karl %A Wiederhold,Alexander Johannes %A Ataian,Maximilian %A Wurlitzer,Marcus %A Gewehr,Jan Erik %A Ückert,Frank %+ Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, Hamburg, 20246, Germany, 49 40741054979, c.gundler@uke.de %K secondary use %K hypothesis testing %K research platform %K clinical data %K Parkinson disease %K data %K health-related research %K health data %K electronic health record %K EHR %K tremor %D 2024 %7 1.10.2024 %9 Original Paper %J Interact J Med Res %G English %X Background: Clinical routine data derived from university hospitals hold immense value for health-related research on large cohorts. However, using secondary data for hypothesis testing necessitates adherence to scientific, legal (such as the General Data Protection Regulation, federal and state protection legislations), technical, and administrative requirements. This process is intricate, time-consuming, and susceptible to errors. Objective: This study aims to develop a platform that enables clinicians to use current real-world data for testing research and evaluate advantages and limitations at a large university medical center (542,944 patients in 2022). Methods: We identified requirements from clinical practitioners, conceptualized and implemented a platform based on the existing components, and assessed its applicability in clinical reality quantitatively and qualitatively. Results: The proposed platform was established at the University Medical Center Hamburg-Eppendorf and made 639 forms encompassing 10,629 data elements accessible to all resident scientists and clinicians. Every day, the number of patients rises, and parts of their electronic health records are made accessible through the platform. Qualitatively, we were able to conduct a retrospective analysis of Parkinson disease over 777 patients, where we provide additional evidence for a significantly higher proportion of action tremors in patients with rest tremors (340/777, 43.8%) compared with those without rest tremors (255/777, 32.8%), as determined by a chi-square test (P<.001). Quantitatively, our findings demonstrate increased user engagement within the last 90 days, underscoring clinicians’ increasing adoption of the platform in their regular research activities. Notably, the platform facilitated the retrieval of clinical data from 600,000 patients, emphasizing its substantial added value. Conclusions: This study demonstrates the feasibility of simplifying the use of clinical data to enhance exploration and sustainability in scientific research. The proposed platform emerges as a potential technological and legal framework for other medical centers, providing them with the means to unlock untapped potential within their routine data. %M 39353185 %R 10.2196/51563 %U https://www.i-jmr.org/2024/1/e51563 %U https://doi.org/10.2196/51563 %U http://www.ncbi.nlm.nih.gov/pubmed/39353185 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60293 %T Toward Better Semantic Interoperability of Data Element Repositories in Medicine: Analysis Study %A Hu,Zhengyong %A Wang,Anran %A Duan,Yifan %A Zhou,Jiayin %A Hu,Wanfei %A Wu,Sizhu %+ Institute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 3 Yabao Road, Chaoyang District, Beijing, 100020, China, 86 52328760, Wu.sizhu@imicams.ac.cn %K data element repository %K FAIR %K ISO/IEC 11179 %K metadata %K semantic interoperability %D 2024 %7 30.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Data element repositories facilitate high-quality medical data sharing by standardizing data and enhancing semantic interoperability. However, the application of repositories is confined to specific projects and institutions. Objective: This study aims to explore potential issues and promote broader application of data element repositories within the medical field by evaluating and analyzing typical repositories. Methods: Following the inclusion of 5 data element repositories through a literature review, a novel analysis framework consisting of 7 dimensions and 36 secondary indicators was constructed and used for evaluation and analysis. Results: The study’s results delineate the unique characteristics of different repositories and uncover specific issues in their construction. These issues include the absence of data reuse protocols and insufficient information regarding the application scenarios and efficacy of data elements. The repositories fully comply with only 45% (9/20) of the subprinciples for Findable and Reusable in the FAIR principle, while achieving a 90% (19/20 subprinciples) compliance rate for Accessible and 67% (10/15 subprinciples) for Interoperable. Conclusions: The recommendations proposed in this study address the issues to improve the construction and application of repositories, offering valuable insights to data managers, computer experts, and other pertinent stakeholders. %M 39348178 %R 10.2196/60293 %U https://medinform.jmir.org/2024/1/e60293 %U https://doi.org/10.2196/60293 %U http://www.ncbi.nlm.nih.gov/pubmed/39348178 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 16 %N %P e53370 %T Harnessing Generalizable Real-World Ophthalmic Big Data: Descriptive Analysis of the Bodhya Eye Consortium Model for Collaborative Research %A Sood,Ishaana %A Sabherwal,Shalinder %A Mathur,Umang %A Jain,Elesh %A Bhadauria,Madhu %A Agrawal,Deepshikha %A Khurana,Ashi %A Mittal,Vikas %A Mahindrakar,Avinash %A Govindahari,Vishal %A Kulkarni,Sucheta %A Nischal,Ken K %+ Division of Pediatric Ophthalmology, Strabismus, and Adult Motility, UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA, 15224, United States, 1 4125083784, nischalkk@upmc.edu %K anthropological and genomic heterogeneity %K big data %K consortium %K collaborative research %K generalizability %K global health impact %K North India %D 2024 %7 30.9.2024 %9 Original Paper %J Online J Public Health Inform %G English %X Background: Eye care organizations and professionals worldwide are increasingly focusing on bridging the gap between population health and medical practice. Recent advances in genomics and anthropology have revealed that most Indian groups trace their ancestry to a blend of 2 genetically distinct populations: Ancestral North Indians, who share genetic affinities with Central Asians, Middle Easterners, Caucasians, and Europeans; and Ancestral South Indians, genetically distinct from groups outside the Indian subcontinent. Studies conducted among North Indian populations can therefore offer insights that are potentially applicable to these diverse global populations, underscoring significant implications for global health. Objective: The Bodhya Eye Consortium is a collaboration among 8 high-volume nonprofit eyecare organizations from across North India. The consortium aims to harness real-world data consistently and with assured quality for collaborative research. This paper outlines the formation of the consortium as a proposed model for controlled collaborative research among the leading eyecare organizations of North India. Methods: We detail the creation and effective implementation of a consortium following a structured road map that included planning and assessment, establishing an exploratory task force, defining specialty areas, setting objectives and priorities, and conducting a SWOT (strengths, weaknesses, opportunities, and threats) analysis. Central to this process was a comprehensive data audit aimed at standardizing data collection across all participating organizations. Results: The consortium currently comprises 9 organizations, each represented in the governance structure by the Governing Council. Scientific standards for published research are established and overseen by the Scientific Committee, while the Conflict Resolution Committee manages any unresolved disputes. The consortium’s working groups, organized by various eyecare specialties, collaborate on research projects through virtual interactions. A foundational step in this process was the organizationwide data audit, which revealed that most organizations complied with accurate and standardized data collection practices. Organizations with deficiencies in data completeness developed action plans to address them. Subsequently, the consortium adopted data collection proformas, contributing to the publication of high-quality manuscripts characterized by low dropout rates. Conclusions: The collaborative research conducted by the Bodhya Eye Consortium—a group of high-volume eyecare organizations primarily from North India—offers a unique opportunity to contribute to scientific knowledge across various domains of eyecare. By leveraging the established heterogeneity of anthropological and genomic origins within the population, the findings can be generalizable, to some extent, to European, Middle Eastern, and European American populations. This access to potentially invaluable, generalizable data has significant global health implications and opens possibilities for broader collaboration. The model outlined in this descriptive paper can serve as a blueprint for other health care organizations looking to develop similar collaborations for research and knowledge sharing. %M 39348171 %R 10.2196/53370 %U https://ojphi.jmir.org/2024/1/e53370 %U https://doi.org/10.2196/53370 %U http://www.ncbi.nlm.nih.gov/pubmed/39348171 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e59392 %T Development of a Cohort Analytics Tool for Monitoring Progression Patterns in Cardiovascular Diseases: Advanced Stochastic Modeling Approach %A Brahma,Arindam %A Chatterjee,Samir %A Seal,Kala %A Fitzpatrick,Ben %A Tao,Youyou %+ Department of Information Systems and Business Analytics, College of Business, Loyola Marymount University, 1 LMU Drive, Los Angeles, CA, 90045, United States, 1 9493021030, arin.brahma@lmu.edu %K healthcare analytics %K eHealth %K disease monitoring %K cardiovascular disease %K disease progression model %K myocardial %K stroke %K decision support %K continuous-time Markov chain model %K stochastic model %K stochastic %K Markov %K cardiology %K cardiovascular %K heart %K monitoring %K progression %D 2024 %7 24.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: The World Health Organization (WHO) reported that cardiovascular diseases (CVDs) are the leading cause of death worldwide. CVDs are chronic, with complex progression patterns involving episodes of comorbidities and multimorbidities. When dealing with chronic diseases, physicians often adopt a “watchful waiting” strategy, and actions are postponed until information is available. Population-level transition probabilities and progression patterns can be revealed by applying time-variant stochastic modeling methods to longitudinal patient data from cohort studies. Inputs from CVD practitioners indicate that tools to generate and visualize cohort transition patterns have many impactful clinical applications. The resultant computational model can be embedded in digital decision support tools for clinicians. However, to date, no study has attempted to accomplish this for CVDs. Objective: This study aims to apply advanced stochastic modeling methods to uncover the transition probabilities and progression patterns from longitudinal episodic data of patient cohorts with CVD and thereafter use the computational model to build a digital clinical cohort analytics artifact demonstrating the actionability of such models. Methods: Our data were sourced from 9 epidemiological cohort studies by the National Heart Lung and Blood Institute and comprised chronological records of 1274 patients associated with 4839 CVD episodes across 16 years. We then used the continuous-time Markov chain method to develop our model, which offers a robust approach to time-variant transitions between disease states in chronic diseases. Results: Our study presents time-variant transition probabilities of CVD state changes, revealing patterns of CVD progression against time. We found that the transition from myocardial infarction (MI) to stroke has the fastest transition rate (mean transition time 3, SD 0 days, because only 1 patient had a MI-to-stroke transition in the dataset), and the transition from MI to angina is the slowest (mean transition time 1457, SD 1449 days). Congestive heart failure is the most probable first episode (371/840, 44.2%), followed by stroke (216/840, 25.7%). The resultant artifact is actionable as it can act as an eHealth cohort analytics tool, helping physicians gain insights into treatment and intervention strategies. Through expert panel interviews and surveys, we found 9 application use cases of our model. Conclusions: Past research does not provide actionable cohort-level decision support tools based on a comprehensive, 10-state, continuous-time Markov chain model to unveil complex CVD progression patterns from real-world patient data and support clinical decision-making. This paper aims to address this crucial limitation. Our stochastic model–embedded artifact can help clinicians in efficient disease monitoring and intervention decisions, guided by objective data-driven insights from real patient data. Furthermore, the proposed model can unveil progression patterns of any chronic disease of interest by inputting only 3 data elements: a synthetic patient identifier, episode name, and episode time in days from a baseline date. %M 39316426 %R 10.2196/59392 %U https://medinform.jmir.org/2024/1/e59392 %U https://doi.org/10.2196/59392 %U http://www.ncbi.nlm.nih.gov/pubmed/39316426 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58977 %T Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study %A Nishiyama,Tomohiro %A Yamaguchi,Ayane %A Han,Peitao %A Pereira,Lis Weiji Kanashiro %A Otsuki,Yuka %A Andrade,Gabriel Herman Bernardim %A Kudo,Noriko %A Yada,Shuntaro %A Wakamiya,Shoko %A Aramaki,Eiji %A Takada,Masahiro %A Toi,Masakazu %+ Department of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, 630-0192, Japan, 81 743 72 5250, aramaki@is.naist.jp %K natural language processing %K named entity recognition %K adverse drug reaction %K adverse event %K peripheral neuropathy %K NLP %K symptoms %K symptom %K machine learning %K ML %K drug %K drugs %K pharmacology %K pharmacotherapy %K pharmaceutic %K pharmaceutics %K pharmaceuticals %K pharmaceutical %K medication %K medications %K adverse %K neuropathy %K cancer %K oncology %K text %K texts %K textual %K note %K notes %K report %K reports %K EHR %K EHRs %K record %K records %K detect %K detection %K detecting %D 2024 %7 24.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse drug event (ADE) signals. As different aspects of a patient’s status are stored in different types of documents, we propose an NLP system capable of processing 6 types of documents: physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. Objective: This study aimed to investigate the system’s performance in detecting ADEs by evaluating the results from multitype texts. The main objective is to detect adverse events accurately using an NLP system. Methods: We used data written in Japanese from 2289 patients with breast cancer, including medication data, physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. Our system performs 3 processes: named entity recognition, normalization of symptoms, and aggregation of multiple types of documents from multiple patients. Among all patients with breast cancer, 103 and 112 with peripheral neuropathy (PN) received paclitaxel or docetaxel, respectively. We evaluate the utility of using multiple types of documents by correlation coefficient and regression analysis to compare their performance with each single type of document. All evaluations of detection rates with our system are performed 30 days after drug administration. Results: Our system underestimates by 13.3 percentage points (74.0%−60.7%), as the incidence of paclitaxel-induced PN was 60.7%, compared with 74.0% in the previous research based on manual extraction. The Pearson correlation coefficient between the manual extraction and system results was 0.87 Although the pharmacist progress notes had the highest detection rate among each type of document, the rate did not match the performance using all documents. The estimated median duration of PN with paclitaxel was 92 days, whereas the previously reported median duration of PN with paclitaxel was 727 days. The number of events detected in each document was highest in the physician’s progress notes, followed by the pharmacist’s and nursing records. Conclusions: Considering the inherent cost that requires constant monitoring of the patient’s condition, such as the treatment of PN, our system has a significant advantage in that it can immediately estimate the treatment duration without fine-tuning a new NLP model. Leveraging multitype documents is better than using single-type documents to improve detection performance. Although the onset time estimation was relatively accurate, the duration might have been influenced by the length of the data follow-up period. The results suggest that our method using various types of data can detect more ADEs from clinical documents. %M 39316418 %R 10.2196/58977 %U https://medinform.jmir.org/2024/1/e58977 %U https://doi.org/10.2196/58977 %U http://www.ncbi.nlm.nih.gov/pubmed/39316418 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58445 %T State-of-the-Art Fast Healthcare Interoperability Resources (FHIR)–Based Data Model and Structure Implementations: Systematic Scoping Review %A Tabari,Parinaz %A Costagliola,Gennaro %A De Rosa,Mattia %A Boeker,Martin %+ Department of Informatics, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, Italy, 39 089 963319, ptabari@unisa.it %K data model %K Fast Healthcare Interoperability Resources %K FHIR %K interoperability %K modeling %K PRISMA %D 2024 %7 24.9.2024 %9 Review %J JMIR Med Inform %G English %X Background: Data models are crucial for clinical research as they enable researchers to fully use the vast amount of clinical data stored in medical systems. Standardized data and well-defined relationships between data points are necessary to guarantee semantic interoperability. Using the Fast Healthcare Interoperability Resources (FHIR) standard for clinical data representation would be a practical methodology to enhance and accelerate interoperability and data availability for research. Objective: This research aims to provide a comprehensive overview of the state-of-the-art and current landscape in FHIR-based data models and structures. In addition, we intend to identify and discuss the tools, resources, limitations, and other critical aspects mentioned in the selected research papers. Methods: To ensure the extraction of reliable results, we followed the instructions of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We analyzed the indexed articles in PubMed, Scopus, Web of Science, IEEE Xplore, the ACM Digital Library, and Google Scholar. After identifying, extracting, and assessing the quality and relevance of the articles, we synthesized the extracted data to identify common patterns, themes, and variations in the use of FHIR-based data models and structures across different studies. Results: On the basis of the reviewed articles, we could identify 2 main themes: dynamic (pipeline-based) and static data models. The articles were also categorized into health care use cases, including chronic diseases, COVID-19 and infectious diseases, cancer research, acute or intensive care, random and general medical notes, and other conditions. Furthermore, we summarized the important or common tools and approaches of the selected papers. These items included FHIR-based tools and frameworks, machine learning approaches, and data storage and security. The most common resource was “Observation” followed by “Condition” and “Patient.” The limitations and challenges of developing data models were categorized based on the issues of data integration, interoperability, standardization, performance, and scalability or generalizability. Conclusions: FHIR serves as a highly promising interoperability standard for developing real-world health care apps. The implementation of FHIR modeling for electronic health record data facilitates the integration, transmission, and analysis of data while also advancing translational research and phenotyping. Generally, FHIR-based exports of local data repositories improve data interoperability for systems and data warehouses across different settings. However, ongoing efforts to address existing limitations and challenges are essential for the successful implementation and integration of FHIR data models. %M 39316433 %R 10.2196/58445 %U https://medinform.jmir.org/2024/1/e58445 %U https://doi.org/10.2196/58445 %U http://www.ncbi.nlm.nih.gov/pubmed/39316433 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 13 %N %P e53821 %T Emerging Indications for Hyperbaric Oxygen Treatment: Registry Cohort Study %A Tanaka,Hideaki L %A Rees,Judy R %A Zhang,Ziyin %A Ptak,Judy A %A Hannigan,Pamela M %A Silverman,Elaine M %A Peacock,Janet L %A Buckey,Jay C %A , %+ Geisel School of Medicine, Dartmouth College, 1 Medical Center Drive, Lebanon, NH, 03756, United States, 1 603 646 5328, jay.buckey@dartmouth.edu %K hyperbaric oxygen %K inflammatory bowel disease %K calciphylaxis %K post–COVID-19 condition %K PCC %K postacute sequelae of COVID-19 %K PASC %K infected implanted hardware %K hypospadias %K frostbite %K facial filler %K pyoderma gangrenosum %D 2024 %7 20.8.2024 %9 Original Paper %J Interact J Med Res %G English %X Background: Hyperbaric oxygen (HBO2) treatment is used across a range of medical specialties for a variety of applications, particularly where hypoxia and inflammation are important contributors. Because of its hypoxia-relieving and anti-inflammatory effects HBO2 may be useful for new indications not currently approved by the Undersea and Hyperbaric Medical Society. Identifying these new applications for HBO2 is difficult because individual centers may only treat a few cases and not track the outcomes consistently. The web-based International Multicenter Registry for Hyperbaric Oxygen Therapy captures prospective outcome data for patients treated with HBO2 therapy. These data can then be used to identify new potential applications for HBO2, which has relevance for a range of medical specialties. Objective: Although hyperbaric medicine has established indications, new ones continue to emerge. One objective of this registry study was to identify cases where HBO2 has been used for conditions falling outside of current Undersea and Hyperbaric Medical Society–approved indications and present outcome data for them. Methods: This descriptive study used data from a web-based, multicenter, international registry of patients treated with HBO2. Participating centers agree to collect data on all patients treated using standard outcome measures, and individual centers send deidentified data to the central registry. HBO2 treatment programs in the United States, the United Kingdom, and Australia participate. Demographic, outcome, complication, and treatment data, including pre- and posttreatment quality of life questionnaires (EQ-5D-5L) were collected for individuals referred for HBO2 treatment. Results: Out of 9726 patient entries, 378 (3.89%) individuals were treated for 45 emerging indications. Post–COVID-19 condition (PCC; also known as postacute sequelae of COVID-19; 149/378, 39.4%), ulcerative colitis (47/378, 12.4%), and Crohn disease (40/378, 10.6%) accounted for 62.4% (n=236) of the total cases. Calciphylaxis (20/378, 5.3%), frostbite (18/378, 4.8%), and peripheral vascular disease–related wounds (12/378, 3.2%) accounted for a further 13.2% (n=50). Patients with PCC reported significant improvement on the Neurobehavioral Symptom Inventory (NSI score: pretreatment=30.6; posttreatment=14.4; P<.001). Patients with Crohn disease reported significantly improved quality of life (EQ-5D score: pretreatment=53.8; posttreatment=68.8), and 5 (13%) reported closing a fistula. Patients with ulcerative colitis and complete pre- and post-HBO2 data reported improved quality of life and lower scores on a bowel questionnaire examining frequency, blood, pain, and urgency. A subset of patients with calciphylaxis and arterial ulcers also reported improvement. Conclusions: HBO2 is being used for a wide range of possible applications across various medical specialties for its hypoxia-relieving and anti-inflammatory effects. Results show statistically significant improvements in patient-reported outcomes for inflammatory bowel disease and PCC. HBO2 is also being used for frostbite, pyoderma gangrenosum, pterygium, hypospadias repair, and facial filler procedures. Other indications show evidence for improvement, and the case series for all indications is growing in the registry. International Registered Report Identifier (IRRID): RR2-10.2196/18857 %M 39078624 %R 10.2196/53821 %U https://www.i-jmr.org/2024/1/e53821 %U https://doi.org/10.2196/53821 %U http://www.ncbi.nlm.nih.gov/pubmed/39078624 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e55657 %T Exploring Cancer Incidence Trends by Age and Sex Among 14.14 Million Individuals in China From 2007 to 2021: Population-Based Study %A Yuan,Yingchao %A Liu,Chang %A Guo,Moning %A Xin,Zhong %A Chen,Guanjie %A Yang,Yue %A Zheng,Jianpeng %A Zang,Bai %A Yang,Jinkui %+ Beijing Key Laboratory of Diabetes Research and Care, Department of Endocrinology and Metabolism, Beijing Diabetes Institute, Beijing Tongren Hospital, Capital Medical University, No.1 Dong Jiao Min Xiang, Beijing, 100730, China, 86 010 58268437, jkyang@ccmu.edu.cn %K cancer %K incidence %K trend %K sex-based %K women %D 2024 %7 7.8.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Sex is a crucial factor in the development, progression, and treatment of cancer, making it vital to examine cancer incidence trends by sex for effective prevention strategies. Objective: This study aimed to assess the incidence of cancer in China between 2007 and 2021, with a focus on sex-based trends. Methods: A population-based cancer registry comprising 14.14 million individuals was maintained between 2007 and 2021 by the Beijing Municipal Health Big Data and Policy Research Center. The age-standardized rates (ASRs) of cancers were calculated using the Segi population. The average annual percentage of change (AAPC) was evaluated using the joinpoint regression model, while the Bayesian age-period-cohort model was used to predict cancer incidence in the next 10 years. Results: From 2007 to 2021, the study included 651,342 incident patients with cancer, of whom 51.2% (n=333,577) were women. The incidence indicated by the ASR for all cancers combined was 200.8 per 100,000 for women and 184.4 per 100,000 for men. The increase in incidence indicated by AAPC for all malignancies combined significantly increased in women between 2007 and 2021 (AAPC=3.1%; P<.001), whereas it remained constant in men (AAPC=0.3%; P=.30). Although the overall incidence of all cancers indicated by AAPC increased in young men (AAPC=3.2%; P=.01), the greatest increase was observed among young women (AAPC=6.1%; P<.001). The incidence rate ratio for cancer in women increased among subsequent younger generations compared with patients born in the 1962-1966 cohort. The ASR in women will increase 1.6-fold over the next 10 years, with women having twice the incidence rate of men by 2031. Conclusions: The rising incidence of cancer among women in China has become a growing concern, emphasizing the need for increased efforts in cancer prevention and early screening, especially among young women. %M 39110964 %R 10.2196/55657 %U https://publichealth.jmir.org/2024/1/e55657 %U https://doi.org/10.2196/55657 %U http://www.ncbi.nlm.nih.gov/pubmed/39110964 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e59187 %T Integrating Clinical Data and Medical Imaging in Lung Cancer: Feasibility Study Using the Observational Medical Outcomes Partnership Common Data Model Extension %A Ji,Hyerim %A Kim,Seok %A Sunwoo,Leonard %A Jang,Sowon %A Lee,Ho-Young %A Yoo,Sooyoung %+ Office of eHealth Research and Business, Seoul National University Bundang Hospital, 172, Dolma-ro, Bundang-gu, Seongnam-si, 13605, Republic of Korea, 82 317878980, yoosoo0@snubh.org %K DICOM %K OMOP %K CDM %K lung cancer %K medical imaging %K data integration %K data quality %K Common Data Model %K Digital Imaging and Communications in Medicine %K Observational Medical Outcomes Partnership %D 2024 %7 12.7.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Digital transformation, particularly the integration of medical imaging with clinical data, is vital in personalized medicine. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardizes health data. However, integrating medical imaging remains a challenge. Objective: This study proposes a method for combining medical imaging data with the OMOP CDM to improve multimodal research. Methods: Our approach included the analysis and selection of digital imaging and communications in medicine header tags, validation of data formats, and alignment according to the OMOP CDM framework. The Fast Healthcare Interoperability Resources ImagingStudy profile guided our consistency in column naming and definitions. Imaging Common Data Model (I-CDM), constructed using the entity-attribute-value model, facilitates scalable and efficient medical imaging data management. For patients with lung cancer diagnosed between 2010 and 2017, we introduced 4 new tables—IMAGING_STUDY, IMAGING_SERIES, IMAGING_ANNOTATION, and FILEPATH—to standardize various imaging-related data and link to clinical data. Results: This framework underscores the effectiveness of I-CDM in enhancing our understanding of lung cancer diagnostics and treatment strategies. The implementation of the I-CDM tables enabled the structured organization of a comprehensive data set, including 282,098 IMAGING_STUDY, 5,674,425 IMAGING_SERIES, and 48,536 IMAGING_ANNOTATION records, illustrating the extensive scope and depth of the approach. A scenario-based analysis using actual data from patients with lung cancer underscored the feasibility of our approach. A data quality check applying 44 specific rules confirmed the high integrity of the constructed data set, with all checks successfully passed, underscoring the reliability of our findings. Conclusions: These findings indicate that I-CDM can improve the integration and analysis of medical imaging and clinical data. By addressing the challenges in data standardization and management, our approach contributes toward enhancing diagnostics and treatment strategies. Future research should expand the application of I-CDM to diverse disease populations and explore its wide-ranging utility for medical conditions. %M 38996330 %R 10.2196/59187 %U https://medinform.jmir.org/2024/1/e59187 %U https://doi.org/10.2196/59187 %U http://www.ncbi.nlm.nih.gov/pubmed/38996330 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e49785 %T User Preferences and Needs for Health Data Collection Using Research Electronic Data Capture: Survey Study %A Soni,Hiral %A Ivanova,Julia %A Wilczewski,Hattie %A Ong,Triton %A Ross,J Nalubega %A Bailey,Alexandra %A Cummins,Mollie %A Barrera,Janelle %A Bunnell,Brian %A Welch,Brandon %+ Doxy.me Research, Doxy.me Inc, 18 Broad Street, 3rd Floor, Suite 6 and 7, Charleston, SC, 29401, United States, 1 8444369963, sonihiralc@gmail.com %K Research Electronic Data Capture %K REDCap %K user experience %K electronic data collection %K health data %K personal health information %K clinical research %K mobile phone %D 2024 %7 25.6.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied. Objective: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool. Methods: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap’s data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience. Results: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes). Conclusions: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap’s data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients. %M 38917448 %R 10.2196/49785 %U https://medinform.jmir.org/2024/1/e49785 %U https://doi.org/10.2196/49785 %U http://www.ncbi.nlm.nih.gov/pubmed/38917448 %0 Journal Article %@ 2291-9694 %I %V 12 %N %P e55118 %T Comparison of Synthetic Data Generation Techniques for Control Group Survival Data in Oncology Clinical Trials: Simulation Study %A Akiya,Ippei %A Ishihara,Takuma %A Yamamoto,Keiichi %K oncology clinical trial %K survival analysis %K synthetic patient data %K machine learning %K SPD %K simulation %D 2024 %7 18.6.2024 %9 %J JMIR Med Inform %G English %X Background: Synthetic patient data (SPD) generation for survival analysis in oncology trials holds significant potential for accelerating clinical development. Various machine learning methods, including classification and regression trees (CART), random forest (RF), Bayesian network (BN), and conditional tabular generative adversarial network (CTGAN), have been used for this purpose, but their performance in reflecting actual patient survival data remains under investigation. Objective: The aim of this study was to determine the most suitable SPD generation method for oncology trials, specifically focusing on both progression-free survival (PFS) and overall survival (OS), which are the primary evaluation end points in oncology trials. To achieve this goal, we conducted a comparative simulation of 4 generation methods, including CART, RF, BN, and the CTGAN, and the performance of each method was evaluated. Methods: Using multiple clinical trial data sets, 1000 data sets were generated by using each method for each clinical trial data set and evaluated as follows: (1) median survival time (MST) of PFS and OS; (2) hazard ratio distance (HRD), which indicates the similarity between the actual survival function and a synthetic survival function; and (3) visual analysis of Kaplan-Meier (KM) plots. Each method’s ability to mimic the statistical properties of real patient data was evaluated from these multiple angles. Results: In most simulation cases, CART demonstrated the high percentages of MSTs for synthetic data falling within the 95% CI range of the MST of the actual data. These percentages ranged from 88.8% to 98.0% for PFS and from 60.8% to 96.1% for OS. In the evaluation of HRD, CART revealed that HRD values were concentrated at approximately 0.9. Conversely, for the other methods, no consistent trend was observed for either PFS or OS. CART demonstrated better similarity than RF, in that CART caused overfitting and RF (a kind of ensemble learning approach) prevented it. In SPD generation, the statistical properties close to the actual data should be the focus, not a well-generalized prediction model. Both the BN and CTGAN methods cannot accurately reflect the statistical properties of the actual data because small data sets are not suitable. Conclusions: As a method for generating SPD for survival data from small data sets, such as clinical trial data, CART demonstrated to be the most effective method compared to RF, BN, and CTGAN. Additionally, it is possible to improve CART-based generation methods by incorporating feature engineering and other methods in future work. %R 10.2196/55118 %U https://medinform.jmir.org/2024/1/e55118 %U https://doi.org/10.2196/55118 %0 Journal Article %@ 2291-9694 %I %V 12 %N %P e49646 %T A Scalable Pseudonymization Tool for Rapid Deployment in Large Biomedical Research Networks: Development and Evaluation Study %A Abu Attieh,Hammam %A Neves,Diogo Telmo %A Guedes,Mariana %A Mirandola,Massimo %A Dellacasa,Chiara %A Rossi,Elisa %A Prasser,Fabian %K biomedical research %K research network %K data sharing %K data protection %K privacy %K pseudonymization %D 2024 %7 23.4.2024 %9 %J JMIR Med Inform %G English %X Background: The SARS-CoV-2 pandemic has demonstrated once again that rapid collaborative research is essential for the future of biomedicine. Large research networks are needed to collect, share, and reuse data and biosamples to generate collaborative evidence. However, setting up such networks is often complex and time-consuming, as common tools and policies are needed to ensure interoperability and the required flows of data and samples, especially for handling personal data and the associated data protection issues. In biomedical research, pseudonymization detaches directly identifying details from biomedical data and biosamples and connects them using secure identifiers, the so-called pseudonyms. This protects privacy by design but allows the necessary linkage and reidentification. Objective: Although pseudonymization is used in almost every biomedical study, there are currently no pseudonymization tools that can be rapidly deployed across many institutions. Moreover, using centralized services is often not possible, for example, when data are reused and consent for this type of data processing is lacking. We present the ORCHESTRA Pseudonymization Tool (OPT), developed under the umbrella of the ORCHESTRA consortium, which faced exactly these challenges when it came to rapidly establishing a large-scale research network in the context of the rapid pandemic response in Europe. Methods: To overcome challenges caused by the heterogeneity of IT infrastructures across institutions, the OPT was developed based on programmable runtime environments available at practically every institution: office suites. The software is highly configurable and provides many features, from subject and biosample registration to record linkage and the printing of machine-readable codes for labeling biosample tubes. Special care has been taken to ensure that the algorithms implemented are efficient so that the OPT can be used to pseudonymize large data sets, which we demonstrate through a comprehensive evaluation. Results: The OPT is available for Microsoft Office and LibreOffice, so it can be deployed on Windows, Linux, and MacOS. It provides multiuser support and is configurable to meet the needs of different types of research projects. Within the ORCHESTRA research network, the OPT has been successfully deployed at 13 institutions in 11 countries in Europe and beyond. As of June 2023, the software manages data about more than 30,000 subjects and 15,000 biosamples. Over 10,000 labels have been printed. The results of our experimental evaluation show that the OPT offers practical response times for all major functionalities, pseudonymizing 100,000 subjects in 10 seconds using Microsoft Excel and in 54 seconds using LibreOffice. Conclusions: Innovative solutions are needed to make the process of establishing large research networks more efficient. The OPT, which leverages the runtime environment of common office suites, can be used to rapidly deploy pseudonymization and biosample management capabilities across research networks. The tool is highly configurable and available as open-source software. %R 10.2196/49646 %U https://medinform.jmir.org/2024/1/e49646 %U https://doi.org/10.2196/49646 %0 Journal Article %@ 2561-3278 %I JMIR Publications %V 9 %N %P e50175 %T Enhancing Energy Efficiency in Telehealth Internet of Things Systems Through Fog and Cloud Computing Integration: Simulation Study %A Guo,Yunyong %A Ganti,Sudhakar %A Wu,Yi %+ Computer Science Department, University of Victoria, 3800 Finnerty Rd, Victoria, BC, V8P 5C2, Canada, 1 (250) 721 7211, yunyong@uvic.ca %K cloud computing %K energy-efficient %K fog computing %K Internet of Things %K IoT %K telehealth %D 2024 %7 6.3.2024 %9 Original Paper %J JMIR Biomed Eng %G English %X Background: The increasing adoption of telehealth Internet of Things (IoT) devices in health care informatics has led to concerns about energy use and data processing efficiency. Objective: This paper introduces an innovative model that integrates telehealth IoT devices with a fog and cloud computing–based platform, aiming to enhance energy efficiency in telehealth IoT systems. Methods: The proposed model incorporates adaptive energy-saving strategies, localized fog nodes, and a hybrid cloud infrastructure. Simulation analyses were conducted to assess the model’s effectiveness in reducing energy consumption and enhancing data processing efficiency. Results: Simulation results demonstrated significant energy savings, with a 2% reduction in energy consumption achieved through adaptive energy-saving strategies. The sample size for the simulation was 10-40, providing statistical robustness to the findings. Conclusions: The proposed model successfully addresses energy and data processing challenges in telehealth IoT scenarios. By integrating fog computing for local processing and a hybrid cloud infrastructure, substantial energy savings are achieved. Ongoing research will focus on refining the energy conservation model and exploring additional functional enhancements for broader applicability in health care and industrial contexts. %M 38875671 %R 10.2196/50175 %U https://biomedeng.jmir.org/2024/1/e50175 %U https://doi.org/10.2196/50175 %U http://www.ncbi.nlm.nih.gov/pubmed/38875671 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 11 %N %P e48030 %T The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research %A Pirmani,Ashkan %A De Brouwer,Edward %A Geys,Lotte %A Parciak,Tina %A Moreau,Yves %A Peeters,Liesbet M %+ Biomedical Research Institute, Hasselt University, Agoralaan, Building C, Diepenbeek, 3590, Belgium, 32 11 26 92 05, liesbet.peeters@uhasselt.be %K data analysis pipeline %K federated model sharing %K real-world data %K evidence-based decision-making %K end-to-end pipeline %K multiple sclerosis %K data analysis %K pipeline %K data science %K federated %K neurology %K brain %K spine %K spinal nervous system %K neuroscience %K data sharing %K rare %K low prevalence %D 2023 %7 9.11.2023 %9 Original Paper %J JMIR Med Inform %G English %X Background: Investigating low-prevalence diseases such as multiple sclerosis is challenging because of the rather small number of individuals affected by this disease and the scattering of real-world data across numerous data sources. These obstacles impair data integration, standardization, and analysis, which negatively impact the generation of significant meaningful clinical evidence. Objective: This study aims to present a comprehensive, research question–agnostic, multistakeholder-driven end-to-end data analysis pipeline that accommodates 3 prevalent data-sharing streams: individual data sharing, core data set sharing, and federated model sharing. Methods: A demand-driven methodology is employed for standardization, followed by 3 streams of data acquisition, a data quality enhancement process, a data integration procedure, and a concluding analysis stage to fulfill real-world data-sharing requirements. This pipeline’s effectiveness was demonstrated through its successful implementation in the COVID-19 and multiple sclerosis global data sharing initiative. Results: The global data sharing initiative yielded multiple scientific publications and provided extensive worldwide guidance for the community with multiple sclerosis. The pipeline facilitated gathering pertinent data from various sources, accommodating distinct sharing streams and assimilating them into a unified data set for subsequent statistical analysis or secure data examination. This pipeline contributed to the assembly of the largest data set of people with multiple sclerosis infected with COVID-19. Conclusions: The proposed data analysis pipeline exemplifies the potential of global stakeholder collaboration and underlines the significance of evidence-based decision-making. It serves as a paradigm for how data sharing initiatives can propel advancements in health care, emphasizing its adaptability and capacity to address diverse research inquiries. %M 37943585 %R 10.2196/48030 %U https://medinform.jmir.org/2023/1/e48030 %U https://doi.org/10.2196/48030 %U http://www.ncbi.nlm.nih.gov/pubmed/37943585 %0 Journal Article %@ 2291-9694 %I %V 11 %N %P e45523 %T Establishment of a Public Mental Health Database for Research Purposes in the Ferrara Province: Development and Preliminary Evaluation Study %A Ferrara,Maria %A Gentili,Elisabetta %A Belvederi Murri,Martino %A Zese,Riccardo %A Alberti,Marco %A Franchini,Giorgia %A Domenicano,Ilaria %A Folesani,Federica %A Sorio,Cristina %A Benini,Lorenzo %A Carozza,Paola %A Little,Julian %A Grassi,Luigi %K mental health %K psychosis %K epidemiology %K electronic health registry %K health care %K machine learning %K medical health records %K electronic health records %K clinical database %K support %K mental disorder %K social determinants %K mental health care %K resource utilization %D 2023 %7 9.8.2023 %9 %J JMIR Med Inform %G English %X Background: The immediate use of data exported from electronic health records (EHRs) for research is often limited by the necessity to transform data elements into an actual data set. Objective: This paper describes the methodology for establishing a data set that originated from an EHR registry that included clinical, health service, and sociodemographic information. Methods: The Extract, Transform, Load process was applied to raw data collected at the Integrated Department of Mental Health and Pathological Addictions in Ferrara, Italy, from 1925 to February 18, 2021, to build the new, anonymized Ferrara-Psychiatry (FEPSY) database. Information collected before the first EHR was implemented (ie, in 1991) was excluded. An unsupervised cluster analysis was performed to identify patient subgroups to support the proof of concept. Results: The FEPSY database included 3,861,432 records on 46,222 patients. Since 1991, each year, a median of 1404 (IQR 1117.5-1757.7) patients had newly accessed care, and a median of 7300 (IQR 6109.5-9397.5) patients were actively receiving care. Among 38,022 patients with a mental disorder, 2 clusters were identified; the first predominantly included male patients who were aged 25 to 34 years at first presentation and were living with their parents, and the second predominantly included female patients who were aged 35 to 44 years and were living with their own families. Conclusions: The process for building the FEPSY database proved to be robust and replicable with similar health care data, even when they were not originally conceived for research purposes. The FEPSY database will enable future in-depth analyses regarding the epidemiology and social determinants of mental disorders, access to mental health care, and resource utilization. %R 10.2196/45523 %U https://medinform.jmir.org/2023/1/e45523 %U https://doi.org/10.2196/45523 %0 Journal Article %@ 2561-6722 %I %V 6 %N 1 %P e48201 %T Using a Design Thinking Approach to Develop a Social Media–Based Parenting Program for Parents of Children With Attention-Deficit/Hyperactivity Disorder: Mixed Methods Study %A Yam-Ubon,Umaporn %A Thongseiratch,Therdpong %K attention-deficit/hyperactivity disorder %K ADHD %K parenting programs %K human-centered design thinking %K online interventions %K COVID-19 pandemic %K children %K development %K online parenting program %K parenting %K behavior %K support %K feasibility %K social media %K prototype %K testing %K design %D 2023 %7 28.7.2023 %9 %J JMIR Pediatr Parent %G English %X Background: Parenting programs have proven effective in improving the behavior of children with attention-deficit/hyperactivity disorder (ADHD). However, barriers such as job and transportation constraints hinder parents from attending face-to-face therapy appointments. The COVID-19 pandemic has further exacerbated these challenges. Objective: This study aimed to develop and test the feasibility of a social media–based parenting program for parents of children with ADHD, considering both the pre-existing challenges faced by parents and the additional barriers imposed by the COVID-19 pandemic. Methods: This study used a 5-stage design thinking process, encompassing empathizing with parents, defining their needs, ideating innovative solutions, prototyping the program, and testing the program with parents. Qualitative interviews were conducted with 18 parents of children with ADHD to understand their unique needs and values. Brainstorming techniques were used to generate creative ideas, leading to the creation of a prototype that was tested with 32 parents. Participants’ engagement with the program was measured, and posttraining feedback was collected to assess the program’s effectiveness. Results: Parents of children with ADHD encounter specific challenges, including managing impulsive behavior and difficulties in emotion regulation. The social media–based parenting program was delivered through the LINE app (Line Corporation) and consisted of 7 modules addressing topics related to ADHD management and effective parenting strategies. The program exhibited a high completion rate, with 84% (27/32) of participants successfully finishing it. Program provider–participant interaction peaked during the first week and gradually decreased over time. Qualitative feedback indicated that the program was feasible, accessible, and well received by participants. The LINE app was found to be convenient and helpful, and participants preferred content delivery once or twice per week, expressing acceptance for various content formats. Conclusions: This study emphasizes the significance of adopting a human-centered design thinking approach to develop parenting programs that cater to the unique needs and values of parents. By leveraging social media platforms, such as LINE, a parenting program can overcome the challenges posed by the COVID-19 pandemic and other constraints faced by parents. LINE offers a viable and feasible option for supporting parents of children with ADHD, with the potential for customization and widespread dissemination beyond the pandemic context. %R 10.2196/48201 %U https://pediatrics.jmir.org/2023/1/e48201 %U https://doi.org/10.2196/48201 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 9 %N %P e34123 %T Trusted Data Spaces as a Viable and Sustainable Solution for Networks of Population-Based Patient Registries %A Nicholson,Nicholas %A Caldeira,Sandra %A Furtado,Artur %A Nicholl,Ciaran %+ European Commission, Joint Research Centre, via E. Fermi 2749, Ispra, 21027, Italy, 39 0332 78 ext 9365, Nicholas.Nicholson@ec.europa.eu %K population-based patient registries %K trusted research environments %K registry network model %K data federation %K cancer registries %K noncommunicable diseases %D 2023 %7 13.1.2023 %9 Viewpoint %J JMIR Public Health Surveill %G English %X Harmonization and integration of health data remain as the focus of many ongoing efforts toward the goal of optimizing health and health care policies. Population-based patient registries constitute a critical element of these endeavors. Although their main function is monitoring and surveillance of a particular disease within a given population, they are also an important data source for epidemiology. Comparing indicators across national boundaries brings an extra dimension to the use of registry data, especially in regions where supranational initiatives are or could be coordinated to leverage good practices; this is particularly relevant for the European Union. However, strict data protection laws can unintentionally hamper the efforts of data harmonization to ensure the removal of statistical bias in the individual data sets, thereby compromising the integrated value of registries’ data. Consequently, there is the motivation for creating a new paradigm to ensure that registries can operate in an environment that is not unnecessarily restrictive and to allow accurate comparison of data to better ascertain the measures and practices that are most conducive to the public health of societies. The pan-European organizational model of cancer registries, owing to its long and successful establishment, was considered as a sound basis from which to proceed toward such a paradigm. However, it has certain drawbacks, particularly regarding governance, scalability, and resourcing, which are essential elements to consider for a generic patient registry model. These issues are addressed in a proposal of an adapted model that promises a valuable pan-European data resource for epidemiological research, while providing a closely regulated environment for the processing of pseudonymized patient summary data on a broader scale than has hitherto been possible. %M 36637894 %R 10.2196/34123 %U https://publichealth.jmir.org/2023/1/e34123 %U https://doi.org/10.2196/34123 %U http://www.ncbi.nlm.nih.gov/pubmed/36637894 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 12 %P e38922 %T A Privacy-Preserving Distributed Medical Data Integration Security System for Accuracy Assessment of Cancer Screening: Development Study of Novel Data Integration System %A Miyaji,Atsuko %A Watanabe,Kaname %A Takano,Yuuki %A Nakasho,Kazuhisa %A Nakamura,Sho %A Wang,Yuntao %A Narimatsu,Hiroto %+ Cancer Prevention and Control Division, Kanagawa Cancer Center Research Institute, 2-3-2 Nakao, Asahi-ku, Yokohama, 241-8515, Japan, 81 45 520 2222 ext 4020, ka-watanabe@gancen.asahi.yokohama.jp %K data linkage %K data security %K secure data integration %K privacy-preserving linkage %K secure matching privacy-preserving linkage %K private set intersection %K PSI %K privacy-preserving distributed data integration %K PDDI %K big data %K medical informatics %K cancer prevention %K cancer epidemiology %K epidemiological survey %D 2022 %7 30.12.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Big data useful for epidemiological research can be obtained by integrating data corresponding to individuals between databases managed by different institutions. Privacy information must be protected while performing efficient, high-level data matching. Objective: Privacy-preserving distributed data integration (PDDI) enables data matching between multiple databases without moving privacy information; however, its actual implementation requires matching security, accuracy, and performance. Moreover, identifying the optimal data item in the absence of a unique matching key is necessary. We aimed to conduct a basic matching experiment using a model to assess the accuracy of cancer screening. Methods: To experiment with actual data, we created a data set mimicking the cancer screening and registration data in Japan and conducted a matching experiment using a PDDI system between geographically distant institutions. Errors similar to those found empirically in data sets recorded in Japanese were artificially introduced into the data set. The matching-key error rate of the data common to both data sets was set sufficiently higher than expected in the actual database: 85.0% and 59.0% for the data simulating colorectal and breast cancers, respectively. Various combinations of name, gender, date of birth, and address were used for the matching key. To evaluate the matching accuracy, the matching sensitivity and specificity were calculated based on the number of cancer-screening data points, and the effect of matching accuracy on the sensitivity and specificity of cancer screening was estimated based on the obtained values. To evaluate the performance, we measured central processing unit use, memory use, and network traffic. Results: For combinations with a specificity ≥99% and high sensitivity, the date of birth and first name were used in the data simulating colorectal cancer, and the matching sensitivity and specificity were 55.00% and 99.85%, respectively. In the data simulating breast cancer, the date of birth and family name were used, and the matching sensitivity and specificity were 88.71% and 99.98%, respectively. Assuming the sensitivity and specificity of cancer screening at 90%, the apparent values decreased to 74.90% and 89.93%, respectively. A trial calculation was performed using a combination with the same data set and 100% specificity. When the matching sensitivity was 82.26%, the apparent screening sensitivity was maintained at 90%, and the screening specificity decreased to 89.89%. For 214 data points, the execution time was 82 minutes and 26 seconds without parallelization and 11 minutes and 38 seconds with parallelization; 19.33% of the calculation time was for the data-holding institutions. Memory use was 3.4 GB for the PDDI server and 2.7 GB for the data-holding institutions. Conclusions: We demonstrated the rudimentary feasibility of introducing a PDDI system for cancer-screening accuracy assessment. We plan to conduct matching experiments based on actual data and compare them with the existing methods. %M 36583931 %R 10.2196/38922 %U https://medinform.jmir.org/2022/12/e38922 %U https://doi.org/10.2196/38922 %U http://www.ncbi.nlm.nih.gov/pubmed/36583931 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 11 %P e36711 %T Linking Biomedical Data Warehouse Records With the National Mortality Database in France: Large-scale Matching Algorithm %A Guardiolle,Vianney %A Bazoge,Adrien %A Morin,Emmanuel %A Daille,Béatrice %A Toublant,Delphine %A Bouzillé,Guillaume %A Merel,Youenn %A Pierre-Jean,Morgane %A Filiot,Alexandre %A Cuggia,Marc %A Wargny,Matthieu %A Lamer,Antoine %A Gourraud,Pierre-Antoine %+ Univ. Lille, CHU Lille, ULR 2694, METRICS: Évaluation des Technologies de santé et des Pratiques médicales, F-59000, 1 place de Verdun, Lille, 59000, France, 33 320626969, antoine.lamer@univ-lille.fr %K data warehousing %K clinical data warehouse %K medical informatics applications %K medical record linkage %K French National Mortality Database %K data reuse %K open data, R %K clinical informatics %D 2022 %7 1.11.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Often missing from or uncertain in a biomedical data warehouse (BDW), vital status after discharge is central to the value of a BDW in medical research. The French National Mortality Database (FNMD) offers open-source nominative records of every death. Matching large-scale BDWs records with the FNMD combines multiple challenges: absence of unique common identifiers between the 2 databases, names changing over life, clerical errors, and the exponential growth of the number of comparisons to compute. Objective: We aimed to develop a new algorithm for matching BDW records to the FNMD and evaluated its performance. Methods: We developed a deterministic algorithm based on advanced data cleaning and knowledge of the naming system and the Damerau-Levenshtein distance (DLD). The algorithm’s performance was independently assessed using BDW data of 3 university hospitals: Lille, Nantes, and Rennes. Specificity was evaluated with living patients on January 1, 2016 (ie, patients with at least 1 hospital encounter before and after this date). Sensitivity was evaluated with patients recorded as deceased between January 1, 2001, and December 31, 2020. The DLD-based algorithm was compared to a direct matching algorithm with minimal data cleaning as a reference. Results: All centers combined, sensitivity was 11% higher for the DLD-based algorithm (93.3%, 95% CI 92.8-93.9) than for the direct algorithm (82.7%, 95% CI 81.8-83.6; P<.001). Sensitivity was superior for men at 2 centers (Nantes: 87%, 95% CI 85.1-89 vs 83.6%, 95% CI 81.4-85.8; P=.006; Rennes: 98.6%, 95% CI 98.1-99.2 vs 96%, 95% CI 94.9-97.1; P<.001) and for patients born in France at all centers (Nantes: 85.8%, 95% CI 84.3-87.3 vs 74.9%, 95% CI 72.8-77.0; P<.001). The DLD-based algorithm revealed significant differences in sensitivity among centers (Nantes, 85.3% vs Lille and Rennes, 97.3%, P<.001). Specificity was >98% in all subgroups. Our algorithm matched tens of millions of death records from BDWs, with parallel computing capabilities and low RAM requirements. We used the Inseehop open-source R script for this measurement. Conclusions: Overall, sensitivity/recall was 11% higher using the DLD-based algorithm than that using the direct algorithm. This shows the importance of advanced data cleaning and knowledge of a naming system through DLD use. Statistically significant differences in sensitivity between groups could be found and must be considered when performing an analysis to avoid differential biases. Our algorithm, originally conceived for linking a BDW with the FNMD, can be used to match any large-scale databases. While matching operations using names are considered sensitive computational operations, the Inseehop package released here is easy to run on premises, thereby facilitating compliance with cybersecurity local framework. The use of an advanced deterministic matching algorithm such as the DLD-based algorithm is an insightful example of combining open-source external data to improve the usage value of BDWs. %M 36318244 %R 10.2196/36711 %U https://medinform.jmir.org/2022/11/e36711 %U https://doi.org/10.2196/36711 %U http://www.ncbi.nlm.nih.gov/pubmed/36318244 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 9 %P e39746 %T Using Electronic Health Records for the Learning Health System: Creation of a Diabetes Research Registry %A Wells,Brian J %A Downs,Stephen M %A Ostasiewski,Brian %+ Department of Biostatistics and Data Science, Wake Forest University School of Medicine, 1 Medical Center Blvd, Winston Salem, NC, 27157, United States, 1 336 416 5185, bjwells@wakehealth.edu %K electronic health record %K EHR %K Learning Health System %K registry %K diabetes %D 2022 %7 23.9.2022 %9 Viewpoint %J JMIR Med Inform %G English %X Electronic health records (EHRs) were originally developed for clinical care and billing. As such, the data are not collected, organized, and curated in a fashion that is optimized for secondary use to support the Learning Health System. Population health registries provide tools to support quality improvement. These tools are generally integrated with the live EHR, are intended to use a minimum of computing resources, and may not be appropriate for some research projects. Researchers may require different electronic phenotypes and variable definitions from those typically used for population health, and these definitions may vary from study to study. Establishing a formal registry that is mapped to the Observation Medical Outcomes Partnership common data model provides an opportunity to add custom mappings and more easily share these with other institutions. Performing preprocessing tasks such as data cleaning, calculation of risk scores, time-to-event analysis, imputation, and transforming data into a format for statistical analyses will improve efficiency and make the data easier to use for investigators. Research registries that are maintained outside the EHR also have the luxury of using significant computational resources without jeopardizing clinical care data. This paper describes a virtual Diabetes Registry at Atrium Health Wake Forest Baptist and the plan for its continued development. %M 36149742 %R 10.2196/39746 %U https://medinform.jmir.org/2022/9/e39746 %U https://doi.org/10.2196/39746 %U http://www.ncbi.nlm.nih.gov/pubmed/36149742 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 9 %P e21878 %T Design and Rationale of the National Observational Multicentric Tunisian Registry of Hypertension: Protocol for Evaluating Hypertensive Patient Care in Clinical Practice %A Abid,Leila %A Hammami,Rania %A Abdesselem,Salem %A Boudiche,Selim %A Hédi,Ben Slima %A Sayahi,Khaled %A Bahloul,Amine %A Chamtouri,Ikram %A Charfeddine,Salma %A Rais,Lamia %A Drissa,Meriem %A Ben Kaab,Badreddine %A Ibn hadj amor,Hassen %A Ben Fatma,Lilia %A Garbaa,Riadh %A Boukhris,Sabrine %A Emna,Allouche %A Ben Halima,Manel %A Amdouni,Nesrine %A Ghorbel,Shayma %A Soudani,Sabrine %A Khaled,Imen %A Triki,Syrine %A Bouazizi,Feten %A Jemai,Imen %A Abdeljalil,Ouday %A Ammar,Yemna %A Farah,Amani %A Neji,Adnen %A Oumaya,Zeineb %A Seghaier,Sana %A Mokrani,Samir %A Thawaba,Hamza %A Sarray,Hela %A Ouaghlani,Khalil %A Thabet,Houssem %A Mnif,Zeineb %A Fatma,Boujelben Masmoudi %A Sghaier,Mohamed %A Khalifa,Roueida %A Fourati,Sami %A Kammoun,Yassmine %A Abid,Syrine %A Hamza,Chiheb %A Ben Jeddou,Syrine %A Sabbah,Lassaad %A Lakhdhar,Rim %A Dammak,Najla %A Sellami,Tarak %A Herbegue,Basma %A Koubaa,Alia %A Triki,Faten %A Ellouze,Tarek %A Hmoudi,Aicha %A Ben Ameur,Ikhlas %A Boukhchina,Mohamed Mongi %A Abid,Neila %A Ouechtati,Wejdene %A Nasrallah,Nizar %A Houidi,Yousra %A Mghaieth Zghal,Fathia %A Elhem,Ghodhbane %A Chayeb,Mounira %A Sarra,Chenik %A Kaabachi,Samira %A Saadaoui,Nizar %A Ben Ameur,Ines %A Affes,Moufida %A Ouali,Sana %A Chaker,Mouna %A Naana,Hela %A Meriem,Dghim %A Jarrar,Mourad %A Mnif,Jihen %A Turki,Ahmed %A Zairi,Ihsen %A Langar,Jamel %A Dardouri,Safa %A Hachaichi,Imen %A Chettaoui,Rafik %A Smat,Wajih %A Chakroun,Amel %A Mzoughi,Khadija %A Mechmeche,Rachid %A Ben Halima,Afef %A Ben Kahla Koubaa,Sahar %A Chtourou,Slim %A Mohamed abdelkader,Maalej %A Ayari,Mohsen %A Hadrich,Moufid %A Rami,Tlili %A Azaiez,Fares %A Bouhlel,Imen %A Sahnoun,Samir %A Jerbi,Habib %A Imtinene,Ben Mrad %A Riahi,Leila %A Sahnoun,Mohamed %A Ben Jemaa,Abdelhamid %A Ben Salem,Amal %A Rekik,Bassem %A Ben Doudou,Maroua %A Boujnah,Mohamed Rachid %A Joulak,Anissa %A Omar,Abid %A Razgallah,Rabie %A Sami,Milouchi %A Neffati,Elyes %A Gamra,Habib %A Ben Youssef,Soraya %A Sdiri,Wissem %A Ben Halima,Nejeh %A Ben Ameur,Youssef %A Kachboura,Salem %A Kraiem,Sondes %A Fehri,Wafa %A Zakhama,Lilia %A Bezdah,leila %A Mohamed Sami,Mourali %A Drissa,Habiba %A Maatouk,Mohamed Faouzi %A Kammoun,Samir %A Addad,Faouzi %+ Tunisian Society of Cardiology and Cardiovascular Surgery, Rue du Lac Huron, Résidence Les Pergolas, Apt. 201 Les Berges du Lac, Tunis, 1053, Tunisia, 216 71965432, leilaabidt@yahoo.fr %K National Tunisian Registry %K hypertension %D 2022 %7 2.9.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: This study was designed to evaluate the care of hypertensive patients in daily clinical practice in public and private centers in all Tunisian regions. Objective: This study will provide us an overview of hypertension (HTN) management in Tunisia and the degree of adherence of practitioners to international recommendations. Methods: This is a national observational cross-sectional multicenter study that will include patients older than 18 years with HTN for a duration of 4 weeks, managed in the public sector from primary and secondary care centers as well as patients managed in the private sector. Every participating patient signed a consent form. The study will exclude patients undergoing dialysis. The parameters that will be evaluated are demographic and anthropometric data, lifestyle habits, blood pressure levels, lipid profiles, treatment, and adherence to treatment. The data are collected via the web interface in the Dacima Clinical Suite. Results: The study began on April 15, 2019 and ended on May 15, 2019. During this period, we included 25,890 patients with HTN. Data collection involved 321 investigators from 24 Tunisian districts. The investigators were doctors working in the private and public sectors. Conclusions: Observational studies are extremely useful in improving the management of HTN in developing countries. Trial Registration: ClinicalTrials.gov NCT04013503; https://clinicaltrials.gov/ct2/show/NCT04013503 International Registered Report Identifier (IRRID): DERR1-10.2196/21878 %M 36053572 %R 10.2196/21878 %U https://www.researchprotocols.org/2022/9/e21878 %U https://doi.org/10.2196/21878 %U http://www.ncbi.nlm.nih.gov/pubmed/36053572 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 8 %P e38874 %T The Variations in Care and Real-world Outcomes in Individuals With Rectal Cancer: Protocol for the Ontario Rectal Cancer Cohort %A Patel,Sunil %A McClintock,Chad %A Booth,Christopher %A Merchant,Shaila %A Heneghan,Carl %A Bankhead,Clare %+ Department of Surgery, Queen's University, 76 Stuart Street, Kingston, ON, K7L 2V7, Canada, 1 613 549 6666 ext 7995, sunil.patel@kingstonhsc.ca %K rectal cancer %K survival %K adherence to care %K regional variability %D 2022 %7 5.8.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Individuals with rectal cancer require a number of pretreatment investigations, often require multidisciplinary treatment, and require ongoing follow-ups after treatment is completed. Due to the complexity of treatments, large variations in practice patterns and outcomes have been identified. At present, few comprehensive, population-level data sets are available for assessing interventions and outcomes in this group. Objective: Our study aims to create a comprehensive database of individuals with rectal cancer who have been treated in a single-payer, universal health care system. This database will provide an excellent resource that investigators can use to study variations in the delivery of care to and real-world outcomes of this population. Methods: The Ontario Rectal Cancer Cohort database will include comprehensive details about the management and outcomes of individuals with rectal cancer who have been diagnosed in Ontario, Canada (population: 14.6 million), between 2010 and 2019. Linked administrative data sets will be used to construct this comprehensive database. Individual and care provider characteristics, investigations, treatments, follow-ups, and outcomes will be derived and linked. Surgical pathology details, including the stage of disease, histopathology characteristics, and the quality of surgical excision, will be included. Ethics approval for this study was obtained through the Queen’s University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board. Results: Approximately 20,000 individuals who meet the inclusion criteria for this study have been identified. Data analysis is ongoing, with an expected completion date of March 2023. This study was funded through the Canadian Institute of Health Research Operating Grant. Conclusions: The Ontario Rectal Cancer Cohort will include a comprehensive data set of individuals with rectal cancer who received care within a single-payer, universal health care system. This cohort will be used to determine factors associated with regional variability and adherence to recommended care, and it will allow for an assessment of a number of understudied areas within the delivery of rectal cancer treatment. International Registered Report Identifier (IRRID): RR1-10.2196/38874 %M 35930352 %R 10.2196/38874 %U https://www.researchprotocols.org/2022/8/e38874 %U https://doi.org/10.2196/38874 %U http://www.ncbi.nlm.nih.gov/pubmed/35930352 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 8 %P e24595 %T Design and Rationale of the National Tunisian Registry of Percutaneous Coronary Intervention: Protocol for a Prospective Multicenter Observational Study %A Hammami,Rania %A Boudiche,Selim %A Rami,Tlili %A Ben Halima,Nejeh %A Jamel,Ahmed %A Rekik,Bassem %A Gribaa,Rym %A Imtinene,Ben Mrad %A Charfeddine,Salma %A Ellouze,Tarek %A Bahloul,Amine %A Hédi,Ben Slima %A Langar,Jamel %A Ben Ahmed,Habib %A Ibn Elhadj,Zied %A Hmam,Mohamed %A Ben Abdessalem,Mohamed Aymen %A Maaoui,Sabri %A Fennira,Sana %A Lobna,Laroussi %A Hassine,Majed %A Ouanes,Sami %A Mohamed Faouzi,Drissi %A Mallek,Souad %A Mahdhaoui,Abdallah %A Meriem,Dghim %A Jomaa,Walid %A Zayed,Sofien %A Kateb,Tawfik %A Bouchahda,Nidhal %A Azaiez,Fares %A Ben Salem,Helmi %A Marouen,Morched %A Noamen,Aymen %A Abdesselem,Salem %A Hichem,Denguir %A Ibn Hadj Amor,Hassen %A Abdeljelil,Farhati %A Amara,Amine %A Bejar,Karim %A Khaldoun,Ben Hamda %A Hamza,Chiheb %A Ben Jamaa,Mohsen %A Fourati,Sami %A Elleuch,Faycal %A Grati,Zeineb %A Chtourou,Slim %A Marouene,Sami %A Sahnoun,Mohamed %A Hadrich,Morched %A Mohamed Abdelkader,Maalej %A Bouraoui,Hatem %A Kamoun,Kamel %A Hadrich,Moufid %A Ben Chedli,Tarek %A Drissa,Mohamed Akrem %A Charfeddine,Hanene %A Saadaoui,Nizar %A Achraf,Gargouri %A Ahmed,Siala %A Ayari,Mokdad %A Nabil,Marsit %A Mnif,Sabeur %A Sahnoun,Maher %A Kammoun,Helmi %A Ben Jemaa,Khaled %A Mostari,Gharbi %A Hamrouni,Nebil %A Yamen,Maazoun %A Ellouz,Yassine %A Smiri,Zahreddine %A Hdiji,Amine %A Bassem,Jerbi %A Ayadi,Wacef %A Zouari,Amir %A Abbassi,Chedly %A Fatma,Boujelben Masmoudi %A Battikh,Kais %A Kharrat,Elyes %A Gtif,Imen %A Sami,Milouchi %A Bezdah,Leila %A Kachboura,Salem %A Maatouk,Mohamed Faouzi %A Kraiem,Sondes %A Jeridi,Gouider %A Neffati,Elyes %A Kammoun,Samir %A Ben Ameur,Youssef %A Fehri,Wafa %A Gamra,Habib %A Zakhama,Lilia %A Addad,Faouzi %A Mohamed Sami,Mourali %A Abid,Leila %+ Department of Cardiology, Hédi Chaker Hospital, Faculty of Medicine of Sfax, University of Sfax, 3029 Al Ain Road, Sfax, 3029, Tunisia, 216 24056985, raniahammami@yahoo.fr %K percutaneous coronary intervention %K 1-year outcome %K Tunisia %K national %K multicentric %K registry %K percutaneous %K coronary %K artery disease %D 2022 %7 5.8.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Coronary artery diseases remain the leading cause of death in the world. The management of this condition has improved remarkably in the recent years owing to the development of new technical tools and multicentric registries. Objective: The aim of this study is to investigate the in-hospital and 1-year clinical outcomes of patients treated with percutaneous coronary intervention (PCI) in Tunisia. Methods: We will conduct a prospective multicentric observational study with patients older than 18 years who underwent PCI between January 31, 2020 and June 30, 2020. The primary end point is the occurrence of a major adverse cardiovascular event, defined as cardiovascular death, myocardial infarction, cerebrovascular accident, or target vessel revascularization with either repeat PCI or coronary artery bypass grafting (CABG). The secondary end points are procedural success rate, stent thrombosis, and the rate of redo PCI/CABG for in-stent restenosis. Results: In this study, the demographic profile and the general risk profile of Tunisian patients who underwent PCI and their end points will be analyzed. The complexity level of the procedures and the left main occlusion, bifurcation occlusion, and chronic total occlusion PCI will be analyzed, and immediate as well as long-term results will be determined. The National Tunisian Registry of PCI (NATURE-PCI) will be the first national multicentric registry of angioplasty in Africa. For this study, the institutional ethical committee approval was obtained (0223/2020). This trial consists of 97 cardiologists and 2498 patients who have undergone PCI with a 1-year follow-up period. Twenty-eight catheterization laboratories from both public (15 laboratories) and private (13 laboratories) sectors will enroll patients after receiving informed consent. Of the 2498 patients, 1897 (75.9%) are managed in the public sector and 601 (24.1%) are managed in the private sector. The COVID-19 pandemic started in Tunisia in March 2020; 719 patients (31.9%) were included before the COVID-19 pandemic and 1779 (60.1%) during the pandemic. The inclusion of patients has been finished, and we expect to publish the results by the end of 2022. Conclusions: This study would add data and provide a valuable opportunity for real-world clinical epidemiology and practice in the field of interventional cardiology in Tunisia with insights into the uptake of PCI in this limited-income region. Trial Registration: Clinicaltrials.gov NCT04219761; https://clinicaltrials.gov/ct2/show/NCT04219761 International Registered Report Identifier (IRRID): RR1-10.2196/24595 %M 35930353 %R 10.2196/24595 %U https://www.researchprotocols.org/2022/8/e24595 %U https://doi.org/10.2196/24595 %U http://www.ncbi.nlm.nih.gov/pubmed/35930353 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 5 %P e32158 %T Domain-Specific Common Data Elements for Rare Disease Registration: Conceptual Approach of a European Joint Initiative Toward Semantic Interoperability in Rare Disease Research %A Abaza,Haitham %A Kadioglu,Dennis %A Martin,Simona %A Papadopoulou,Andri %A dos Santos Vieira,Bruna %A Schaefer,Franz %A Storf,Holger %+ Institute of Medical Informatics, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern-Kai 7, Frankfurt am Main, 60590, Germany, 49 696301 ext 80692, dennis.kadioglu@kgu.de %K semantic interoperability %K common data elements %K standardization %K data collection %K data discoverability %K rare diseases %K EJP RD %K EU RD Platform %K ERNs %K FAIRification %K health infrastructure %K industry %K medical informatics %K health platforms %K health registries %K health and research platforms %K health domains %D 2022 %7 20.5.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: With hundreds of registries across Europe, rare diseases (RDs) suffer from fragmented knowledge, expertise, and research. A joint initiative of the European Commission Joint Research Center and its European Platform on Rare Disease Registration (EU RD Platform), the European Reference Networks (ERNs), and the European Joint Programme on Rare Diseases (EJP RD) was launched in 2020. The purpose was to extend the set of common data elements (CDEs) for RD registration by defining domain-specific CDEs (DCDEs). Objective: This study aims to introduce and assess the feasibility of the concept of a joint initiative that unites the efforts of the European Platform on Rare Disease Registration Platform, ERNs, and European Joint Programme on Rare Diseases toward extending RD CDEs, aiming to improve the semantic interoperability of RD registries and enhance the quality of RD research. Methods: A joint conference was conducted in December 2020. All 24 ERNs were invited. Before the conference, a survey was communicated to all ERNs, proposing 18 medical domains and requesting them to identify highly relevant choices. After the conference, a 3-phase plan for defining and modeling DCDEs was drafted. Expected outcomes included harmonized lists of DCDEs. Results: All ERNs attended the conference. The survey results indicated that genetic, congenital, pediatric, and cancer were the most overlapping domains. Accordingly, the proposed list was reorganized into 10 domain groups and recommunicated to all ERNs, aiming at a smaller number of domains. Conclusions: The approach described for defining DCDEs appears to be feasible. However, it remains dynamic and should be repeated regularly based on arising research needs. %M 35594066 %R 10.2196/32158 %U https://medinform.jmir.org/2022/5/e32158 %U https://doi.org/10.2196/32158 %U http://www.ncbi.nlm.nih.gov/pubmed/35594066 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 4 %P e32776 %T Mechanism of Impact of Big Data Resources on Medical Collaborative Networks From the Perspective of Transaction Efficiency of Medical Services: Survey Study %A Yuan,Junyi %A Wang,Sufen %A Pan,Changqing %+ Hospital’s Office, Shanghai Chest Hospital, Shanghai Jiao Tong University, No 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China, 86 21 62805080, panchangqing@shchest.org %K medical collaborative networks %K big data resources %K transaction efficiency %D 2022 %7 21.4.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: The application of big data resources and the development of medical collaborative networks (MCNs) boost each other. However, MCNs are often assumed to be exogenous. How big data resources affect the emergence, development, and evolution of endogenous MCNs has not been well explained. Objective: This study aimed to explore and understand the influence of the mechanism of a wide range of shared and private big data resources on the transaction efficiency of medical services to reveal the impact of big data resources on the emergence and development of endogenous MCNs. Methods: This study was conducted by administering a survey questionnaire to information technology staff and medical staff from 132 medical institutions in China. Data from information technology staff and medical staff were integrated. Structural equation modeling was used to test the direct impact of big data resources on transaction efficiency of medical services. For those big data resources that had no direct impact, we analyzed their indirect impact. Results: Sharing of diagnosis and treatment data (β=.222; P=.03) and sharing of medical research data (β=.289; P=.04) at the network level (as big data itself) positively directly affected the transaction efficiency of medical services. Network protection of the external link systems (β=.271; P=.008) at the level of medical institutions (as big data technology) positively directly affected the transaction efficiency of medical services. Encryption security of web-based data (as big data technology) at the level of medical institutions, medical service capacity available for external use, real-time data of diagnosis and treatment services (as big data itself) at the level of medical institutions, and policies and regulations at the network level indirectly affected the transaction efficiency through network protection of the external link systems at the level of medical institutions. Conclusions: This study found that big data technology, big data itself, and policy at the network and organizational levels interact with, and influence, each other to form the transaction efficiency of medical services. On the basis of the theory of neoclassical economics, the study highlighted the implications of big data resources for the emergence and development of endogenous MCNs. %M 35318187 %R 10.2196/32776 %U https://www.jmir.org/2022/4/e32776 %U https://doi.org/10.2196/32776 %U http://www.ncbi.nlm.nih.gov/pubmed/35318187 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 8 %N 2 %P e33240 %T Barriers to Clinical Trial Participation: Comparative Study Between Rural and Urban Participants %A Mudaranthakam,Dinesh Pal %A Gajewski,Byron %A Krebill,Hope %A Coulter,James %A Springer,Michelle %A Calhoun,Elizabeth %A Hughes,Dorothy %A Mayo,Matthew %A Doolittle,Gary %+ University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66085, United States, 1 9139456922, dmudaranthakam@kumc.edu %K rural residents %K clinical trials %K screening %K cancer %K patients %K lung cancer %K health policy epidemiology %K cancer patients %K electronic screening logs %K electronic screening %D 2022 %7 21.4.2022 %9 Original Paper %J JMIR Cancer %G English %X Background: The National Clinical Trials Network program conducts phase 2 or phase 3 treatment trials across all National Cancer Institute’s designated cancer centers. Participant accrual across these clinical trials is a critical factor in deciding their success. Cancer centers that cater to rural populations, such as The University of Kansas Cancer Center, have an additional responsibility to ensure rural residents have access and are well represented across these studies. Objective: There are scant data available regarding the factors that act as barriers to the accrual of rural residents in these clinical trials. This study aims to use electronic screening logs that were used to gather patient data at several participating sites in The Kansas University of Cancer Center’s Catchment area. Methods: Screening log data were used to assess what clinical trial participation barriers are faced by these patients. Additionally, the differences in clinical trial participation barriers were compared between rural and urban participating sites. Results: Analysis revealed that the hospital location rural urban category, defined as whether the hospital was in an urban or rural setting, had a medium effect on enrolment of patients in breast cancer and lung cancer trials (Cohen d=0.7). Additionally, the hospital location category had a medium effect on the proportion of recurrent lung cancer cases at the time of screening (d=0.6). Conclusions: In consideration of the financially hostile nature of cancer treatment as well as geographical and transportation barriers, clinical trials extended to rural communities are uniquely positioned to alleviate the burden of nonmedical costs in trial participation. However, these options can be far less feasible for patients in rural settings. Since the number of patients with cancer who are eligible for a clinical trial is already limited by the stringent eligibility criteria required of such a complex disease, improving accessibility for rural patients should be a greater focus in health policy. %M 35451964 %R 10.2196/33240 %U https://cancer.jmir.org/2022/2/e33240 %U https://doi.org/10.2196/33240 %U http://www.ncbi.nlm.nih.gov/pubmed/35451964 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 4 %P e28696 %T Patient Recruitment System for Clinical Trials: Mixed Methods Study About Requirements at Ten University Hospitals %A Fitzer,Kai %A Haeuslschmid,Renate %A Blasini,Romina %A Altun,Fatma Betül %A Hampf,Christopher %A Freiesleben,Sherry %A Macho,Philipp %A Prokosch,Hans-Ulrich %A Gulden,Christian %+ Core Unit Data Integration Center, University Medicine Greifswald, Walter-Rathenau-Str 48, Greifswald, 17487, Germany, 49 383486 ext 7555, kai.fitzer@uni-greifswald.de %K patient recruitment system %K clinical trial recruitment support system %K recruitment %K patient screening %K requirements %K user needs %K clinical trial %K interview %K survey %K electronic support %K clinical information systems %K eHealth %D 2022 %7 20.4.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Clinical trials are the gold standard for advancing medical knowledge and improving patient outcomes. For their success, an appropriately sized cohort is required. However, patient recruitment remains one of the most challenging aspects of clinical trials. Information technology (IT) support systems—for instance, patient recruitment systems—may help overcome existing challenges and improve recruitment rates, when customized to the user needs and environment. Objective: The goal of our study is to describe the status quo of patient recruitment processes and to identify user requirements for the development of a patient recruitment system. Methods: We conducted a web-based survey with 56 participants as well as semistructured interviews with 33 participants from 10 German university hospitals. Results: We here report the recruitment procedures and challenges of 10 university hospitals. The recruitment process was influenced by diverse factors such as the ward, use of software, and the study inclusion criteria. Overall, clinical staff seemed more involved in patient identification, while the research staff focused on screening tasks. Ad hoc and planned screenings were common. Identifying eligible patients was still associated with significant manual efforts. The recruitment staff used Microsoft Office suite because tailored software were not available. To implement such software, data from disparate sources will need to be made available. We discussed concrete technical challenges concerning patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration, and we contributed to the support of developing a successful system. Conclusions: Identifying eligible patients is still associated with significant manual efforts. To fully make use of the high potential of IT in patient recruitment, many technical and process challenges have to be solved first. We contribute and discuss concrete technical challenges for patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration. %M 35442203 %R 10.2196/28696 %U https://medinform.jmir.org/2022/4/e28696 %U https://doi.org/10.2196/28696 %U http://www.ncbi.nlm.nih.gov/pubmed/35442203 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 3 %P e35190 %T Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS) %A Lerner,Ivan %A Serret-Larmande,Arnaud %A Rance,Bastien %A Garcelon,Nicolas %A Burgun,Anita %A Chouchana,Laurent %A Neuraz,Antoine %+ Inserm, Centre de Recherche des Cordeliers, Sorbonne Université, Université de Paris, 15 Rue de l'École de Médecine, Paris, 75006, France, 33 01 44 27 64 82, antoine.neuraz@aphp.fr %K COVID-19 %K drug repurposing %K wide association studies %K clinical data %K pharmacopeia %K electronic medical records %K health data %K mortality rate %K hospitalization %K patient data %D 2022 %7 30.3.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Patients hospitalized for a given condition may be receiving other treatments for other contemporary conditions or comorbidities. The use of such observational clinical data for pharmacological hypothesis generation is appealing in the context of an emerging disease but particularly challenging due to the presence of drug indication bias. Objective: With this study, our main objective was the development and validation of a fully data-driven pipeline that would address this challenge. Our secondary objective was to generate pharmacological hypotheses in patients with COVID-19 and demonstrate the clinical relevance of the pipeline. Methods: We developed a pharmacopeia-wide association study (PharmWAS) pipeline inspired from the PheWAS methodology, which systematically screens for associations between the whole pharmacopeia and a clinical phenotype. First, a fully data-driven procedure based on adaptive least absolute shrinkage and selection operator (LASSO) determined drug-specific adjustment sets. Second, we computed several measures of association, including robust methods based on propensity scores (PSs) to control indication bias. Finally, we applied the Benjamini and Hochberg procedure of the false discovery rate (FDR). We applied this method in a multicenter retrospective cohort study using electronic medical records from 16 university hospitals of the Greater Paris area. We included all adult patients between 18 and 95 years old hospitalized in conventional wards for COVID-19 between February 1, 2020, and June 15, 2021. We investigated the association between drug prescription within 48 hours from admission and 28-day mortality. We validated our data-driven pipeline against a knowledge-based pipeline on 3 treatments of reference, for which experts agreed on the expected association with mortality. We then demonstrated its clinical relevance by screening all drugs prescribed in more than 100 patients to generate pharmacological hypotheses. Results: A total of 5783 patients were included in the analysis. The median age at admission was 69.2 (IQR 56.7-81.1) years, and 3390 (58.62%) of the patients were male. The performance of our automated pipeline was comparable or better for controlling bias than the knowledge-based adjustment set for 3 reference drugs: dexamethasone, phloroglucinol, and paracetamol. After correction for multiple testing, 4 drugs were associated with increased in-hospital mortality. Among these, diazepam and tramadol were the only ones not discarded by automated diagnostics, with adjusted odds ratios of 2.51 (95% CI 1.52-4.16, Q=.01) and 1.94 (95% CI 1.32-2.85, Q=.02), respectively. Conclusions: Our innovative approach proved useful in generating pharmacological hypotheses in an outbreak setting, without requiring a priori knowledge of the disease. Our systematic analysis of early prescribed treatments from patients hospitalized for COVID-19 showed that diazepam and tramadol are associated with increased 28-day mortality. Whether these drugs could worsen COVID-19 needs to be further assessed. %M 35275837 %R 10.2196/35190 %U https://medinform.jmir.org/2022/3/e35190 %U https://doi.org/10.2196/35190 %U http://www.ncbi.nlm.nih.gov/pubmed/35275837 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 3 %P e27921 %T Lessons From a Rapid Project Management Exercise in the Time of Pandemic: Methodology for a Global COVID-19 VIRUS Registry Database %A Turek,Janice R %A Bansal,Vikas %A Tekin,Aysun %A Singh,Shuchita %A Deo,Neha %A Sharma,Mayank %A Bogojevic,Marija %A Qamar,Shahraz %A Singh,Romil %A Kumar,Vishakha %A Kashyap,Rahul %+ Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 1216 2nd St SW, Rochester, MN, 55902, United States, 1 507 255 7196, kashyap.rahul@mayo.edu %K COVID-19 %K critical care %K global %K program management %K registry %D 2022 %7 15.3.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: The rapid emergence of the COVID-19 pandemic globally collapsed health care organizations worldwide. Incomplete knowledge of best practices, progression of disease, and its impact could result in fallible care. Data on symptoms and advancement of the SARS-CoV-2 virus leading to critical care admission have not been captured or communicated well between international organizations experiencing the same impact from the virus. This led to the expedited need for establishing international communication and data collection on the critical care patients admitted with COVID-19. Objective: Developing a global registry to collect patient data in the critical care setting was imperative with the goal of analyzing and ameliorating outcomes. Methods: A prospective, observational global registry database was put together to record extensive deidentified clinical information for patients hospitalized with COVID-19. Results: Project management was crucial for prompt implementation of the registry for synchronization, improving efficiency, increasing innovation, and fostering global collaboration for valuable data collection. The Society of Critical Care Medicine Discovery VIRUS (Viral Infection and Respiratory Illness Universal Study): COVID-19 Registry would compile data for crucial longitudinal outcomes for disease, treatment, and research. The agile project management approach expedited establishing the registry in 15 days and submission of institutional review board agreement for 250 participating sites. There has been enrollment of sites every month with a total of 306 sites from 28 countries and 64,114 patients enrolled (as of June 7, 2021). Conclusions: This protocol addresses project management lessons in a time of crises which can be a precept for rapid project management for a large-scale health care data registry. We aim to discuss the approach and methodology for establishing the registry, the challenges faced, and the factors contributing to successful outcomes. Trial Registration: ClinicalTrials.gov NCT04323787; https://clinicaltrials.gov/ct2/show/NCT04323787 %M 34762062 %R 10.2196/27921 %U https://www.researchprotocols.org/2022/3/e27921 %U https://doi.org/10.2196/27921 %U http://www.ncbi.nlm.nih.gov/pubmed/34762062 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e31684 %T A National Network of Safe Havens: Scottish Perspective %A Gao,Chuang %A McGilchrist,Mark %A Mumtaz,Shahzad %A Hall,Christopher %A Anderson,Lesley Ann %A Zurowski,John %A Gordon,Sharon %A Lumsden,Joanne %A Munro,Vicky %A Wozniak,Artur %A Sibley,Michael %A Banks,Christopher %A Duncan,Chris %A Linksted,Pamela %A Hume,Alastair %A Stables,Catherine L %A Mayor,Charlie %A Caldwell,Jacqueline %A Wilde,Katie %A Cole,Christian %A Jefferson,Emily %+ Health Informatics Centre, Ninewells Hospital & Medical School, University of Dundee, Mail Box 15, , Dundee, DD1 9SY, United Kingdom, 44 (0)1382 383943, e.r.jefferson@dundee.ac.uk %K electronic health records %K Safe Haven %K data governance %D 2022 %7 9.3.2022 %9 Viewpoint %J J Med Internet Res %G English %X For over a decade, Scotland has implemented and operationalized a system of Safe Havens, which provides secure analytics platforms for researchers to access linked, deidentified electronic health records (EHRs) while managing the risk of unauthorized reidentification. In this paper, a perspective is provided on the state-of-the-art Scottish Safe Haven network, including its evolution, to define the key activities required to scale the Scottish Safe Haven network’s capability to facilitate research and health care improvement initiatives. A set of processes related to EHR data and their delivery in Scotland have been discussed. An interview with each Safe Haven was conducted to understand their services in detail, as well as their commonalities. The results show how Safe Havens in Scotland have protected privacy while facilitating the reuse of the EHR data. This study provides a common definition of a Safe Haven and promotes a consistent understanding among the Scottish Safe Haven network and the clinical and academic research community. We conclude by identifying areas where efficiencies across the network can be made to meet the needs of population-level studies at scale. %M 35262495 %R 10.2196/31684 %U https://www.jmir.org/2022/3/e31684 %U https://doi.org/10.2196/31684 %U http://www.ncbi.nlm.nih.gov/pubmed/35262495 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 1 %P e34567 %T Cocreating a Harmonized Living Lab for Big Data–Driven Hybrid Persona Development: Protocol for Cocreating, Testing, and Seeking Consensus %A Santonen,Teemu %A Petsani,Despoina %A Julin,Mikko %A Garschall,Markus %A Kropf,Johannes %A Van der Auwera,Vicky %A Bernaerts,Sylvie %A Losada,Raquel %A Almeida,Rosa %A Garatea,Jokin %A Muñoz,Idoia %A Nagy,Eniko %A Kehayia,Eva %A de Guise,Elaine %A Nadeau,Sylvie %A Azevedo,Nancy %A Segkouli,Sofia %A Lazarou,Ioulietta %A Petronikolou,Vasileia %A Bamidis,Panagiotis %A Konstantinidis,Evdokimos %+ Department of Research, Development, Innovation and Business Development, Laurea University of Applied Sciences, Vanha maantie 9, Espoo, 02650, Finland, 358 503658353, teemu.santonen@laurea.fi %K Living Lab %K everyday living %K technology %K big data %K harmonization %K personas %K small-scale real-life testing %K mobile phone %D 2022 %7 6.1.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Living Labs are user-centered, open innovation ecosystems based on a systematic user cocreation approach, which integrates research and innovation processes in real-life communities and settings. The Horizon 2020 Project VITALISE (Virtual Health and Wellbeing Living Lab Infrastructure) unites 19 partners across 11 countries. The project aims to harmonize Living Lab procedures and enable effective and convenient transnational and virtual access to key European health and well-being research infrastructures, which are governed by Living Labs. The VITALISE consortium will conduct joint research activities in the fields included in the care pathway of patients: rehabilitation, transitional care, and everyday living environments for older adults. This protocol focuses on health and well-being research in everyday living environments. Objective: The main aim of this study is to cocreate and test a harmonized research protocol for developing big data–driven hybrid persona, which are hypothetical user archetypes created to represent a user community. In addition, the use and applicability of innovative technologies will be investigated in the context of various everyday living and Living Lab environments. Methods: In phase 1, surveys and structured interviews will be used to identify the most suitable Living Lab methods, tools, and instruments for health-related research among VITALISE project Living Labs (N=10). A series of web-based cocreation workshops and iterative cowriting processes will be applied to define the initial protocols. In phase 2, five small-scale case studies will be conducted to test the cocreated research protocols in various real-life everyday living settings and Living Lab infrastructures. In phase 3, a cross-case analysis grounded on semistructured interviews will be conducted to identify the challenges and benefits of using the proposed research protocols. Furthermore, a series of cocreation workshops and the consensus seeking Delphi study process will be conducted in parallel to cocreate and validate the acceptance of the defined harmonized research protocols among wider Living Lab communities. Results: As of September 30, 2021, project deliverables Ethics and safety manual and Living lab standard version 1 have been submitted to the European Commission review process. The study will be finished by March 2024. Conclusions: The outcome of this research will lead to harmonized procedures and protocols in the context of big data–driven hybrid persona development among health and well-being Living Labs in Europe and beyond. Harmonized protocols enable Living Labs to exploit similar research protocols, devices, hardware, and software for interventions and complex data collection purposes. Economies of scale and improved use of resources will speed up and improve research quality and offer novel possibilities for open data sharing, multidisciplinary research, and comparative studies beyond current practices. Case studies will also provide novel insights for implementing innovative technologies in the context of everyday Living Lab research. International Registered Report Identifier (IRRID): DERR1-10.2196/34567 %M 34989697 %R 10.2196/34567 %U https://www.researchprotocols.org/2022/1/e34567 %U https://doi.org/10.2196/34567 %U http://www.ncbi.nlm.nih.gov/pubmed/34989697 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e31121 %T An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study %A Lajonchere,Clara %A Naeim,Arash %A Dry,Sarah %A Wenger,Neil %A Elashoff,David %A Vangala,Sitaram %A Petruse,Antonia %A Ariannejad,Maryam %A Magyar,Clara %A Johansen,Liliana %A Werre,Gabriela %A Kroloff,Maxwell %A Geschwind,Daniel %+ Center for SMART Health, Institute for Precision Health, David Geffen School of Medicine at UCLA, 10911 Weyburn Ave, Suite 300e, Los Angeles, CA, 90095, United States, 1 3103670148, anaeim@mednet.ucla.edu %K biobanking %K precision medicine %K electronic consent %K privacy %K consent %K patient privacy %K clinical data %K eHealth %K recruitment %K population health %K data collection %K research methods %K video %K research %K validation %K scalability %D 2021 %7 8.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. Objective: We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. Methods: The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. Results: The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P<.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; P<.001), Asian (OR 0.72, 95% CI 0.68-0.77; P<.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; P<.001) were less likely to participate than White individuals. Conclusions: This is one of the few large-scale, electronic video–based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research. %M 34889741 %R 10.2196/31121 %U https://www.jmir.org/2021/12/e31121 %U https://doi.org/10.2196/31121 %U http://www.ncbi.nlm.nih.gov/pubmed/34889741 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e28021 %T Recruitment of Patients With Amyotrophic Lateral Sclerosis for Clinical Trials and Epidemiological Studies: Descriptive Study of the National ALS Registry’s Research Notification Mechanism %A Mehta,Paul %A Raymond,Jaime %A Han,Moon Kwon %A Larson,Theodore %A Berry,James D %A Paganoni,Sabrina %A Mitsumoto,Hiroshi %A Bedlack,Richard Stanley %A Horton,D Kevin %+ Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Atlanta, GA, 30341, United States, 1 770 488 0556, pum4@cdc.gov %K amyotrophic lateral sclerosis %K Lou Gehrig disease %K motor neuron disease %K clinical trials %K patient recruitment %K National ALS Registry %K research notification mechanism %D 2021 %7 7.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Researchers face challenges in patient recruitment, especially for rare, fatal diseases such as amyotrophic lateral sclerosis (ALS). These challenges include obtaining sufficient statistical power as well as meeting eligibility requirements such as age, sex, and study proximity. Similarly, persons with ALS (PALS) face difficulty finding and enrolling in research studies for which they are eligible. Objective: The aim of this study was to describe how the federal Agency for Toxic Substances and Disease Registry’s (ATSDR) National ALS Registry is linking PALS to scientists who are conducting research, clinical trials, and epidemiological studies. Methods: Through the Registry’s online research notification mechanism (RNM), PALS can elect to be notified about new research opportunities. This mechanism allows researchers to upload a standardized application outlining their study design and objectives, and proof of Institutional Review Board approval. If the application is approved, ATSDR queries the Registry for PALS meeting the study’s specific eligibility criteria, and then distributes the researcher’s study material and contact information to PALS via email. PALS then need to contact the researcher directly to take part in any research. Such an approach allows ATSDR to protect the confidentiality of Registry enrollees. Results: From 2013 to 2019, a total of 46 institutions around the United States and abroad have leveraged this tool and over 600,000 emails have been sent, resulting in over 2000 patients conservatively recruited for clinical trials and epidemiological studies. Patients between the ages of 60 and 69 had the highest level of participation, whereas those between the ages of 18 and 39 and aged over 80 had the lowest. More males participated (4170/7030, 59.32%) than females (2860/7030, 40.68%). Conclusions: The National ALS Registry’s RNM benefits PALS by connecting them to appropriate ALS research. Simultaneously, the system benefits researchers by expediting recruitment, increasing sample size, and efficiently identifying PALS meeting specific eligibility requirements. As more researchers learn about and use this mechanism, both PALS and researchers can hasten research and expand trial options for PALS. %M 34878988 %R 10.2196/28021 %U https://www.jmir.org/2021/12/e28021 %U https://doi.org/10.2196/28021 %U http://www.ncbi.nlm.nih.gov/pubmed/34878988 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e20028 %T Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group %A Ye,Ye %A Barapatre,Seemran %A Davis,Michael K %A Elliston,Keith O %A Davatzikos,Christos %A Fedorov,Andrey %A Fillion-Robin,Jean-Christophe %A Foster,Ian %A Gilbertson,John R %A Lasso,Andras %A Miller,James V %A Morgan,Martin %A Pieper,Steve %A Raumann,Brigitte E %A Sarachan,Brion D %A Savova,Guergana %A Silverstein,Jonathan C %A Taylor,Donald P %A Zelnis,Joyce B %A Zhang,Guo-Qiang %A Cuticchia,Jamie %A Becich,Michael J %+ Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, 5607 Baum Blvd Office 502, 15206, Pittsburgh, PA, United States, 1 412 648 9244, becich@pitt.edu %K open-source software %K sustainability %K licensing model %K financial model %K product management %K cancer informatics %D 2021 %7 2.12.2021 %9 Viewpoint %J J Med Internet Res %G English %X Background: The National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019. Objective: The charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective. Methods: This paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene. Results: Information available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS. Conclusions: We recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene. %M 34860667 %R 10.2196/20028 %U https://www.jmir.org/2021/12/e20028 %U https://doi.org/10.2196/20028 %U http://www.ncbi.nlm.nih.gov/pubmed/34860667 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e26890 %T ClinicalTrials.gov as a Source of Information About Expanded Access Programs: Cohort Study %A Borysowski,Jan %A Górski,Andrzej %+ Department of Clinical Immunology, Medical University of Warsaw, Nowogrodzka Str 59, Warsaw, 02-006, Poland, 48 22 502 10 58, jborysowski@interia.pl %K ClinicalTrials.gov %K expanded access %K expanded access program %K compassionate use %K unapproved drug %K investigational drug %D 2021 %7 28.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: ClinicalTrials.gov (CT.gov) is the most comprehensive internet-based register of different types of clinical studies. Expanded access is the use of unapproved drugs, biologics, or medical devices outside of clinical trials. One of the key problems in expanded access is the availability to both health care providers and patients of information about unapproved treatments. Objective: We aimed to evaluate CT.gov as a potential source of information about expanded access programs. Methods: We assessed the completeness of information in the records of 228 expanded access programs registered with CT.gov from February 2017 through May 2020. Moreover, we examined what percentage of published expanded access studies has been registered with CT.gov. Logistic regression (univariate and multivariate) and mediation analyses were used to identify the predictors of the absence of some information and a study’s nonregistration. Results: We found that some important data were missing from the records of many programs. Information that was missing most often included a detailed study description, facility information, central contact person, and eligibility criteria (55.3%, 54.0%, 41.7%, and 17.5% of the programs, respectively). Multivariate analysis showed that information about central contact person was more likely to be missing from records of studies registered in 2017 (adjusted OR 21.93; 95% CI 4.42-172.29; P<.001). This finding was confirmed by mediation analysis (P=.02). Furthermore, 14% of the programs were registered retrospectively. We also showed that only 33 of 77 (42.9%) expanded access studies performed in the United States and published from 2014 through 2019 were registered with CT.gov. However, multivariate logistic regression analysis showed no significant association between any of the variables related to the studies and the odds of study nonregistration (P>.01). Conclusions: Currently, CT.gov is a quite fragmentary source of data on expanded access programs. This problem is important because CT.gov is the only publicly available primary source of information about specific programs. We suggest the actions that should be taken by different stakeholders to fully exploit this register as a source of information about expanded access. %M 34709189 %R 10.2196/26890 %U https://www.jmir.org/2021/10/e26890 %U https://doi.org/10.2196/26890 %U http://www.ncbi.nlm.nih.gov/pubmed/34709189 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 10 %P e12262 %T Design and Rationale of the National Tunisian Registry of Heart Failure (NATURE-HF): Protocol for a Multicenter Registry Study %A Abid,Leila %A Kammoun,Ikram %A Ben Halima,Manel %A Charfeddine,Salma %A Ben Slima,Hedi %A Drissa,Meriem %A Mzoughi,Khadija %A Mbarek,Dorra %A Riahi,Leila %A Antit,Saoussen %A Ben Halima,Afef %A Ouechtati,Wejdene %A Allouche,Emna %A Mechri,Mehdi %A Yousfi,Chedi %A Khorchani,Ali %A Abid,Omar %A Sammoud,Kais %A Ezzaouia,Khaled %A Gtif,Imen %A Ouali,Sana %A Triki,Feten %A Hamdi,Sonia %A Boudiche,Selim %A Chebbi,Marwa %A Hentati,Mouna %A Farah,Amani %A Triki,Habib %A Ghardallou,Houda %A Raddaoui,Haythem %A Zayed,Sofien %A Azaiez,Fares %A Omri,Fadwa %A Zouari,Akram %A Ben Ali,Zine %A Najjar,Aymen %A Thabet,Houssem %A Chaker,Mouna %A Mohamed,Samar %A Chouaieb,Marwa %A Ben Jemaa,Abdelhamid %A Tangour,Haythem %A Kammoun,Yassmine %A Bouhlel,Mahmoud %A Azaiez,Seifeddine %A Letaief,Rim %A Maskhi,Salah %A Amri,Aymen %A Naanaa,Hela %A Othmani,Raoudha %A Chahbani,Iheb %A Zargouni,Houcine %A Abid,Syrine %A Ayari,Mokdad %A ben Ameur,Ines %A Gasmi,Ali %A ben Halima,Nejeh %A Haouala,Habib %A Boughzela,Essia %A Zakhama,Lilia %A ben Youssef,Soraya %A Nasraoui,Wided %A Boujnah,Mohamed Rachid %A Barakett,Nadia %A Kraiem,Sondes %A Drissa,Habiba %A Ben Khalfallah,Ali %A Gamra,Habib %A Kachboura,Salem %A Bezdah,Leila %A Baccar,Hedi %A Milouchi,Sami %A Sdiri,Wissem %A Ben Omrane,Skander %A Abdesselem,Salem %A Kanoun,Alifa %A Hezbri,Karima %A Zannad,Faiez %A Mebazaa,Alexandre %A Kammoun,Samir %A Mourali,Mohamed Sami %A Addad,Faouzi %+ Société Tunisienne De Cardiologie Et De Chirurgie Cardiovasculaire, Residence Pergolas, Maison du coeur de la Tunisie Appartement 201, Rue du Lac Huron, Tunis, 1053, Tunisia, 216 22739092, addad.faouzi@planet.tn %K heart failure %K acute heart failure %K chronic heart failure %K diagnosis %K prognosis %K treatment %D 2021 %7 27.10.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The frequency of heart failure (HF) in Tunisia is on the rise and has now become a public health concern. This is mainly due to an aging Tunisian population (Tunisia has one of the oldest populations in Africa as well as the highest life expectancy in the continent) and an increase in coronary artery disease and hypertension. However, no extensive data are available on demographic characteristics, prognosis, and quality of care of patients with HF in Tunisia (nor in North Africa). Objective: The aim of this study was to analyze, follow, and evaluate patients with HF in a large nation-wide multicenter trial. Methods: A total of 1700 patients with HF diagnosed by the investigator will be included in the National Tunisian Registry of Heart Failure study (NATURE-HF). Patients must visit the cardiology clinic 1, 3, and 12 months after study inclusion. This follow-up is provided by the investigator. All data are collected via the DACIMA Clinical Suite web interface. Results: At the end of the study, we will note the occurrence of cardiovascular death (sudden death, coronary artery disease, refractory HF, stroke), death from any cause (cardiovascular and noncardiovascular), and the occurrence of a rehospitalization episode for an HF relapse during the follow-up period. Based on these data, we will evaluate the demographic characteristics of the study patients, the characteristics of pathological antecedents, and symptomatic and clinical features of HF. In addition, we will report the paraclinical examination findings such as the laboratory standard parameters and brain natriuretic peptides, electrocardiogram or 24-hour Holter monitoring, echocardiography, and coronarography. We will also provide a description of the therapeutic environment and therapeutic changes that occur during the 1-year follow-up of patients, adverse events following medical treatment and intervention during the 3- and 12-month follow-up, the evaluation of left ventricular ejection fraction during the 3- and 12-month follow-up, the overall rate of rehospitalization over the 1-year follow-up for an HF relapse, and the rate of rehospitalization during the first 3 months after inclusion into the study. Conclusions: The NATURE-HF study will fill a significant gap in the dynamic landscape of HF care and research. It will provide unique and necessary data on the management and outcomes of patients with HF. This study will yield the largest contemporary longitudinal cohort of patients with HF in Tunisia. Trial Registration: ClinicalTrials.gov NCT03262675; https://clinicaltrials.gov/ct2/show/NCT03262675 International Registered Report Identifier (IRRID): DERR1-10.2196/12262 %M 34704958 %R 10.2196/12262 %U https://www.researchprotocols.org/2021/10/e12262 %U https://doi.org/10.2196/12262 %U http://www.ncbi.nlm.nih.gov/pubmed/34704958 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e28096 %T The Transition to an Entirely Digital Immunization Registry in Ha Noi Province and Son La Province, Vietnam: Readiness Assessment Study %A Duong,Hong %A Dao,Sang %A Dang,Huyen %A Nguyen,Linh %A Ngo,Tuan %A Nguyen,Trung %A Tran,Lan Anh %A Nguyen,Doan %A Rivera,Maya %A Nguyen,Nga %+ PATH Vietnam, #1101, 11th floor, Hanoi Towers, 49 Hai Ba Trung Street, Hoan Kiem District, Hanoi, 100000, Vietnam, 84 024 3936 2215 ext 130, ntnguyen@path.org %K immunizations %K immunization registry %K readiness assessment %K electronic immunization records %K Vietnam %D 2021 %7 25.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Vietnam is one of the first low- to middle-income countries to develop and implement a national-scale electronic immunization registry. This system was finalized into the National Immunization Information System (NIIS) and scaled up to a national-level system in 2017. As a result, immunization coverage and the timeliness of vaccinations have drastically improved. The time spent on planning and reporting vaccinations has drastically reduced; as a result, vaccination planning and reporting has become more accurate and effective. However, to date, end users have been tasked with managing both the NIIS and paper-based systems in parallel until a formal assessment of the readiness to fully transition to the NIIS is conducted. Objective: This study aims to evaluate the readiness to move to an entirely digital NIIS in 2 provinces of Vietnam—Ha Noi and Son La. Methods: All health facilities were surveyed to assess their infrastructure, capacity, and need for human resources. NIIS end users were observed and interviewed to evaluate their NIIS knowledge and skill sets. Data from immunization cards and facility paper-based logbooks were compared with data from the NIIS, and vaccine stocks at selected facilities were tallied and compared with data from the NIIS. Results: Of the 990 health facilities evaluated, most used the NIIS to enter and track immunizations (987/990, 99.7%) and vaccine stocks (889/990, 90.8%). Most had stable electricity (971/990, 98.1%), at least 1 computer (986/990, 99.6%), and ≥2 trained NIIS end users (825/990, 83.3%). End users reported that the NIIS supported them in managing and reporting immunization data and saving them time (725/767, 94.5%). Although many end users were able to perform basic skills, almost half struggled with performing more complex tasks. Immunization data were compiled from the NIIS and immunization cards (338/378, 89.4%) and paper-based logbooks (254/269, 94.4%). However, only 54.5% (206/378) of immunization IDs matched, 57% (13/23) of Bacillus Calmette-Guérin vaccination records were accurate, and 70% (21/30) of the facilities had consistent physical vaccine stock balances. The feedback received from NIIS end users suggests that more supportive supervision, frequent refresher training for strengthening their skill sets, and detailed standardized guides for improving data quality are needed. Conclusions: The readiness to transition to a digital system is promising; however, additional resources are required to address the timeliness, completeness, and accuracy of the data. %M 34694232 %R 10.2196/28096 %U https://formative.jmir.org/2021/10/e28096 %U https://doi.org/10.2196/28096 %U http://www.ncbi.nlm.nih.gov/pubmed/34694232 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 10 %P e31288 %T Verifying the Feasibility of Implementing Semantic Interoperability in Different Countries Based on the OpenEHR Approach: Comparative Study of Acute Coronary Syndrome Registries %A Min,Lingtong %A Atalag,Koray %A Tian,Qi %A Chen,Yani %A Lu,Xudong %+ College of Biomedical Engineering & Instrument Science, Zhejiang University, Room 512, Zhouyiqing Building, 38 Zheda Road, Hangzhou, China, 86 13957118891, lvxd@zju.edu.cn %K semantic interoperability %K openEHR %K archetype %K registry %K acute coronary syndrome %D 2021 %7 19.10.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: The semantic interoperability of health care information has been a critical challenge in medical informatics and has influenced the integration, sharing, analysis, and use of medical big data. International standard organizations have developed standards, approaches, and models to improve and implement semantic interoperability. The openEHR approach—one of the standout semantic interoperability approaches—has been implemented worldwide to improve semantic interoperability based on reused archetypes. Objective: This study aimed to verify the feasibility of implementing semantic interoperability in different countries by comparing the openEHR-based information models of 2 acute coronary syndrome (ACS) registries from China and New Zealand. Methods: A semantic archetype comparison method was proposed to determine the semantics reuse degree of reused archetypes in 2 ACS-related clinical registries from 2 countries. This method involved (1) determining the scope of reused archetypes; (2) identifying corresponding data items within corresponding archetypes; (3) comparing the semantics of corresponding data items; and (4) calculating the number of mappings in corresponding data items and analyzing results. Results: Among the related archetypes in the two ACS-related, openEHR-based clinical registries from China and New Zealand, there were 8 pairs of reusable archetypes, which included 89 pairs of corresponding data items and 120 noncorresponding data items. Of the 89 corresponding data item pairs, 87 pairs (98%) were mappable and therefore supported semantic interoperability, and 71 pairs (80%) were labeled as “direct mapping” data items. Of the 120 noncorresponding data items, 114 (95%) data items were generated via archetype evolution, and 6 (5%) data items were generated via archetype localization. Conclusions: The results of the semantic comparison between the two ACS-related clinical registries prove the feasibility of establishing the semantic interoperability of health care data from different countries based on the openEHR approach. Archetype reuse provides data on the degree to which semantic interoperability exists when using the openEHR approach. Although the openEHR community has effectively promoted archetype reuse and semantic interoperability by providing archetype modeling methods, tools, model repositories, and archetype design patterns, the uncontrolled evolution of archetypes and inconsistent localization have resulted in major challenges for achieving higher levels of semantic interoperability. %M 34665150 %R 10.2196/31288 %U https://medinform.jmir.org/2021/10/e31288 %U https://doi.org/10.2196/31288 %U http://www.ncbi.nlm.nih.gov/pubmed/34665150 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 7 %P e26918 %T An Electronic Registry for Improving the Quality of Antenatal Care in Rural Bangladesh (eRegMat): Protocol for a Cluster Randomized Controlled Trial %A Rahman,Anisur %A Friberg,Ingrid K %A Dolphyne,Akuba %A Fjeldheim,Ingvild %A Khatun,Fatema %A O'Donnell,Brian %A Pervin,Jesmin %A Rahman,Monjur %A Rahman,A M Qaiyum %A Nu,U Tin %A Sarker,Bidhan Krishna %A Venkateswaran,Mahima %A Frøen,J Frederik %+ Global Health Cluster, Division for Health Services, Norwegian Institute of Public Health, Sandakerveien 24 C, entrance D11, 3rd floor, East wing, Oslo, Norway, 47 21 07 70 00, frederik.froen@fhi.no %K quality of care %K antenatal care %K maternal and newborn health %K eHealth %K digital health interventions %K eRegistries %K health information systems %K Bangladesh %D 2021 %7 6.7.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Digital health interventions (DHIs) can alleviate several barriers to achieving better maternal and child health. The World Health Organization’s guideline recommendations for DHIs emphasize the need to integrate multiple DHIs for maximizing impact. The complex health system of Bangladesh provides a unique setting for evaluating and understanding the role of an electronic registry (eRegistry) for antenatal care, with multiple integrated DHIs for strengthening the health system as well as improving the quality and utilization of the public health care system. Objective: The aim of this study is to assess the effect of an eRegistry with DHIs compared with a simple digital data entry tool without DHIs in the community and frontline health facilities. Methods: The eRegMat is a cluster-randomized controlled trial conducted in the Matlab North and Matlab South subdistricts in the Chandpur district, Bangladesh, where health facilities are currently using the eRegistry for digital tracking of the health status of pregnant women longitudinally. The intervention arm received 3 superimposed data-driven DHIs: health worker clinical decision support, health worker feedback dashboards with action items, and targeted client communication to pregnant women. The primary outcomes are appropriate screening as well as management of hypertension during pregnancy and timely antenatal care attendance. The secondary outcomes include morbidity and mortality in the perinatal period as well as timely first antenatal care visit; successful referrals for anemia, diabetes, or hypertension during pregnancy; and facility delivery. Results: The eRegistry and DHIs were co-designed with end users between 2016 and 2018. The eRegistry was implemented in the study area in July 2018. Recruitment for the trial started in October 2018 and ended in June 2020, followed by an 8-month follow-up period to capture outcome data until February 2021. Trial results will be available for publication in June 2021. Conclusions: This trial allows the simultaneous assessment of multiple integrated DHIs for strengthening the health system and aims to provide evidence for its implementation. The study design and outcomes are geared toward informing the living review process of the guidelines for implementing DHIs. Trial Registration: ISRCTN Registry ISRCTN69491836; https://www.isrctn.com/ISRCTN69491836 International Registered Report Identifier (IRRID): DERR1-10.2196/26918 %M 34255723 %R 10.2196/26918 %U https://www.researchprotocols.org/2021/7/e26918 %U https://doi.org/10.2196/26918 %U http://www.ncbi.nlm.nih.gov/pubmed/34255723 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 7 %P e29614 %T Preferences of the Public for Sharing Health Data: Discrete Choice Experiment %A Viberg Johansson,Jennifer %A Bentzen,Heidi Beate %A Shah,Nisha %A Haraldsdóttir,Eik %A Jónsdóttir,Guðbjörg Andrea %A Kaye,Jane %A Mascalzoni,Deborah %A Veldwijk,Jorien %+ Centre for Research Ethics & Bioethics, Department of Public Health and Caring Sciences, Uppsala Universitet, Box 564, Uppsala, SE-751 22, Sweden, 46 184716288, jennifer.viberg@crb.uu.se %K preferences %K discrete choice experiment %K health data %K secondary use %K willingness to share %D 2021 %7 5.7.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people’s preferences for sharing digital health data. Objective: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts. Methods: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates. Results: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents’ willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels. Conclusions: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism. %M 36260402 %R 10.2196/29614 %U https://medinform.jmir.org/2021/7/e29614 %U https://doi.org/10.2196/29614 %U http://www.ncbi.nlm.nih.gov/pubmed/36260402 %0 Journal Article %@ 2563-6316 %I JMIR Publications %V 2 %N 2 %P e25560 %T Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study %A Surodina,Svitlana %A Lam,Ching %A Grbich,Svetislav %A Milne-Ives,Madison %A van Velthoven,Michelle %A Meinert,Edward %+ Centre for Health Technology, University of Plymouth, 6 Kirkby Place, Room 2, Plymouth, PL4 6DN, United Kingdom, 44 1752600600, edward.meinert@plymouth.ac.uk %K data collection %K herpes simplex virus %K registries %K machine learning %K risk assessment %K artificial intelligence %K medical information system %K user-centered design %K predictor %K risk %D 2021 %7 11.6.2021 %9 Original Paper %J JMIRx Med %G English %X Background: Researching people with herpes simplex virus (HSV) is challenging because of poor data quality, low user engagement, and concerns around stigma and anonymity. Objective: This project aimed to improve data collection for a real-world HSV registry by identifying predictors of HSV infection and selecting a limited number of relevant questions to ask new registry users to determine their level of HSV infection risk. Methods: The US National Health and Nutrition Examination Survey (NHANES, 2015-2016) database includes the confirmed HSV type 1 and type 2 (HSV-1 and HSV-2, respectively) status of American participants (14-49 years) and a wealth of demographic and health-related data. The questionnaires and data sets from this survey were used to form two data sets: one for HSV-1 and one for HSV-2. These data sets were used to train and test a model that used a random forest algorithm (devised using Python) to minimize the number of anonymous lifestyle-based questions needed to identify risk groups for HSV. Results: The model selected a reduced number of questions from the NHANES questionnaire that predicted HSV infection risk with high accuracy scores of 0.91 and 0.96 and high recall scores of 0.88 and 0.98 for the HSV-1 and HSV-2 data sets, respectively. The number of questions was reduced from 150 to an average of 40, depending on age and gender. The model, therefore, provided high predictability of risk of infection with minimal required input. Conclusions: This machine learning algorithm can be used in a real-world evidence registry to collect relevant lifestyle data and identify individuals’ levels of risk of HSV infection. A limitation is the absence of real user data and integration with electronic medical records, which would enable model learning and improvement. Future work will explore model adjustments, anonymization options, explicit permissions, and a standardized data schema that meet the General Data Protection Regulation, Health Insurance Portability and Accountability Act, and third-party interface connectivity requirements. %M 37725536 %R 10.2196/25560 %U https://xmed.jmir.org/2021/2/e25560 %U https://doi.org/10.2196/25560 %U http://www.ncbi.nlm.nih.gov/pubmed/37725536 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 5 %P e28164 %T A Real-World Rheumatology Registry and Research Consortium: The German RheumaDatenRhePort (RHADAR) Registry %A Kleinert,Stefan %A Bartz-Bazzanella,Peter %A von der Decken,Cay %A Knitza,Johannes %A Witte,Torsten %A Fekete,Sándor P %A Konitzny,Matthias %A Zink,Alexander %A Gauler,Georg %A Wurth,Patrick %A Aries,Peer %A Karberg,Kirsten %A Kuhn,Christoph %A Schuch,Florian %A Späthling-Mestekemper,Susanna %A Vorbrüggen,Wolfgang %A Englbrecht,Matthias %A Welcker,Martin %A , %+ Praxisgemeinschaft Rheumatologie-Nephrologie, Möhrendorferstr 1c, Erlangen, Germany, 49 9131 890031, stefan.kleinert@pgrn.de %K registry %K rheumatology %K real-world data %K symptom checker %K patient-reported outcomes %D 2021 %7 20.5.2021 %9 Viewpoint %J J Med Internet Res %G English %X Real-world data are crucial to continuously improve the management of patients with rheumatic and musculoskeletal diseases (RMDs). The German RheumaDatenRhePort (RHADAR) registry encompasses a network of rheumatologists and researchers in Germany providing pseudonymized real-world patient data and allowing timely and continuous improvement in the care of RMD patients. The RHADAR modules allow automated anamnesis and adaptive coordination of appointments regarding individual urgency levels. Further modules focus on the collection and integration of electronic patient-reported outcomes in between consultations. The digital RHADAR modules ultimately allow a patient-centered adaptive approach to integrated medical care starting as early as possible in the disease course. Such a closed-loop system consisting of various modules along the whole patient pathway enables comprehensive and timely patient management in an unprecedented manner. %M 34014170 %R 10.2196/28164 %U https://www.jmir.org/2021/5/e28164 %U https://doi.org/10.2196/28164 %U http://www.ncbi.nlm.nih.gov/pubmed/34014170 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 1 %P e22296 %T Electronic Health Records–Based Cardio-Oncology Registry for Care Gap Identification and Pragmatic Research: Procedure and Observational Study %A Chandra,Alvin %A Philips,Steven T %A Pandey,Ambarish %A Basit,Mujeeb %A Kannan,Vaishnavi %A Sara,Evan J %A Das,Sandeep R %A Lee,Simon J C %A Haley,Barbara %A Willett,DuWayne L %A Zaha,Vlad G %+ Cardiology Division, Department of Internal Medicine, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390-8568, United States, 1 214 648 1400, vlad.zaha@utsouthwestern.edu %K electronic health records %K cardio-oncology %K patient registry %K heart failure %K screening %D 2021 %7 12.5.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: Professional society guidelines are emerging for cardiovascular care in cancer patients. However, it is not yet clear how effectively the cancer survivor population is screened and treated for cardiomyopathy in contemporary clinical practice. As electronic health records (EHRs) are now widely used in clinical practice, we tested the hypothesis that an EHR-based cardio-oncology registry can address these questions. Objective: The aim of this study was to develop an EHR-based pragmatic cardio-oncology registry and, as proof of principle, to investigate care gaps in the cardiovascular care of cancer patients. Methods: We generated a programmatically deidentified, real-time EHR-based cardio-oncology registry from all patients in our institutional Cancer Population Registry (N=8275, 2011-2017). We investigated: (1) left ventricular ejection fraction (LVEF) assessment before and after treatment with potentially cardiotoxic agents; and (2) guideline-directed medical therapy (GDMT) for left ventricular dysfunction (LVD), defined as LVEF<50%, and symptomatic heart failure with reduced LVEF (HFrEF), defined as LVEF<50% and Problem List documentation of systolic congestive heart failure or dilated cardiomyopathy. Results: Rapid development of an EHR-based cardio-oncology registry was feasible. Identification of tests and outcomes was similar using the EHR-based cardio-oncology registry and manual chart abstraction (100% sensitivity and 83% specificity for LVD). LVEF was documented prior to initiation of cancer therapy in 19.8% of patients. Prevalence of postchemotherapy LVD and HFrEF was relatively low (9.4% and 2.5%, respectively). Among patients with postchemotherapy LVD or HFrEF, those referred to cardiology had a significantly higher prescription rate of a GDMT. Conclusions: EHR data can efficiently populate a real-time, pragmatic cardio-oncology registry as a byproduct of clinical care for health care delivery investigations. %M 33797396 %R 10.2196/22296 %U https://cardio.jmir.org/2021/1/e22296 %U https://doi.org/10.2196/22296 %U http://www.ncbi.nlm.nih.gov/pubmed/33797396 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 1 %P e20470 %T Prototypical Clinical Trial Registry Based on Fast Healthcare Interoperability Resources (FHIR): Design and Implementation Study %A Gulden,Christian %A Blasini,Romina %A Nassirian,Azadeh %A Stein,Alexandra %A Altun,Fatma Betül %A Kirchner,Melanie %A Prokosch,Hans-Ulrich %A Boeker,Martin %+ Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Wetterkreuz 15, Erlangen, 91058, Germany, 49 9131 85 47291, christian.gulden@fau.de %K clinical trials %K trials registry %K health information interoperability %K data sharing %K HL7 FHIR %D 2021 %7 12.1.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Clinical trial registries increase transparency in medical research by making information and results of planned, ongoing, and completed studies publicly available. However, the registration of clinical trials remains a time-consuming manual task complicated by the fact that the same studies often need to be registered in different registries with different data entry requirements and interfaces. Objective: This study investigates how Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) may be used as a standardized format for exchanging and storing clinical trial records. Methods: We designed and prototypically implemented an open-source central trial registry containing records from university hospitals, which are automatically exported and updated by local study management systems. Results: We provided an architecture and implementation of a multisite clinical trials registry based on HL7 FHIR as a data storage and exchange format. Conclusions: The results show that FHIR resources establish a harmonized view of study information from heterogeneous sources by enabling automated data exchange between trial centers and central study registries. %M 33433393 %R 10.2196/20470 %U https://medinform.jmir.org/2021/1/e20470 %U https://doi.org/10.2196/20470 %U http://www.ncbi.nlm.nih.gov/pubmed/33433393 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 9 %N 4 %P e20352 %T Time to Treatment and In-Hospital Major Adverse Cardiac Events Among Patients With ST-Segment Elevation Myocardial Infarction Who Underwent Primary Percutaneous Coronary Intervention (PCI) According to the 24/7 Primary PCI Service Registry in Iran: Cross-Sectional Study %A Nozari,Younes %A Geraiely,Babak %A Alipasandi,Kian %A Mortazavi,Seyedeh Hamideh %A Omidi,Negar %A Aghajani,Hassan %A Amirzadegan,Alireza %A Pourhoseini,Hamidreza %A Salarifar,Mojtaba %A Alidoosti,Mohammad %A Haji-Zeinali,Ali-Mohammad %A Nematipour,Ebrahim %A Nomali,Mahin %+ Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, North Kargar St, Tehran, Iran, 98 9121721474, k.alipasandi1988@gmail.com %K ST-segment elevation myocardial infarction %K time to treatment %K percutaneous coronary intervention %K registries %K Iran %D 2020 %7 16.12.2020 %9 Original Paper %J Interact J Med Res %G English %X Background: Performing primary percutaneous coronary intervention (PCI) as a preferred reperfusion strategy for patients with ST-segment elevation myocardial infarction (STEMI) may be associated with major adverse cardiocerebrovascular events (MACCEs). Thus, timely primary PCI has been emphasized in order to improve outcomes. Despite guideline recommendations on trying to reduce the door-to-balloon time to <90 minutes in order to reduce mortality, less attention has been paid to other components of time to treatment, such as the symptom-to-balloon time, as an indicator of the total ischemic time, which includes the symptom-to-door time and door-to-balloon time, in terms of clinical outcomes of patients with STEMI undergoing primary PCI. Objective: We aimed to determine the association between each component of time to treatment (ie, symptom-to-door time, door-to-balloon time, and symptom-to-balloon time) and in-hospital MACCEs among patients with STEMI who underwent primary PCI. Methods: In this observational study, according to a prospective primary PCI 24/7 service registry, adult patients with STEMI who underwent primary PCI in one of six catheterization laboratories of Tehran Heart Center from November 2015 to August 2019, were studied. The primary outcome was in-hospital MACCEs, which was a composite index consisting of cardiac death, revascularization (ie, target vessel revascularization/target lesion revascularization), myocardial infarction, and stroke. It was compared at different levels of time to treatment (ie, symptom-to-door and door-to-balloon time <90 and ≥90 minutes, and symptom-to-balloon time <180 and ≥180 minutes). Data were analyzed using SPSS software version 24 (IBM Corp), with descriptive statistics, such as frequency, percentage, mean, and standard deviation, and statistical tests, such as chi-square test, t test, and univariate and multivariate logistic regression analyses, and with a significance level of <.05 and 95% CIs for odds ratios (ORs). Results: Data from 2823 out of 3204 patients were analyzed (mean age of 59.6 years, SD 11.6 years; 79.5% male [n=2243]; completion rate: 88.1%). Low proportions of symptom-to-door time ≤90 minutes and symptom-to-balloon time ≤180 minutes were observed among the study patients (579/2823, 20.5% and 691/2823, 24.5%, respectively). Overall, 2.4% (69/2823) of the patients experienced in-hospital MACCEs, and cardiac death (45/2823, 1.6%) was the most common cardiac outcome. In the univariate analysis, the symptom-to-balloon time predicted in-hospital MACCEs (OR 2.2, 95% CI 1.1-4.4; P=.03), while the symptom-to-door time (OR 1.4, 95% CI 0.7-2.6; P=.34) and door-to-balloon time (OR 1.1, 95% CI 0.6-1.8, P=.77) were not associated with in-hospital MACCEs. In the multivariate analysis, only symptom-to-balloon time ≥180 minutes was associated with in-hospital MACCEs and was a predictor of in-hospital MACCEs (OR 2.3, 95% CI 1.1-5.2; P=.04). Conclusions: A longer symptom-to-balloon time was the only component associated with higher in-hospital MACCEs in the present study. Efforts should be made to shorten the symptom-to-balloon time in order to improve in-hospital MACCEs. International Registered Report Identifier (IRRID): RR2-10.2196/13161 %M 33325826 %R 10.2196/20352 %U http://www.i-jmr.org/2020/4/e20352/ %U https://doi.org/10.2196/20352 %U http://www.ncbi.nlm.nih.gov/pubmed/33325826 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 9 %N 12 %P e23973 %T The Swiss Prison Study (SWIPS): Protocol for Establishing a Public Health Registry of Prisoners in Switzerland %A Gaisl,Thomas %A Musli,Naser %A Baumgartner,Patrick %A Meier,Marc %A Rampini,Silvana K %A Blozik,Eva %A Battegay,Edouard %A Kohler,Malcolm %A Saxena,Shekhar %+ Department of Pulmonology, University Hospital Zurich, Rämistrasse 100, Zurich, 8091, Switzerland, 41 762318339, thomasgaisl@hsph.harvard.edu %K public health %K prison medicine %K epidemiology %K health register %D 2020 %7 8.12.2020 %9 Protocol %J JMIR Res Protoc %G English %X Background: The health aspects, disease frequencies, and specific health interests of prisoners and refugees are poorly understood. Importantly, access to the health care system is limited for this vulnerable population. There has been no systematic investigation to understand the health issues of inmates in Switzerland. Furthermore, little is known on how recent migration flows in Europe may have affected the health conditions of inmates. Objective: The Swiss Prison Study (SWIPS) is a large-scale observational study with the aim of establishing a public health registry in northern-central Switzerland. The primary objective is to establish a central database to assess disease prevalence (ie, International Classification of Diseases-10 codes [German modification]) among prisoners. The secondary objectives include the following: (1) to compare the 2015 versus 2020 disease prevalence among inmates against a representative sample from the local resident population, (2) to assess longitudinal changes in disease prevalence from 2015 to 2020 by using cross-sectional medical records from all inmates at the Police Prison Zurich, Switzerland, and (3) to identify unrecognized health problems to prepare successful public health strategies. Methods: Demographic and health-related data such as age, sex, country of origin, duration of imprisonment, medication (including the drug name, brand, dosage, and release), and medical history (including the International Classification of Diseases-10 codes [German modification] for all diagnoses and external results that are part of the medical history in the prison) have been deposited in a central register over a span of 5 years (January 2015 to August 2020). The final cohort is expected to comprise approximately 50,000 to 60,000 prisoners from the Police Prison Zurich, Switzerland. Results: This study was approved on August 5, 2019 by the ethical committee of the Canton of Zurich with the registration code KEK-ZH No. 2019-01055 and funded in August 2020 by the “Walter and Gertrud Siegenthaler” foundation and the “Theodor and Ida Herzog-Egli” foundation. This study is registered with the International Standard Randomized Controlled Trial Number registry. Data collection started in August 2019 and results are expected to be published in 2021. Findings will be disseminated through scientific papers as well as presentations and public events. Conclusions: This study will construct a valuable database of information regarding the health of inmates and refugees in Swiss prisons and will act as groundwork for future interventions in this vulnerable population. Trial Registration: ISRCTN registry ISRCTN11714665; http://www.isrctn.com/ISRCTN11714665 International Registered Report Identifier (IRRID): DERR1-10.2196/23973 %M 33099459 %R 10.2196/23973 %U https://www.researchprotocols.org/2020/12/e23973 %U https://doi.org/10.2196/23973 %U http://www.ncbi.nlm.nih.gov/pubmed/33099459 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 6 %N 4 %P e21939 %T Leveraging a Cloud-Based Critical Care Registry for COVID-19 Pandemic Surveillance and Research in Low- and Middle-Income Countries %A , %A Hashmi,Madiha %A Beane,Abi %A Murthy,Srinivas %A Dondorp,Arjen M %A Haniffa,Rashan %+ Collaboration for Research, Improvement and Training in Critical Care in Asia, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand, 66 07841131252, abi@nicslk.com %K critical care %K registry %K informatics %K COVID-19 %K severe acute respiratory infection %K pandemic %K surveillance %K cloud-based %K research %K low-and-middle-income countries %D 2020 %7 23.11.2020 %9 Viewpoint %J JMIR Public Health Surveill %G English %X The COVID-19 pandemic has revealed limitations in real-time surveillance needed for responsive health care action in low- and middle-income countries (LMICs). The Pakistan Registry for Intensive CarE (PRICE) was adapted to enable International Severe Acute Respiratory and emerging Infections Consortium (ISARIC)–compliant real-time reporting of severe acute respiratory infection (SARI). The cloud-based common data model and standardized nomenclature of the registry platform ensure interoperability of data and reporting between regional and global stakeholders. Inbuilt analytics enable stakeholders to visualize individual and aggregate epidemiological, clinical, and operational data in real time. The PRICE system operates in 5 of 7 administrative regions of Pakistan. The same platform supports acute and critical care registries in eleven countries in South Asia and sub-Saharan Africa. ISARIC-compliant SARI reporting was successfully implemented by leveraging the existing PRICE infrastructure in all 49 member intensive care units (ICUs), enabling clinicians, operational leads, and established stakeholders with responsibilities for coordinating the pandemic response to access real-time information on suspected and confirmed COVID-19 cases (N=592 as of May 2020) via secure registry portals. ICU occupancy rates, use of ICU resources, mechanical ventilation, renal replacement therapy, and ICU outcomes were reported through registry dashboards. This information has facilitated coordination of critical care resources, health care worker training, and discussions on treatment strategies. The PRICE network is now being recruited to international multicenter clinical trials regarding COVID-19 management, leveraging the registry platform. Systematic and standardized reporting of SARI is feasible in LMICs. Existing registry platforms can be adapted for pandemic research, surveillance, and resource planning. %M 33147162 %R 10.2196/21939 %U http://publichealth.jmir.org/2020/4/e21939/ %U https://doi.org/10.2196/21939 %U http://www.ncbi.nlm.nih.gov/pubmed/33147162 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 9 %N 10 %P e18366 %T A Systematic Framework for Analyzing Observation Data in Patient-Centered Registries: Case Study for Patients With Depression %A Zolnoori,Maryam %A Williams,Mark D %A Leasure,William B %A Angstman,Kurt B %A Ngufor,Che %+ Mayo Clinic, 200 1st St SW, Rochester, MN 55902, Rochester, MN, , United States, 1 3175151950, Zolnoori.Maryam@mayo.edu %K patient-centered registry %K collaborative care model %K care coordination management %K integrated behavior health %K systematic framework %D 2020 %7 29.10.2020 %9 Protocol %J JMIR Res Protoc %G English %X Background: Patient-centered registries are essential in population-based clinical care for patient identification and monitoring of outcomes. Although registry data may be used in real time for patient care, the same data may further be used for secondary analysis to assess disease burden, evaluation of disease management and health care services, and research. The design of a registry has major implications for the ability to effectively use these clinical data in research. Objective: This study aims to develop a systematic framework to address the data and methodological issues involved in analyzing data in clinically designed patient-centered registries. Methods: The systematic framework was composed of 3 major components: visualizing the multifaceted and heterogeneous patient-centered registries using a data flow diagram, assessing and managing data quality issues, and identifying patient cohorts for addressing specific research questions. Results: Using a clinical registry designed as a part of a collaborative care program for adults with depression at Mayo Clinic, we were able to demonstrate the impact of the proposed framework on data integrity. By following the data cleaning and refining procedures of the framework, we were able to generate high-quality data that were available for research questions about the coordination and management of depression in a primary care setting. We describe the steps involved in converting clinically collected data into a viable research data set using registry cohorts of depressed adults to assess the impact on high-cost service use. Conclusions: The systematic framework discussed in this study sheds light on the existing inconsistency and data quality issues in patient-centered registries. This study provided a step-by-step procedure for addressing these challenges and for generating high-quality data for both quality improvement and research that may enhance care and outcomes for patients. International Registered Report Identifier (IRRID): DERR1-10.2196/18366 %M 33118958 %R 10.2196/18366 %U http://www.researchprotocols.org/2020/10/e18366/ %U https://doi.org/10.2196/18366 %U http://www.ncbi.nlm.nih.gov/pubmed/33118958 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 10 %P e17420 %T Enabling External Inquiries to an Existing Patient Registry by Using the Open Source Registry System for Rare Diseases: Demonstration of the System Using the European Society for Immunodeficiencies Registry %A Scheible,Raphael %A Kadioglu,Dennis %A Ehl,Stephan %A Blum,Marco %A Boeker,Martin %A Folz,Michael %A Grimbacher,Bodo %A Göbel,Jens %A Klein,Christoph %A Nieters,Alexandra %A Rusch,Stephan %A Kindle,Gerhard %A Storf,Holger %+ Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Stefan-Meier-Str. 26, Freiburg, 79104, Germany, 49 761 203 69272, raphael.scheible@uniklinik-freiburg.de %K registry interoperability %K collaboration in research %K data findability %K registry software %D 2020 %7 7.10.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: The German Network on Primary Immunodeficiency Diseases (PID-NET) utilizes the European Society for Immunodeficiencies (ESID) registry as a platform for collecting data. In the context of PID-NET data, we show how registries based on custom software can be made interoperable for better collaborative access to precollected data. The Open Source Registry System for Rare Diseases (Open-Source-Registersystem für Seltene Erkrankungen [OSSE], in German) provides patient organizations, physicians, scientists, and other parties with open source software for the creation of patient registries. In addition, the necessary interoperability between different registries based on the OSSE, as well as existing registries, is supported, which allows those registries to be confederated at both the national and international levels. Objective: Data from the PID-NET registry should be made available in an interoperable manner without losing data sovereignty by extending the existing custom software of the registry using the OSSE registry framework. Methods: This paper describes the following: (1) the installation and configuration of the OSSE bridgehead, (2) an approach using a free toolchain to set up the required interfaces to connect a registry with the OSSE bridgehead, and (3) the decentralized search, which allows the formulation of inquiries that are sent to a selected set of registries of interest. Results: PID-NET uses the established and highly customized ESID registry software. By setting up a so-called OSSE bridgehead, PID-NET data are made interoperable according to a federated approach, and centrally formulated inquiries for data can be received. As the first registry to use the OSSE bridgehead, the authors introduce an approach using a free toolchain to efficiently implement and maintain the required interfaces. Finally, to test and demonstrate the system, two inquiries are realized using the graphical query builder. By establishing and interconnecting an OSSE bridgehead with the underlying ESID registry, confederated queries for data can be received and, if desired, the inquirer can be contacted to further discuss any requirements for cooperation. Conclusions: The OSSE offers an infrastructure that provides the possibility of more collaborative and transparent research. The decentralized search functionality includes registries into one search application while still maintaining data sovereignty. The OSSE bridgehead enables any registry software to be integrated into the OSSE network. The proposed toolchain to set up the required interfaces consists of freely available software components that are well documented. The use of the decentralized search is uncomplicated to use and offers a well-structured, yet still improvable, graphical user interface to formulate queries. %M 33026355 %R 10.2196/17420 %U http://medinform.jmir.org/2020/10/e17420/ %U https://doi.org/10.2196/17420 %U http://www.ncbi.nlm.nih.gov/pubmed/33026355 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 7 %P e19081 %T The Kaiser Permanente Northern California Adult Alcohol Registry, an Electronic Health Records-Based Registry of Patients With Alcohol Problems: Development and Implementation %A Palzes,Vanessa A %A Weisner,Constance %A Chi,Felicia W %A Kline-Simon,Andrea H %A Satre,Derek D %A Hirschtritt,Matthew E %A Ghadiali,Murtuza %A Sterling,Stacy %+ Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, United States, 1 510 891 3743, vanessa.a.palzes@kp.org %K electronic health records %K alcohol %K registry %K unhealthy alcohol use %K alcohol use disorder %K recovery %K secondary data %D 2020 %7 22.7.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: Electronic health record (EHR)–based disease registries have aided health care professionals and researchers in increasing their understanding of chronic illnesses, including identifying patients with (or at risk of developing) conditions and tracking treatment progress and recovery. Despite excessive alcohol use being a major contributor to the global burden of disease and disability, no registries of alcohol problems exist. EHR-based data in Kaiser Permanente Northern California (KPNC), an integrated health system that conducts systematic alcohol screening, which provides specialty addiction medicine treatment internally and has a membership of over 4 million members that are highly representative of the US population with access to care, provide a unique opportunity to develop such a registry. Objective: Our objectives were to describe the development and implementation of a protocol for assembling the KPNC Adult Alcohol Registry, which may be useful to other researchers and health systems, and to characterize the registry cohort descriptively, including underlying health conditions. Methods: Inclusion criteria were adult members with unhealthy alcohol use (using National Institute on Alcohol Abuse and Alcoholism guidelines), an alcohol use disorder (AUD) diagnosis, or an alcohol-related health problem between June 1, 2013, and May 31, 2019. We extracted patients’ longitudinal, multidimensional EHR data from 1 year before their date of eligibility through May 31, 2019, and conducted descriptive analyses. Results: We identified 723,604 adult patients who met the registry inclusion criteria at any time during the study period: 631,780 with unhealthy alcohol use, 143,690 with an AUD diagnosis, and 18,985 with an alcohol-related health problem. We identified 65,064 patients who met two or more criteria. Of the 4,973,195 adult patients with at least one encounter with the health system during the study period, the prevalence of unhealthy alcohol use was 13% (631,780/4,973,195), the prevalence of AUD diagnoses was 3% (143,690/4,973,195), and the prevalence of alcohol-related health problems was 0.4% (18,985/4,973,195). The registry cohort was 60% male (n=432,847) and 41% non-White (n=295,998) and had a median age of 41 years (IQR=27). About 48% (n=346,408) had a chronic medical condition, 18% (n=130,031) had a mental health condition, and 4% (n=30,429) had a drug use disorder diagnosis. Conclusions: We demonstrated that EHR-based data collected during clinical care within an integrated health system could be leveraged to develop a registry of patients with alcohol problems that is flexible and can be easily updated. The registry’s comprehensive patient-level data over multiyear periods provides a strong foundation for robust research addressing critical public health questions related to the full course and spectrum of alcohol problems, including recovery, which would complement other methods used in alcohol research (eg, population-based surveys, clinical trials). %M 32706676 %R 10.2196/19081 %U http://medinform.jmir.org/2020/7/e19081/ %U https://doi.org/10.2196/19081 %U http://www.ncbi.nlm.nih.gov/pubmed/32706676 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 5 %N 2 %P e122 %T A Registry for Evaluation of Efficiency and Safety of Surgical Treatment of Cartilage Defects: The German Cartilage Registry (KnorpelRegister DGOU) %A Maurer,Julia %A Grotejohann,Birgit %A Jenkner,Carolin %A Schneider,Carla %A Flury,Thomas %A Tassoni,Adrian %A Angele,Peter %A Fritz,Jürgen %A Albrecht,Dirk %A Niemeyer,Philipp %+ Clinical Trials Unit, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Elsaesser Str 2, Freiburg im Breisgau, 79110, Germany, 49 761 270 ext 77830, julia.maurer@uniklinik-freiburg.de %K ankle joint %K cartilage defect %K chondral defect %K hip joint %K knee joint %K patient registry %D 2016 %7 29.06.2016 %9 Original Paper %J JMIR Res Protoc %G English %X Background: The need for documentation in cartilage defects is as obvious as in other medical specialties. Cartilage defects can cause significant pain, and lead to reduced quality of life and loss of function of the affected joint. The risk of developing osteoarthritis is high. Therefore, the socioeconomic burden of cartilage defects should not be underestimated. Objective: The objective of our study was to implement and maintain a registry of all patients undergoing surgical treatment of cartilage defects. Methods: We designed this multicenter registry for adults whose cartilage defects of a knee, ankle, or hip joint are treated surgically. The registry consists of two parts: one for the physician and one for the patient. Data for both parts will be gathered at baseline and at 6-, 12-, 24-, 36-, 60-, and 120-month follow-ups. Results: To date, a wide range of German, Swiss, and Austrian trial sites are taking part in the German Cartilage Registry, soon to be followed by further sites. More than 2124 (as of January 31, 2016) cases are already documented and the first publications have been released. Conclusions: The German Cartilage Registry addresses fundamental issues regarding the current medical care situation of patients with cartilage defects of knee, ankle, and hip joints. In addition, the registry will help to identify various procedure-specific complications, along with putative advantages and disadvantages of different chondrocyte products. It provides an expanding large-scale, unselected, standardized database for cost and care research for further retrospective studies. Trial Registration: German Clinical Trials Register: DRKS00005617; https://drks-neu.uniklinik-freiburg.de/ drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00005617 (Archived by WebCite at http://www.webcitation.org/6hbFqSws0) %M 27357998 %R 10.2196/resprot.5895 %U http://www.researchprotocols.org/2016/2/e122/ %U https://doi.org/10.2196/resprot.5895 %U http://www.ncbi.nlm.nih.gov/pubmed/27357998 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 6 %P e141 %T Medical Registry Data Collection Efficiency: A Crossover Study Comparing Web-Based Electronic Data Capture and a Standard Spreadsheet %A Staziaki,Pedro Vinícius %A Kim,Phillip %A Vadvala,Harshna V %A Ghoshhajra,Brian B %+ Massachusetts General Hospital, Department of Radiology, Harvard Medical School, 165 Cambridge St, Suite 400, Boston, MA, 02114, United States, 1 6177263745, bghoshhajra@mgh.harvard.edu %K electronic data capture %K clinical research %K translational research %K registry %K data management %D 2016 %7 08.06.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Electronic medical records and electronic data capture (EDC) have changed data collection in clinical and translational research. However, spreadsheet programs, such as Microsoft Excel, are still used as data repository to record and organize patient data for research. Objective: The objective of this study is to assess the efficiency of EDC as against a standard spreadsheet in regards to time to collect data and data accuracy, measured in number of errors after adjudication. Methods: This was a crossover study comparing the time to collect data in minutes between EDC and a spreadsheet. The EDC tool used was Research Electronic Data Capture (REDCap), whereas the spreadsheet was Microsoft Excel. The data collected was part of a registry of patients who underwent coronary computed tomography angiography in the emergency setting. Two data collectors with the same experience went over the same patients and collected relevant data on a case report form identical to the one used in our Emergency Department (ED) registry. Data collection tool was switched after the patient that represented half the cohort. For this, the patient cohort was exactly 30 days of our ED coronary Computed Tomography Angiography registry and the point of crossover was determined beforehand to be 15 days. We measured the number of patients admitted, and time to collect data. Accuracy was defined as absence of blank fields and errors, and was assessed by comparing data between data collectors and counting every time the data differed. Statistical analysis was made using paired t -test. Results: The study included 61 patients (122 observations) and 55 variables. The crossover occurred after the 30th patient. Mean time to collect data using EDC in minutes was 6.2±2.3, whereas using Excel was 8.0±2.0 (P <.001), a difference of 1.8 minutes between both means (22%). The cohort was evenly distributed with 3 admissions in the first half of the crossover and 4 in the second half. We saw 2 (<0.1%) continuous variable typos in the spreadsheet that a single data collector made. There were no blank fields. The data collection tools showed no differences in accuracy of data on comparison. Conclusions: Data collection for our registry with an EDC tool was faster than using a spreadsheet, which in turn allowed more efficient follow-up of cases. %M 27277523 %R 10.2196/jmir.5576 %U http://www.jmir.org/2016/6/e141/ %U https://doi.org/10.2196/jmir.5576 %U http://www.ncbi.nlm.nih.gov/pubmed/27277523 %0 Journal Article %@ 14388871 %I JMIR Publications Inc. %V 15 %N 9 %P e202 %T A Web-Based Interactive Diabetes Registry for Health Care Management and Planning in Saudi Arabia %A Al-Rubeaan,Khalid A %A Youssef,Amira M %A Subhani,Shazia N %A Ahmad,Najlaa A %A Al-Sharqawi,Ahmad H %A Ibrahim,Heba M %+ Strategic Center for Diabetes Research, University Diabetes Centre, King Saud University, PO Box 18397, Riyadh, 11415, Saudi Arabia, 966 11 282 5402, krubean@ksu.edu.sa %K diabetes mellitus %K registries %K geographic information systems %K medical records systems, computerized %K health planning %K research report %K data bank, factual %K epidemiology %D 2013 %7 11.09.2013 %9 Viewpoint %J J Med Internet Res %G English %X Background: Worldwide, eHealth is a rapidly growing technology. It provides good quality health services at lower cost and increased availability. Diabetes has reached an epidemic stage in Saudi Arabia and has a medical and economic impact at a countrywide level. Data are greatly needed to better understand and plan to prevent and manage this medical problem. Objective: The Saudi National Diabetes Registry (SNDR) is an electronic medical file supported by clinical, investigational, and management data. It functions as a monitoring tool for medical, social, and cultural bases for primary and secondary prevention programs. Economic impact, in the form of direct or indirect cost, is part of the registry’s scope. The registry’s geographic information system (GIS) produces a variety of maps for diabetes and associated diseases. In addition to availability and distribution of health facilities in the Kingdom, GIS data provide health planners with the necessary information to make informed decisions. The electronic data bank serves as a research tool to help researchers for both prospective and retrospective studies. Methods: A Web-based interactive GIS system was designed to serve as an electronic medical file for diabetic patients retrieving data from medical files by trained registrars. Data was audited and cleaned before it was archived in the electronic filing system. It was then used to produce epidemiologic, economic, and geographic reports. A total of 84,942 patients were registered from 2000 to 2012, growing by 10% annually. Results: The SNDR reporting system for epidemiology data gives better understanding of the disease pattern, types, and gender characteristics. Part of the reporting system is to assess quality of health care using different parameters, such as HbA1c, that gives an impression of good diabetes control for each institute. Economic reports give accurate cost estimation of different services given to diabetic patients, such as the annual insulin cost per patient for type 1, type 2, and gestational diabetes, which are 1155 SR (US $308), 1406 SR (US $375), and 1002 SR (US $267), respectively. Of this, 72.02% of the total insulin cost is spent on type 2 patients and 55.39% is in the form of premixed insulin. The SNDR can provide an accurate assessment of the services provided for research purposes. For example, only 27.00% of registered patients had an ophthalmic examination and only 71.10% of patients with proliferative retinopathy had laser therapy. Conclusions: The SNDR is an effective electronic medical file that can provide epidemiologic, economic, and geographic reports that can be used for disease management and health care planning. It is a useful tool for research and disease health care quality monitoring. %M 24025198 %R 10.2196/jmir.2722 %U http://www.jmir.org/2013/9/e202/ %U https://doi.org/10.2196/jmir.2722 %U http://www.ncbi.nlm.nih.gov/pubmed/24025198