JMIR Medical Informatics

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

A Practical Guideline to Safeguard Custom Applications in Hospital Setting: Maximizing the Use of and Minimizing the Security Risk of BYOD

Background: Allowing healthcare professionals to use personal mobile devices at work, known as bring-your-own-device (BYOD), has potential to support both hospital and the professionals to deliver effective and efficient care. Unfortunately, the guidelines are lacking on how hospitals should best integrate personal devices into hospital information systems, which include electronic medical records and custom applications developed by hospitals, while maintaining their existing privacy and security policies. The are also pertain deficiencies in BYOD in the area of guiding the development of the custom applications for patient care. Objective: This paper offers a qualitative analysis why and how BYOD can be implemented in hospital settings as well as provides an example of how Boston Children’s Hospital (BCH) has approached BYOD to develop custom applications to leverage the use of personal mobile devices for the clinicians in the hospital. Methods: Through a literature review, discussion with external security experts, and interviews with the leaders within the Information Systems Department at the Boston Children’s Hospital, we developed hospital appropriate BYOD guidelines for custom application development. After establishing the guidelines, the research team developed a mobile application, called TaskList, which could be an appropriate test case to determine security and privacy requirements for an application that will be deployed in a BYOD environment. Results: Fifteen practical recommendations were identified named BCH BYOD Guideline to Safeguard Custom Applications in Hospital Settings. The recommendations were grouped into 1) Authentication and authorization, 2) Data Management, 3) Safeguarding Application Environment, and 4) Remote Enforcement. Following the guidelines, a mobile, collaborative, real time TaskList application was developed on the iOS platform. The application listed shared tasks for patient and allowed a team of medical residents to check and update tasks through the course of the day and automatically provide real time update to the team members. The application was piloted with an inpatient pediatric ward team. Conclusions: The guideline was very useful for developers and managers when designing and implementing TaskList application that was developed and deployed at the Boston Children’s Hospital. The guideline could also be useful for similar requirements when an application need to be developed and deployed in BYOD healthcare settings where HIPAA requirements must be complied.

Journal Description

JMIR Medical Informatics (JMI, ISSN 2291-9694) focusses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals.

Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2013: 4.7), JMIR Med Inform has a different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.

JMIR Medical Informatics journal features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs (ready for deposit in PubMed Central/PubMed). The site is optimized for mobile and iPad use.

JMIR Medical Informatics adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics (http://www.jmir.org/issue/current).

 

Recent Articles:

  • Implementation details of the CIMIDx framework.

    CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency

    Abstract:

    Background: The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. Objective: We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called “CIMIDx”, based on representative association rules that support the diagnosis of medical images (mammograms). Methods: The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype’s classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user’s perspective. Results: We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information from 150 breast cancer survivors from hospitals and health centers. The CIMIDx prototype achieved high sensitivity of up to 99.29%, and accuracy of up to 98%. The second set of experiments evaluated CIMIDx use for breast health issues, using t tests and Pearson chi-square tests to assess differences, and binary logistic regression to estimate the odds ratio (OR) for the predictors’ use of CIMIDx. For the prototype usage statistics for the same 150 breast cancer survivors, we interviewed 114 (76.0%), through self-report questionnaires from CIMIDx blogs. The frequency of log-ins/person ranged from 0 to 30, total duration/person from 0 to 1500 minutes (25 hours). The 114 participants continued logging in to all phases, resulting in an intervention adherence rate of 44.3% (95% CI 33.2-55.9). The overall performance of the prototype for the good category, reported usefulness of the prototype (P=.77), overall satisfaction of the prototype (P=.31), ease of navigation (P=.89), user friendliness evaluation (P=.31), and overall satisfaction (P=.31). Positive evaluations given by 100 participants via a Web-based questionnaire supported our hypothesis. Conclusions: The present study shows that women felt favorably about the use of a generic fully automated cloud-based self- management prototype. The study also demonstrated that the CIMIDx prototype resulted in the detection of more cancers in screening and diagnosing patients, with an increased accuracy rate.

  • This is a royalty free image (http://pixabay.com/en/medical-drugs-tablets-inject-41834/).
License: CC0 Public Domain.

    Effects of Individual Health Topic Familiarity on Activity Patterns During Health Information Searches

    Abstract:

    Background: Non-medical professionals (consumers) are increasingly using the Internet to support their health information needs. However, the cognitive effort required to perform health information searches is affected by the consumer’s familiarity with health topics. Consumers may have different levels of familiarity with individual health topics. This variation in familiarity may cause misunderstandings because the information presented by search engines may not be understood correctly by the consumers. Objective: As a first step toward the improvement of the health information search process, we aimed to examine the effects of health topic familiarity on health information search behaviors by identifying the common search activity patterns exhibited by groups of consumers with different levels of familiarity. Methods: Each participant completed a health terminology familiarity questionnaire and health information search tasks. The responses to the familiarity questionnaire were used to grade the familiarity of participants with predefined health topics. The search task data were transcribed into a sequence of search activities using a coding scheme. A computational model was constructed from the sequence data using a Markov chain model to identify the common search patterns in each familiarity group. Results: Forty participants were classified into L1 (not familiar), L2 (somewhat familiar), and L3 (familiar) groups based on their questionnaire responses. They had different levels of familiarity with four health topics. The video data obtained from all of the participants were transcribed into 4595 search activities (mean 28.7, SD 23.27 per session). The most frequent search activities and transitions in all the familiarity groups were related to evaluations of the relevancy of selected web pages in the retrieval results. However, the next most frequent transitions differed in each group and a chi-squared test confirmed this finding (P<.001). Next, according to the results of a perplexity evaluation, the health information search patterns were best represented as a 5-gram sequence pattern. The most common patterns in group L1 were frequent query modifications, with relatively low search efficiency, and accessing and evaluating selected results from a health website. Group L2 performed frequent query modifications, but with better search efficiency, and accessed and evaluated selected results from a health website. Finally, the members of group L3 successfully discovered relevant results from the first query submission, performed verification by accessing several health websites after they discovered relevant results, and directly accessed consumer health information websites. Conclusions: Familiarity with health topics affects health information search behaviors. Our analysis of state transitions in search activities detected unique behaviors and common search activity patterns in each familiarity group during health information searches.

  • This is a royalty free image by hyena reality (http://www.freedigitalphotos.net/images/person-using-a-digital-tablet-photo-p265558).

    Real-Time Patient Survey Data During Routine Clinical Activities for Rapid-Cycle Quality Improvement

    Abstract:

    Background: Surveying patients is increasingly important for evaluating and improving health care delivery, but practical survey strategies during routine care activities have not been available. Objective: We examined the feasibility of conducting routine patient surveys in a primary care clinic using commercially available technology (Web-based survey creation, deployment on tablet computers, cloud-based management of survey data) to expedite and enhance several steps in data collection and management for rapid quality improvement cycles. Methods: We used a Web-based data management tool (survey creation, deployment on tablet computers, real-time data accumulation and display of survey results) to conduct four patient surveys during routine clinic sessions over a one-month period. Each survey consisted of three questions and focused on a specific patient care domain (dental care, waiting room experience, care access/continuity, Internet connectivity). Results: Of the 727 available patients during clinic survey days, 316 patients (43.4%) attempted the survey, and 293 (40.3%) completed the survey. For the four 3-question surveys, the average time per survey was overall 40.4 seconds, with a range of 5.4 to 20.3 seconds for individual questions. Yes/No questions took less time than multiple choice questions (average 9.6 seconds versus 14.0). Average response time showed no clear pattern by order of questions or by proctor strategy, but monotonically increased with number of words in the question (<20 words, 21-30 words, >30 words)—8.0, 11.8, 16.8, seconds, respectively. Conclusions: This technology-enabled data management system helped capture patient opinions, accelerate turnaround of survey data, with minimal impact on a busy primary care clinic. This new model of patient survey data management is feasible and sustainable in a busy office setting, supports and engages clinicians in the quality improvement process, and harmonizes with the vision of a learning health care system.

  • Screen capture of an application prototype to manage the PHQ-9 object.

    Information Persistence Services Designed to Support Home Care

    Abstract:

    Background: Due to the challenges faced by health and social care systems, in particular those related to actual demographic trends, home care emerges as a potentially cost-effective solution to answer the needs of citizens, and to allow the reallocation of resources to alternatives to hospitalization or institutionalization. Objective: Home care services require cooperation between different actors, including health and social caregivers, care receivers, and their informal caregivers (eg, relatives or friends), across time, space, and organizational boundaries. Therefore, it is foreseeable that eHealth services can contribute to their improvement. The aim of this study is to evaluate information persistence services based on the Reference Information Model (RIM) of the Health Level Seven (HL7) version 3 to support formal caregivers, both health and social care providers, and informal caregivers in the context of home care services. Methods: A pilot study was set up involving two Portuguese institutions that provide home care services for the elderly. Defining of information requirements was performed according to a comprehensive process. This included a review of the literature, observations of work activities, interviews with caregivers, care receivers and their relatives, analysis of paper documentation related to care receivers’ histories, health conditions and care plans, and brainstorming groups involving specialized professionals. Following this, information objects were implemented and validated. Results: The methodological approach, as well as the information persistence services, proved to be robust and adequate to specify, implement, and validate different types of information objects related to home care services for the elderly. This study also reinforces the application of the RIM of the HL7 version 3 beyond the strict scope of health care, allowing the persistence of not only health care information, but also information related to social assistance activities. Conclusions: This study contributes to the ongoing efforts related to the development of eHealth applications to improve the cooperation among formal health care and social caregivers, as well as care receivers and their informal caregivers.

  • Development and evaluation of a clinical decision support system (CDSS) for Sepsis. 
(A) Synopsis of the EHR database, distribution of vitals, states, actions. Likelihood functions were used to calculate state-specific transition and observation probabilities. (B) The state-action diagram describes underlying patient states, possible transitions and beliefs based on the values of the observed variables. There are two absorbing states, “Death” and “Dismissal”. The training of the POMDP model that is applied on the state-action space performs value iteration updates on a sample set of beliefs, effectively using a Monte Carlo approach for sampling together with dynamic programming for the calculation of the value iteration. (C) Belief (ie, probability distribution of the patient states) is updated based on the action taken and the new observations. At each time step patient vitals are observed and the action that corresponds to the optimal policy is taken. A new set of observations (vitals, tests) will lead to an updated belief that may lead to a new action to be undertaken. The update is asynchronous, as it is calculated on-the-fly as new information arrives.  (D) Evaluation of the CDSS framework was performed through 5-fold cross validation and data size sensitivity analysis.

    From Data to Optimal Decision Making: A Data-Driven, Probabilistic Machine Learning Approach to Decision Support for Patients With Sepsis

    Abstract:

    Background: A tantalizing question in medical informatics is how to construct knowledge from heterogeneous datasets, and as an extension, inform clinical decisions. The emergence of large-scale data integration in electronic health records (EHR) presents tremendous opportunities. However, our ability to efficiently extract informed decision support is limited due to the complexity of the clinical states and decision process, missing data and lack of analytical tools to advice based on statistical relationships. Objective: Development and assessment of a data-driven method that infers the probability distribution of the current state of patients with sepsis, likely trajectories, optimal actions related to antibiotic administration, prediction of mortality and length-of-stay. Methods: We present a data-driven, probabilistic framework for clinical decision support in sepsis-related cases. We first define states, actions, observations and rewards based on clinical practice, expert knowledge and data representations in an EHR dataset of 1492 patients. We then use Partially Observable Markov Decision Process (POMDP) model to derive the optimal policy based on individual patient trajectories and we evaluate the performance of the model-derived policies in a separate test set. Policy decisions were focused on the type of antibiotic combinations to administer. Multi-class and discriminative classifiers were used to predict mortality and length of stay. Results: Data-derived antibiotic administration policies led to a favorable patient outcome in 49% of the cases, versus 37% when the alternative policies were followed (P=1.3e-13). Sensitivity analysis on the model parameters and missing data argue for a highly robust decision support tool that withstands parameter variation and data uncertainty. When the optimal policy was followed, 387 patients (25.9%) have 90% of their transitions to better states and 503 patients (33.7%) patients had 90% of their transitions to worse states (P=4.0e-06), while in the non-policy cases, these numbers are 192 (12.9%) and 764 (51.2%) patients (P=4.6e-117), respectively. Furthermore, the percentage of transitions within a trajectory that lead to a better or better/same state are significantly higher by following the policy than for non-policy cases (605 vs 344 patients, P=8.6e-25). Mortality was predicted with an AUC of 0.7 and 0.82 accuracy in the general case and similar performance was obtained for the inference of the length-of-stay (AUC of 0.69 to 0.73 with accuracies from 0.69 to 0.82). Conclusions: A data-driven model was able to suggest favorable actions, predict mortality and length of stay with high accuracy. This work provides a solid basis for a scalable probabilistic clinical decision support framework for sepsis treatment that can be expanded to other clinically relevant states and actions, as well as a data-driven model that can be adopted in other clinical areas with sufficient training data.

  • Grading physician review of results.

    Teleophthalmology for First Nations Clients at Risk of Diabetic Retinopathy: A Mixed Methods Evaluation

    Abstract:

    Background: Access to health services is a particular challenge for First Nations (aboriginal Canadians) communities living in remote or underserviced areas. Teleophthalmology can provide them with the same level of retinal screening services provided to those in urban centers. This screening can lead to the identification of high-risk individuals who can then be monitored and receive treatment related to their diabetes or other health issues. Objective: The intent was to develop, implement, and evaluate a service delivery model for teleophthalmology screening and follow-up for at-risk and diabetic First Nations clients on Vancouver Island, British Columbia, Canada. Methods: A highly consultative, culturally appropriate, and collaborative approach was used to develop and deploy a teleophthalmology service delivery model to First Nations communities. This project was evaluated with regard to utilization and operational costs. Also, clinicians and team members involved in the teleophthalmology project provided assessments of the teleopthalmology quality, productivity, and access. Health providers in First Nations communities provided their perceptions of areas of improvement for the remote retinal screening services, areas where expansion of services could be offered, and opportunities to increase client education and health promotion. Results: All 51 First Nations communities on Vancouver Island expressed interest in receiving teleopthalmology services. During the 1-year project, teleopthalmology clinics were held in 43 of 51 communities on Vancouver Island. During these clinics, 524 clients were screened and 140 of those clients were referred to a general ophthalmologist, family doctor, retinal specialist, optometrist, or other provider. Ratings of teleopthalmology system quality, information quality, service quality, and system usage were positive. Satisfaction with the teleopthalmology project was high among clinicians involved with the project. Satisfaction was also high among health providers in First Nations communities, with clinic scheduling identified as a potential area of improvement moving forward. The average cost savings per client, taking project costs into consideration, was calculated to be CAN $28.16, which was largely due to the elimination of client travel costs. Conclusions: Teleophthalmology was a welcome addition to health services by the First Nations communities on Vancouver Island, as evidenced by the 100% rate of interest from those communities. There was no evidence of dissatisfaction by clinicians involved in the teleopthalmology project or by First Nations community health providers. The now-operational teleopthalmology program is a testament to the early success of the project.

  • Specify Data window for the FAIR Concept Tracker.

    Identification of Relationships Between Patients Through Elements in a Data Warehouse Using the Familial, Associational, and Incidental Relationship (FAIR)...

    Abstract:

    Background: Over the last several years there has been widespread development of medical data warehouses. Current data warehouses focus on individual cases, but lack the ability to identify family members that could be used for dyadic or familial research. Currently, the patient’s family history in the medical record is the only documentation we have to understand the health status and social habits of their family members. Identifying familial linkages in a phenotypic data warehouse can be valuable in cohort identification and in beginning to understand the interactions of diseases among families. Objective: The goal of the Familial, Associational, & Incidental Relationships (FAIR) initiative is to identify an index set of patients’ relationships through elements in a data warehouse. Methods: Using a test set of 500 children, we measured the sensitivity and specificity of available linkage algorithm identifiers (eg, insurance identification numbers and phone numbers) and validated this tool/algorithm through a manual chart audit. Results: Of all the children, 52.4% (262/500) were male, and the mean age of the cohort was 8 years old (SD 5). Of the children, 51.6% (258/500) were identified as white in race. The identifiers used for FAIR were available for the majority of patients: insurance number (483/500, 96.6%), phone number (500/500, 100%), and address (497/500, 99.4%). When utilizing the FAIR tool and various combinations of identifiers, sensitivity ranged from 15.5% (62/401) to 83.8% (336/401), and specificity from 72% (71/99) to 100% (99/99). The preferred method was matching patients using insurance or phone number, which had a sensitivity of 72.1% (289/401) and a specificity of 94% (93/99). Using the Informatics for Integrating Biology and the Bedside (i2b2) warehouse infrastructure, we have now developed a Web app that facilitates FAIR for any index population. Conclusions: FAIR is a valuable research and clinical resource that extends the capabilities of existing data warehouses and lays the groundwork for family-based research. FAIR will expedite studies that would otherwise require registry or manual chart abstraction data sources.

  • Decubitus pressure ulcer. Image source: https://skindisorders3.wikispaces.com/ are licensed under a Creative Commons Attribution Share-Alike 3.0 License.

    On-Admission Pressure Ulcer Prediction Using the Nursing Needs Score

    Abstract:

    Background: Pressure ulcers (PUs) are considered a serious problem in nursing care and require preventive measures. Many risk assessment methods are currently being used, but most require the collection of data not available on admission. Although nurses assess the Nursing Needs Score (NNS) on a daily basis in Japanese acute care hospitals, these data are primarily used to standardize the cost of nursing care in the public insurance system for appropriate nurse staffing, and have never been used for PU risk assessment. Objective: The objective of this study was to predict the risk of PU development using only data available on admission, including the on-admission NNS score. Methods: Logistic regression was used to generate a prediction model for the risk of developing PUs after admission. A random undersampling procedure was used to overcome the problem of imbalanced data. Results: A combination of gender, age, surgical duration, and on-admission total NNS score (NNS group B; NNS-B) was the best predictor with an average sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of 69.2% (6920/100), 82.8% (8280/100), and 84.0% (8400/100), respectively. The model with the median AUC achieved 80% (4/5) sensitivity, 81.3% (669/823) specificity, and 84.3% AUC. Conclusions: We developed a model for predicting PU development using gender, age, surgical duration, and on-admission total NNS-B score. These results can be used to improve the efficiency of nurses and reduce the number of PU cases by identifying patients who require further examination.

  • The sample distribution in the high and low voluntariness environments.

    Moderating Effects of Voluntariness on the Actual Use of Electronic Health Records for Allied Health Professionals

    Abstract:

    Background: Mandatory versus voluntary requirement has moderating effect on a person’s intention to use a new information technology. Studies have shown that the use of technology in health care settings is predicted by perceived ease of use, perceived usefulness, social influence, facilitating conditions, and attitude towards computer. These factors have different effects on mandatory versus voluntary environment of use. However, the degree and direction of moderating effect of voluntariness on these factors remain inconclusive. Objective: This study aimed to examine the moderating effect of voluntariness on the actual use of an electronic health record (EHR) designed for use by allied health professionals in Hong Kong. Specifically, this study explored and compared the moderating effects of voluntariness on factors organized into technology, implementation, and individual contexts. Methods: Physiotherapists who had taken part in the implementation of a new EHR were invited to complete a survey. The survey included questions that measured the levels of voluntariness, technology acceptance and use, and attitude towards technology. Multiple logistic regressions were conducted to identify factors associated with actual use of a compulsory module and a noncompulsory module of the EHR. Results: In total, there were 93 participants in the study. All of them had access to the noncompulsory module, the e-Progress Note, to record progress notes of their patients. Out of the 93 participants, 57 (62%) were required to use a compulsory module, the e-Registration, to register patient attendance. In the low voluntariness environment, Actual Use was associated with Effort Expectancy (mean score of users 3.51, SD 0.43; mean score of non-users 3.21, SD 0.31; P=.03). Effort Expectancy measured the perceived ease of use and was a variable in the technology context. The variables in the implementation and individual contexts did not show a difference between the two groups. In the high voluntariness environment, the mean score of Actual Use was associated with Performance Expectancy (P=.03), Organization Facilitating Condition (P=.02), and Interest in Internet and Computer (P=.052) in univariate analyses. The only variable left in the logistic regression model was Organization Facilitating Conditions (mean score of users 3.82, SD 0.35; mean score of non-users 3.40, SD 0.48; P=.03), a variable in the implementation context. The factors affecting actual use were different in mandatory and voluntary environments, indicating a moderating effect of voluntariness. Conclusions: The results of this study have provided preliminary supports of moderating effects of voluntariness on the use of EHR by allied health professionals. Different factors were identified to be associated with actual use: (1) Ease of Use in mandatory environment, and (2) Organization Facilitating Conditions in voluntary environment. More studies are needed to examine the direction of moderating effects. The findings of this study have potential practical implications. In sum, voluntariness can be a highly relevant and important moderating factor not to be ignored in the design and evaluation of EHR.

  • This is a royalty free image by Ambro (http://www.freedigitalphotos.net/images/Healthcare_g355-General_Practitioner_p38464.html).

    Veteran, Primary Care Provider, and Specialist Satisfaction With Electronic Consultation

    Abstract:

    Background: Access to specialty care is challenging for veterans in rural locations. To address this challenge, in December 2009, the Veterans Affairs (VA) Pittsburgh Healthcare System (VAPHS) implemented an electronic consultation (e-consult) program to provide primary care providers (PCPs) and patients with enhanced specialty care access. Objective: The aim of this quality improvement (QI) project evaluation was to: (1) assess satisfaction with the e-consult process, and (2) identify perceived facilitators and barriers to using the e-consult program. Methods: We conducted semistructured telephone interviews with veteran patients (N=15), Community Based Outpatient Clinic (CBOC) PCPs (N=15), and VA Pittsburgh specialty physicians (N=4) who used the e-consult program between December 2009 to August 2010. Participants answered questions regarding satisfaction in eight domains and identified factors contributing to their responses. Results: Most participants were white (patients=87%; PCPs=80%; specialists=75%) and male (patients=93%; PCPs=67%; specialists=75%). On average, patients had one e-consult (SD 0), PCPs initiated 6 e-consults (SD 6), and VAPHS specialists performed 17 e-consults (SD 11). Patients, PCPs, and specialty physicians were satisfied with e-consults median (range) of 5.0 (4-5) on 1-5 Likert-scale, 4.0 (3-5), and 3.5 (3-5) respectively. The most common reason why patients and specialists reported increased overall satisfaction with e-consults was improved communication, whereas improved timeliness of care was the most common reason for PCPs. Communication was the most reported perceived barrier and facilitator to e-consult use. Conclusions: Veterans and VA health care providers were satisfied with the e-consult process. Our findings suggest that while the reasons for satisfaction with e-consult differ somewhat for patients and physicians, e-consult may be a useful tool to improve VA health care system access for rural patients.

  • Dynamic consent interface. The origin of the image is from HW Communications and the University of Oxford.

    Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research

    Abstract:

    With one million people treated every 36 hours, routinely collected UK National Health Service (NHS) health data has huge potential for medical research. Advances in data acquisition from electronic patient records (EPRs) means such data are increasingly digital and can be anonymised for research purposes. NHS England’s care.data initiative recently sought to increase the amount and availability of such data. However, controversy and uncertainty following the care.data public awareness campaign led to a delay in rollout, indicating that the success of EPR data for medical research may be threatened by a loss of patient and public trust. The sharing of sensitive health care data can only be done through maintaining such trust in a constantly evolving ethicolegal and political landscape. We propose that a dynamic consent model, whereby patients can electronically control consent through time and receive information about the uses of their data, provides a transparent, flexible, and user-friendly means to maintain public trust. This could leverage the huge potential of the EPR for medical research and, ultimately, patient and societal benefit.

  • TOC image
http://www.istockphoto.com/photo/e-health-data-link-40258008?st=7e2178d
paid the 1 credit cost to iStock.

    Impact of Information Technology on Information Gaps in Canadian Ambulatory Care Encounters

    Abstract:

    Background: Specialist physicians require clinical information for patient visits in ambulatory encounters, some of which they may access via digital health solutions. Objective: This study explored the completeness of information for patient care and the consequences of gaps for ambulatory specialist services provided in ambulatory settings in Canada. Methods: A sample of specialist physicians practising in outpatient clinics was recruited from a health care provider research panel. The study (n=1800 patient encounters) looked at the completeness of patient information experienced by physicians who work in environments with rich health information exchange (Connected) and a comparison cohort with less information available electronically (Unconnected). Results: Unconnected physicians were significantly more likely to be missing information they needed for patient encounters (13% of encounters for Unconnected physicians vs 7% for Connected physicians). Unconnected physicians were also more likely to report that missing information had consequences (23% vs 13% of encounters). Lab results were the most common type of patient information missing for both Unconnected and Connected specialists (25% for Unconnected physicians vs 11% Connected physicians). Conclusions: The results from this study indicate that Canadian physicians commonly experience information gaps in ambulatory encounters, and that many of these gaps are of consequence to themselves, their patients, and the healthcare system. Wasting physician and patient time, as well as being forced to proceed with incomplete information, were the most common consequences of information gaps reported.

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  • A Practical Guideline to Safeguard Custom Applications in Hospital Setting: Maximizing the Use of and Minimizing the Security Risk of BYOD

    Date Submitted: Mar 12, 2015

    Open Peer Review Period: Mar 13, 2015 - May 8, 2015

    Background: Allowing healthcare professionals to use personal mobile devices at work, known as bring-your-own-device (BYOD), has potential to support both hospital and the professionals to deliver eff...

    Background: Allowing healthcare professionals to use personal mobile devices at work, known as bring-your-own-device (BYOD), has potential to support both hospital and the professionals to deliver effective and efficient care. Unfortunately, the guidelines are lacking on how hospitals should best integrate personal devices into hospital information systems, which include electronic medical records and custom applications developed by hospitals, while maintaining their existing privacy and security policies. The are also pertain deficiencies in BYOD in the area of guiding the development of the custom applications for patient care. Objective: This paper offers a qualitative analysis why and how BYOD can be implemented in hospital settings as well as provides an example of how Boston Children’s Hospital (BCH) has approached BYOD to develop custom applications to leverage the use of personal mobile devices for the clinicians in the hospital. Methods: Through a literature review, discussion with external security experts, and interviews with the leaders within the Information Systems Department at the Boston Children’s Hospital, we developed hospital appropriate BYOD guidelines for custom application development. After establishing the guidelines, the research team developed a mobile application, called TaskList, which could be an appropriate test case to determine security and privacy requirements for an application that will be deployed in a BYOD environment. Results: Fifteen practical recommendations were identified named BCH BYOD Guideline to Safeguard Custom Applications in Hospital Settings. The recommendations were grouped into 1) Authentication and authorization, 2) Data Management, 3) Safeguarding Application Environment, and 4) Remote Enforcement. Following the guidelines, a mobile, collaborative, real time TaskList application was developed on the iOS platform. The application listed shared tasks for patient and allowed a team of medical residents to check and update tasks through the course of the day and automatically provide real time update to the team members. The application was piloted with an inpatient pediatric ward team. Conclusions: The guideline was very useful for developers and managers when designing and implementing TaskList application that was developed and deployed at the Boston Children’s Hospital. The guideline could also be useful for similar requirements when an application need to be developed and deployed in BYOD healthcare settings where HIPAA requirements must be complied.

  • Mobile health insurance system: sustainable business model for Primary Health Centers in Abuja-Nigeria

    Date Submitted: Feb 12, 2015

    Open Peer Review Period: Feb 12, 2015 - Apr 9, 2015

    Background: Over the last few decades, maternal health indicators like other health indices have remained discouraging in Nigeria. Although Nigeria contributes only 2% of the world’s population, it...

    Background: Over the last few decades, maternal health indicators like other health indices have remained discouraging in Nigeria. Although Nigeria contributes only 2% of the world’s population, it accounts for 10% of the global maternal death burden. Health care at primary health centers, the lowest level of public health care is far below optimal in quality and grossly inadequate in coverage. Private primary health facilities attempt to fill this gap but at additional costs to the client. Over 95% Nigerians still pay out of pocket for health services. Meanwhile, the use of mobile phones and related services has risen geometrically in recent years in Nigeria and their adoption into health care is an enterprise worth exploring. Objective: The purpose of this study was to investigate the sustainability and reliability of mobile technology supported community-based health insurance scheme. Methods: This analytic cross-sectional survey used a hybrid of mixed methods stakeholder interviews coupled with prototype throw-away software development to gather data from 50 public primary health facilities and 50 private primary care centers in Abuja, Nigeria. Data gathered specifically focused on the reliability and sustainability of a mobile health insurance system. Clients and health workers were interviewed using structured questionnaires on services provided and cost of those services. Trained interviewers conducted the structured interviews and one client and one health worker were interviewed per health facility. Clinic expenditure was analyzed to include: personnel, fixed equipment, medical consumables, and operations costs. Results: All the 200 respondents indicated willingness to use the proposed system. Differences in the cost of services between public and private facilities were analyzed using student t-distribution at 95% confidence interval of 5%. Results showed cost of services at private health facilities to be significantly higher than those at public primary health facilities. Key informant interviews with 2 health management organizations and a telecoms operator revealed high investment interests. Cost effectiveness analysis of income versus expenditure for the major service areas - antenatal care, routine immunization, and birth attendance for one year showed that primary health facilities would still be profitable if mHealth-supported community based health insurance schemes were adopted. Conclusions: This project demonstrated a business case for the implementation of enrolment, treatment verification and reimbursement using mobile technology for community health in Abuja Nigeria. Available data shows that the introduction of an electronic job aid made work easier. There will be greater risk pulling if the numbers increase to the minimum 1000 clients recommended by National Health Insurance Scheme. However, since drug and medical consumables costing data were not collected during this study, it is difficult to categorically say that the 5-year projection showed a sustainable business model.