JMIR Medical Informatics

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

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

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.

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:

  • 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.

  • Metadata Correction: Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

    Abstract:

    See Manuscript File

  • 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.

  • License to use purchased from http://www.istockphoto.com/.

    Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    Abstract:

    Background: Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective: The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods: This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results: A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the decision maker(s). For articles reviewed, there were no studies referring to the active involvement of the patient in the decision-making process or to patient self-management. None of the articles reviewed adopted mobile technologies. There were no rigorous evaluations of usability or effectiveness of the CDS systems reported. Conclusions: This review shows that multimorbidity is underinvestigated in the informatics of supporting clinical decisions. CDS interventions that systematize clinical practice guidelines without considering the interactions of different conditions and care processes may lead to unhelpful or harmful clinical actions. To improve patient safety in multimorbidity, there is a need for more evidence about how both conditions and care processes interact. The data needed to build this evidence base exist in many electronic health record systems and are underused.

  • E-prescribing. Image Source: Jupiterimages/Gettyimages http://www.gettyimages.com/detail/photo/pharmacist-with-pill-bottles-at-computer-royalty-free-image/86530681.

    Impact of Early Electronic Prescribing on Pharmacists’ Clarification Calls in Four Community Pharmacies Located in St John’s, Newfoundland

    Abstract:

    Background: Electronic prescribing (e-prescribing) can potentially help prevent medication errors. As the use of e-prescribing increases across Canada, understanding the benefits and gaps of early e-prescribing can help inform deployment of future e-prescribing systems. Objective: The purpose of this exploratory study was to determine the prevalence of, reasons for, and average time taken for pharmacist clarification calls to prescribers for electronic medical record (EMR)-generated and handwritten prescriptions. Methods: Four community pharmacies in St John’s, Newfoundland, Canada prospectively collected information on clarification calls to prescribers for new prescriptions over a period of 17 to 19 weeks. Four semistructured interviews were conducted following the data collection period to gain further insight. Results: An estimated 1.33% of handwritten prescriptions required clarification compared with 0.66% of EMR-generated prescriptions. Overall, 1.11% of prescriptions required clarification with the prescriber. While illegibility was eliminated with EMR-generated prescriptions, clarification was still required for missing information (24%) and appropriateness (51%). Key themes, including errors unique to EMR-generated prescriptions, emerged from the qualitative interviews. Conclusions: Advanced e-prescribing functionality will enable secure transmission of prescriptions from prescribers to a patient’s pharmacy of choice through a provincial electronic Drug Information System (DIS)/Pharmacy Network, which will lessen the need for clarification calls, especially in the domains of missing information and appropriateness of the prescription. This exploratory study provides valuable insight into the benefits and gaps of early e-prescribing. Advanced e-prescribing systems will provide an opportunity for further realization of quality and safety benefits related to medication prescribing.

  • URL: http://pixabay.com 
License: Creative Commons Deed CC0 - http://pixabay.com/en/service/terms/#download_terms.

    CohortExplorer: A Generic Application Programming Interface for Entity Attribute Value Database Schemas

    Abstract:

    Background: Most electronic data capture (EDC) and electronic data management (EDM) systems developed to collect and store clinical data from participants recruited into studies are based on generic entity-attribute-value (EAV) database schemas which enable rapid and flexible deployment in a range of study designs. The drawback to such schemas is that they are cumbersome to query with structured query language (SQL). The problem increases when researchers involved in multiple studies use multiple electronic data capture and management systems each with variation on the EAV schema. Objective: The aim of this study is to develop a generic application which allows easy and rapid exploration of data and metadata stored under EAV schemas that are organized into a survey format (questionnaires/events, questions, values), in other words, the Clinical Data Interchange Standards Consortium (CDISC) Observational Data Model (ODM). Methods: CohortExplorer is written in Perl programming language and uses the concept of SQL abstract which allows the SQL query to be treated like a hash (key-value pairs). Results: We have developed a tool, CohortExplorer, which once configured for a EAV system will "plug-n-play" with EAV schemas, enabling the easy construction of complex queries through an abstracted interface. To demonstrate the utility of the CohortExplorer system, we show how it can be used with the popular EAV based frameworks; Opal (OBiBa) and REDCap. Conclusions: The application is available under a GPL-3+ license at the CPAN website. Currently the application only provides datasource application programming interfaces (APIs) for Opal and REDCap. In the future the application will be available with datasource APIs for all major electronic data capture and management systems such as OpenClinica and LabKey. At present the application is only compatible with EAV systems where the metadata is organized into surveys, questionnaires and events. Further work is needed to make the application compatible with EAV schemas where the metadata is organized into hierarchies such as Informatics for Integrating Biology & the Bedside (i2b2). A video tutorial demonstrating the application setup, datasource configuration, and search features is available on YouTube. The application source code is available at the GitHub website and the users are encouraged to suggest new features and contribute to the development of APIs for new EAV systems.

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Latest Submissions Open for Peer-Review:

View All Open Peer Review Articles
  • 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.