mUzima Mobile Electronic Health Record (EHR) System: Development and Implementation at Scale.

BACKGROUND: The predominant implementation paradigm of electronic health record (EHR) systems in low- and middle-income countries (LMICs) relies on standalone system installations at facilities. This implementation approach exacerbates the digital divide, with facilities in areas with inadequate electrical and network infrastructure often left behind. Mobile health (mHealth) technologies have been implemented to extend the reach of digital health, but these systems largely add to the problem of siloed patient data, with few seamlessly interoperating with the EHR systems that are now scaled nationally in many LMICs. Robust mHealth applications that effectively extend EHR systems are needed to improve access, improve quality of care, and ameliorate the digital divide. OBJECTIVE: We report on the development and scaled implementation of mUzima, an mHealth extension of the most broadly deployed EHR system in LMICs (OpenMRS). METHODS: The "Guidelines for reporting of health interventions using mobile phones: mobile (mHealth) evidence reporting assessment (mERA)" checklist was employed to report on the mUzima application. The World Health Organization (WHO) Principles for Digital Development framework was used as a secondary reference framework. Details of mUzima's architecture, core features, functionalities, and its implementation status are provided to highlight elements that can be adapted in other systems. RESULTS: mUzima is an open-source, highly configurable Android application with robust features including offline management, deduplication, relationship management, security, cohort management, and error resolution, among many others. mUzima allows providers with lower-end Android smartphones (version 4.4 and above) who work remotely to access historical patient data, collect new data, view media, leverage decision support, conduct store-and-forward teleconsultation, and geolocate clients. The application is supported by an active community of developers and users, with feature priorities vetted by the community. mUzima has been implemented nationally in Kenya, is widely used in Rwanda, and is gaining scale in Uganda and Mozambique. It is disease-agnostic, with current use cases in HIV, cancer, chronic disease, and COVID-19 management, among other conditions. mUzima meets all WHO's Principles of Digital Development, and its scaled implementation success has led to its recognition as a digital global public good and its listing in the WHO Digital Health Atlas. CONCLUSIONS: Greater emphasis should be placed on mHealth applications that robustly extend reach of EHR systems within resource-limited settings, as opposed to siloed mHealth applications. This is particularly important given that health information exchange infrastructure is yet to mature in many LMICs. The mUzima application demonstrates how this can be done at scale, as evidenced by its adoption across multiple countries and for numerous care domains.

Implementation of Fingerprint Technology for Unique Patient Matching and Identification at an HIV Care and Treatment Facility in Western Kenya: Cross-sectional Study.

BACKGROUND: Unique patient identification remains a challenge in many health care settings in low- and middle-income countries (LMICs). Without national-level unique identifiers for whole populations, countries rely on demographic-based approaches that have proven suboptimal. Affordable biometrics-based approaches, implemented with consideration of contextual ethical, legal, and social implications, have the potential to address this challenge and improve patient safety and reporting accuracy. However, limited studies exist to evaluate the actual performance of biometric approaches and perceptions of these systems in LMICs. OBJECTIVE: The aim of this study is to evaluate the performance and acceptability of fingerprint technology for unique patient matching and identification in the LMIC setting of Kenya. METHODS: In this cross-sectional study conducted at an HIV care and treatment facility in Western Kenya, an open source fingerprint application was integrated within an implementation of the Open Medical Record System, an open source electronic medical record system (EMRS) that is nationally endorsed and deployed for HIV care in Kenya and in more than 40 other countries; hence, it has potential to translate the findings across multiple countries. Participants aged >18 years were conveniently sampled and enrolled into the study. Participants' left thumbprints were captured and later used to retrieve and match records. The technology's performance was evaluated using standard measures: sensitivity, false acceptance rate, false rejection rate, and failure to enroll rate. The Wald test was used to compare the accuracy of the technology with the probabilistic patient-matching technique of the EMRS. Time to retrieval and matching of records were compared using the independent samples 2-tailed t test. A survey was administered to evaluate patient acceptance and satisfaction with use of the technology. RESULTS: In all, 300 participants were enrolled; their mean age was 36.3 (SD 12.2) years, and 58% (174/300) were women. The relevant values for the technology's performance were sensitivity 89.3%, false acceptance rate 0%, false rejection rate 11%, and failure to enroll rate 2.3%. The technology's mean record retrieval speed was 3.2 (SD 1.1) seconds versus 9.5 (SD 1.9) seconds with demographic-based record retrieval in the EMRS (P<.001). The survey results revealed that 96.3% (289/300) of the participants were comfortable with the technology and 90.3% (271/300) were willing to use it. Participants who had previously used fingerprint biometric systems for identification were estimated to have more than thrice increased odds of accepting the technology (odds ratio 3.57, 95% CI 1.0-11.92). CONCLUSIONS: Fingerprint technology performed very well in identifying adult patients in an LMIC setting. Patients reported a high level of satisfaction and acceptance. Serious considerations need to be given to the use of fingerprint technology for patient identification in LMICs, but this has to be done with strong consideration of ethical, legal, and social implications as well as security issues.

Comparative analysis of competency coverage within accredited master's in health informatics programs in the East African region.

OBJECTIVE: As master of science in health informatics (MSc HI) programs emerge in developing countries, quality assurance of these programs is essential. This article describes a comprehensive comparative analysis of competencies covered by accredited MSc HI programs in the East African common labor and educational zone. MATERIALS AND METHODS: Two reviewers independently reviewed curricula from 7 of 8 accredited MSc HI university programs. The reviewers extracted covered competencies, coding these based on a template that contained 73 competencies derived from competencies recommended by the International Medical Informatics Association, plus additional unique competencies contained within the MSc HI programs. Descriptive statistics were used to summarize the structure and completion requirements of each MSc HI program. Jaccard similarity coefficient was used to compare similarities in competency coverage between universities. RESULTS: The total number of courses within the MSc HI degree programs ranged from 8 to 22, with 35 to 180 credit hours. Cohen's kappa for coding competencies was 0.738. The difference in competency coverage was statistically significant across the 7 institutions (P = .012), with covered competencies across institutions ranging from 32 (43.8%) to 49 (67.1%) of 73. Only 4 (19%) of 21 university pairs met a cutoff of over 70% similarity in shared competencies. DISCUSSION: Significant variations observed in competency coverage within MSc HI degree programs could limit mobility of student, faculty, and labor. CONCLUSIONS: Comparative analysis of MSc HI degree programs across 7 universities in East Africa revealed significant differences in the competencies that were covered.

Coverage of IMIA-recommended Competencies by Masters in Health Informatics Degree Programs in East Africa.

OBJECTIVE: The International Medical Informatics Association (IMIA) has provided recommendations on Education in Biomedical and Health Informatics (BMHI) as guidance on competencies relevant to education of BMHI specialists. However, it remains unclear how well these competencies have been adopted to guide emerging degree programs in low- and middle-income countries (LMICs). We evaluated comprehensiveness of IMIA-recommended competency coverage by Masters in Health Informatics (MSc HI) programs in East Africa. MATERIALS AND METHODS: Two investigators independently reviewed curricula for seven accredited MSc HI university programs in the East Africa region to extract covered competencies using an instrument based on the IMIA education recommendations. Descriptive statistics were used to determine competency coverage by institution and across institutions and by IMIA-defined competency domains. Duplication of competency coverage in courses within each curriculum was also evaluated. Multivariable logistic regression was used to test whether coverage of IMIA-recommended competencies differed between institutions. RESULTS: Cohen's Kappa for coding competencies within courses was 0.738 (95% CI, 0.713-0.764). Coverage of the 40 recommended required IMIA competencies by institutional curricula ranged from 25 (62.5%) to 39 (97.5%) (p < 0.0001), with only 18 (45%) of these competencies covered by all seven institutions. No significant variations in competency coverage were observed between the domains of information sciences (83.7%), health sciences (71.4%), and core BMHI competencies (83.5%) (p = 0.13). On average, each competency was covered by 3.06 courses in each curriculum (range 0 - 14). Curricula also contained 25 additional competencies not part of the IMIA recommendations, 15 of which were found only within the curriculum of a single institution. DISCUSSION: There is significant variability in coverage of IMIA-recommended competencies across MSc HI curricula evaluated, with observed duplication of competency coverage within each curriculum. The additional competencies uncovered that were not part of the IMIA-recommendations were not universally shared across institutions. CONCLUSION: The IMIA education recommendations provide a relevant, comprehensive reference guide for developing and improving health informatics degree programs within LMIC settings. Variability in competency coverage needs to be addressed for institutions within similar educational and labor regions.

Assessing the impact of a primary care electronic medical record system in three Kenyan rural health centers.

OBJECTIVE: Efficient, effective health care requires rapid availability of patient information. We designed, implemented, and assessed the impact of a primary care electronic medical record (EMR) in three rural Kenyan health centers. METHOD: Local clinicians identified data required for primary care and public health reporting. We designed paper encounter forms to capture these data in adult medicine, pediatric, and antenatal clinics. Encounter form data were hand-entered into a new primary care module in an existing EMR serving onsite clinics serving patients infected with the human immunodeficiency virus (HIV). Before subsequent visits, Summary Reports were printed containing selected patient data with reminders for needed HIV care. We assessed effects on patient flow and provider work with time-motion studies before implementation and two years later, and we surveyed providers' satisfaction with the EMR. RESULTS: Between September 2008 and December 2011, 72 635 primary care patients were registered and 114 480 encounter forms were completed. During 2011, 32 193 unique patients visited primary care clinics, and encounter forms were completed for all visits. Of 1031 (3.2%) who were HIV-infected, 85% received HIV care. Patient clinic time increased from 37 to 81 min/visit after EMR implementation in one health center and 56 to 106 min/visit in the other. However, outpatient visits to both health centers increased by 85%. Three-quarters of increased time was spent waiting. Despite nearly doubling visits, there was no change in clinical officers' work patterns, but the nurses' and the clerks' patient care time decreased after EMR implementation. Providers were generally satisfied with the EMR but desired additional training. CONCLUSIONS: We successfully implemented a primary care EMR in three rural Kenyan health centers. Patient waiting time was dramatically lengthened while the nurses' and the clerks' patient care time decreased. Long-term use of EMRs in such settings will require changes in culture and workflow.

A clinical decision support system for integrating tuberculosis and HIV care in Kenya: a human-centered design approach.

With the aim of integrating HIV and tuberculosis care in rural Kenya, a team of researchers, clinicians, and technologists used the human-centered design approach to facilitate design, development, and deployment processes of new patient-specific TB clinical decision support system for medical providers. In Kenya, approximately 1.6 million people are living with HIV and have a 20-times higher risk of dying of tuberculosis. Although tuberculosis prevention and treatment medication is widely available, proven to save lives, and prioritized by the World Health Organization, ensuring that it reaches the most vulnerable communities remains challenging. Human-centered design, used in the fields of industrial design and information technology for decades, is an approach to improving the effectiveness and impact of innovations that has been scarcely used in the health field. Using this approach, our team followed a 3-step process, involving mixed methods assessment to (1) understand the situation through the collection and analysis of site observation sessions and key informant interviews; (2) develop a new clinical decision support system through iterative prototyping, end-user engagement, and usability testing; and, (3) implement and evaluate the system across 24 clinics in rural West Kenya. Through the application of this approach, we found that human-centered design facilitated the process of digital innovation in a complex and resource-constrained context.

Experience implementing electronic health records in three East African countries.

INTRODUCTION: Efficient use of health care resources in low-income countries by providers and local and national managers requires timely access to patient data. OBJECTIVE: To implement electronic health records (EHRs) in HIV clinics in Kenya, Tanzania, and Uganda. RESULTS: We initially developed and implemented an EHR in Kenya through a mature academic partnership. The EHR was then implemented in six HIV clinics in Tanzania and Uganda in collaboration with their National AIDS Control Programmes. All implementations were successful, but the system's use and sustainability varied depending on who controlled clinic funding. CONCLUSIONS: Successful EHR use and sustainability were enhanced by local control of funds, academic partnerships (mainly by leveraging research funds), and in-country technology support.

A single health status question had important prognostic value among outpatients with chronic heart failure.

OBJECTIVE: Health status is an important marker of the impact of disease on function among patients with chronic heart failure (CHF). However, the prognostic value of CHF-specific health status on long-term mortality has not been adequately evaluated. Our objective was to assess CHF-specific health status and 5-year mortality among outpatients with CHF. STUDY DESIGN AND SETTING: We analyzed data from 494 Veterans Affairs outpatients with diagnoses of CHF and objective evidence of left ventricular dysfunction who enrolled in a quality improvement intervention. We extracted information about comorbid diagnoses, severity of illness (Charlson index), health care utilization, drug therapy, laboratory, and vital sign data along with generic and CHF-specific health status. We then identified multivariate correlates of subsequent mortality at 5 years. RESULTS: Five-year mortality was 44%. Age (chi2=26.1, hazard ratio [HR]=1.63, confidence interval [CI]: 1.35, 1.97; P<0.0001) and Charlson index (chi2=12.9, HR=1.39, CI: 1.16, 1.67; P=0.0003) were significantly associated with 5-year mortality. Controlling for clinical, lab, medication, and administrative data, a single-item assessing change in CHF-specific health status was independently associated with 5-year mortality (chi2=11.4, HR=0.87, CI: 0.80, 0.94, P=0.0007). CONCLUSIONS: Given the strength of the association with mortality, health care providers should routinely assess this single-item change in health status among outpatients with CHF to identify higher risk patients and guide therapy.