Patient-Specific Mobile Phone-Generated Reminders and Quality of Hypertension Care in Western Kenya.

To evaluate the impact of clinician-targeted mHealth-generated care suggestions on compliance with hypertension care guidelines in a resource-limited setting. This study was conducted in 10 rural health clinics in Western Kenya that offered hypertension care through nurses and clinical officers. Sites were grouped into intervention and control groups. Intervention group clinicians had patient-specific care suggestions triggered and displayed on a mobile application, mUzima, for their action. Care suggestions were also triggered in the mHealth application for control arm clinicians but were not displayed. Differences in compliance with hypertension care guidelines were evaluated. The study involved 378 patients with hypertension who had care suggestions generated during visits (217 in intervention group and 161 in control group). There was a higher proportion of adherence to hypertension care guidelines in the intervention group compared to the control group (91.1% vs. 85.7%, p=0.014). The random effects model showed significant variability in compliance rates among study clinicians (variance of 0.44, 95% CI: 0.12 -1.62). When displayed care suggestions were rejected by intervention providers, the most common reason given was 'Previously ordered' (58.8%). Clinicians felt that care suggestions improved awareness of hypertension care guidelines. The successful scaled implementation of mUzima with patient specific care suggestions led to higher adherence to hypertension care guidelines and improved quality of hypertension care. Tailormade m-Health applications in resource constrained settings for hypertension care and other chronic non-communicable diseases has the potential to lead to better adherence to care guidelines and quality of care.

PEERNaija-a mobile health platform incentivizing medication adherence among youth living with HIV in Nigeria: study protocol for a randomized controlled trial.

BACKGROUND: Poor medication adherence is a major barrier to HIV control among youth living with HIV (Y-PLWH). The PEERNaija application (app) is an adapted smartphone app grounded in social cognitive and contigency management theories and designed to harness peer-based social incentives and conditional financial incentives to promote medication adherence. The app delivers a multifaceted medication adherence intervention including (1) peer-based social incentives, (2) financial incentives, (3) virtual peer social support, and (4) early clinic-based outreach for non-adherent Y-PLWH. A pilot trial of the app will be conducted in Nigeria, Africa's most populous country with the 4th largest HIV epidemic, and home to 10% of the world's four million Y-PLWH. METHODS: In this randomized controlled trial, we will compare implementation outcomes (feasibility, acceptability, appropriateness measured via validated scales, enrollment and application installation rates, feedback surveys and focus group discussions with participants, and back-end application data), and preliminary efficacy (in improving medication adherence and viral suppression) of the PEERNaija app at 6 months. Participants in Arm 1 (PEERNaija) will receive daily medication reminders, peer-based social incentives, and virtual peer social support. Participants in Arm 2 (PEERNaija +) will additionally receive a conditional financial incentive based on their adherence performance. Eligibility for Y-PLWH includes (1) being aged 14-29 years, (2) being on ART, (3) owning a smartphone, (4) being willing to download an app, and (5) being able to read simple text in English. DISCUSSION: This study will serve as the basis for a larger intervention trial evaluating the PEERNaija app (and the integration of mHealth, incentive, and peer-support-based strategies) to improve HIV outcomes in a critically important region of the world for Y-PLWH. TRIAL REGISTRATION: ClinicalTrials.gov. NCT04930198. First submitted date: May 25, 2021. Study start: August 1, 2021, https://clinicaltrials.gov/ . PROTOCOL VERSION: January 21, 2022.

Differences in Health Professionals' Engagement With Electronic Health Records Based on Inpatient Race and Ethnicity.

Importance: US health professionals devote a large amount of effort to engaging with patients' electronic health records (EHRs) to deliver care. It is unknown whether patients with different racial and ethnic backgrounds receive equal EHR engagement. Objective: To investigate whether there are differences in the level of health professionals' EHR engagement for hospitalized patients according to race or ethnicity during inpatient care. Design, Setting, and Participants: This cross-sectional study analyzed EHR access log data from 2 major medical institutions, Vanderbilt University Medical Center (VUMC) and Northwestern Medicine (NW Medicine), over a 3-year period from January 1, 2018, to December 31, 2020. The study included all adult patients (aged ≥18 years) who were discharged alive after hospitalization for at least 24 hours. The data were analyzed between August 15, 2022, and March 15, 2023. Exposures: The actions of health professionals in each patient's EHR were based on EHR access log data. Covariates included patients' demographic information, socioeconomic characteristics, and comorbidities. Main Outcomes and Measures: The primary outcome was the quantity of EHR engagement, as defined by the average number of EHR actions performed by health professionals within a patient's EHR per hour during the patient's hospital stay. Proportional odds logistic regression was applied based on outcome quartiles. Results: A total of 243 416 adult patients were included from VUMC (mean [SD] age, 51.7 [19.2] years; 54.9% female and 45.1% male; 14.8% Black, 4.9% Hispanic, 77.7% White, and 2.6% other races and ethnicities) and NW Medicine (mean [SD] age, 52.8 [20.6] years; 65.2% female and 34.8% male; 11.7% Black, 12.1% Hispanic, 69.2% White, and 7.0% other races and ethnicities). When combining Black, Hispanic, or other race and ethnicity patients into 1 group, these patients were significantly less likely to receive a higher amount of EHR engagement compared with White patients (adjusted odds ratios, 0.86 [95% CI, 0.83-0.88; P < .001] for VUMC and 0.90 [95% CI, 0.88-0.92; P < .001] for NW Medicine). However, a reduction in this difference was observed from 2018 to 2020. Conclusions and Relevance: In this cross-sectional study of inpatient EHR engagement, the findings highlight differences in how health professionals distribute their efforts to patients' EHRs, as well as a method to measure these differences. Further investigations are needed to determine whether and how EHR engagement differences are correlated with health care outcomes.

Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics: Second Revision.

BACKGROUND: The purpose of educational recommendations is to assist in establishing courses and programs in a discipline, to further develop existing educational activities in the various nations, and to support international initiatives for collaboration and sharing of courseware. The International Medical Informatics Association (IMIA) has published two versions of its international recommendations in biomedical and health informatics (BMHI) education, initially in 2000 and revised in 2010. Given the recent changes to the science, technology, the needs of the healthcare systems, and the workforce of BMHI, a revision of the recommendations is necessary. OBJECTIVE: The aim of these updated recommendations is to support educators in developing BMHI curricula at different education levels, to identify essential skills and competencies for certification of healthcare professionals and those working in the field of BMHI, to provide a tool for evaluators of academic BMHI programs to compare and accredit the quality of delivered programs, and to motivate universities, organizations, and health authorities to recognize the need for establishing and further developing BMHI educational programs. METHOD: An IMIA taskforce, established in 2017, updated the recommendations. The taskforce included representatives from all IMIA regions, with several having been involved in the development of the previous version. Workshops were held at different IMIA conferences, and an international Delphi study was performed to collect expert input on new and revised competencies. RESULTS: Recommendations are provided for courses/course tracks in BMHI as part of educational programs in biomedical and health sciences, health information management, and informatics/computer science, as well as for dedicated programs in BMHI (leading to bachelor's, master's, or doctoral degree). The educational needs are described for the roles of BMHI user, BMHI generalist, and BMHI specialist across six domain areas - BMHI core principles; health sciences and services; computer, data and information sciences; social and behavioral sciences; management science; and BMHI specialization. Furthermore, recommendations are provided for dedicated educational programs in BMHI at the level of bachelor's, master's, and doctoral degrees. These are the mainstream academic programs in BMHI. In addition, recommendations for continuing education, certification, and accreditation procedures are provided. CONCLUSION: The IMIA recommendations reflect societal changes related to globalization, digitalization, and digital transformation in general and in healthcare specifically, and center on educational needs for the healthcare workforce, computer scientists, and decision makers to acquire BMHI knowledge and skills at various levels. To support education in BMHI, IMIA offers accreditation of quality BMHI education programs. It supports information exchange on programs and courses in BMHI through its Working Group on Health and Medical Informatics Education.

Data Cleaning Process for mHealth Log Data to Inform Health Worker Performance.

Log data, captured during use of mobile health (mHealth) applications by health providers, can play an important role in informing nature of user engagement with the application. The log data can also be employed in understanding health provider work patterns and performance. However, given that these logs are raw data, they require robust cleaning and curation if accurate conclusions are to be derived from analyzing them. This paper describes a systematic data cleaning process for mHealth-derived logs based on Broeck's framework, which involves iterative screening, diagnosis, and treatment of the log data. For this study, log data from the demonstrative mUzima mHealth application are used. The employed data cleaning process uncovered data inconsistencies, duplicate logs, missing data within logs that required imputation, among other issues. After the data cleaning process, only 39,229 log records out of the initial 91,432 usage logs (42.9%) could be included in the final dataset suitable for analyses of health provider work patterns. This work highlights the significance of having a systematic data cleaning approach for log data to derive useful information on health provider work patterns and performance.

Developing Harmonized Benchmarks for the Master of Science in Health Informatics for the East African Region.

Higher education institutions in low- and middle-income countries are increasingly offering post-graduate degree programmes in health informatics. An analysis of accredited Master of Science in Health Informatics (MSc HI) programmes in the East African Community (EAC), a common higher education and labor zone, revealed wide variability in covered courses and competencies. In this paper, we describe the process undertaken to harmonize and establish common benchmarks for MSc HI for the EAC, in collaboration with the Inter-University Council for East Africa (IUCEA). After a multi-step process involving desk-reviews, benchmarking workshop with stakeholders, and quality assurance of benchmarks by IUCEA, the MSc HI benchmarks were finalized. These benchmarks outline the MSc HI degree programme goal, objectives, admission criteria, graduation requirements, and expected Learning Outcomes (ELOs). The ELOs are further translated into courses covering all identified skills and competencies. The benchmarks should facilitate mobility of students, faculty and labor, and improve program quality.

Leveraging mHealth usage logs to inform health worker performance in a Resource-Limited setting: Case example of mUzima use for a chronic disease program in Western Kenya.

BACKGROUND: Health systems in low- and middle-income countries (LMICs) can be strengthened when quality information on health worker performance is readily available. With increasing adoption of mobile health (mHealth) technologies in LMICs, there is an opportunity to improve work-performance and supportive supervision of workers. The objective of this study was to evaluate usefulness of mHealth usage logs (paradata) to inform health worker performance. METHODOLOGY: This study was conducted at a chronic disease program in Kenya. It involved 23 health providers serving 89 facilities and 24 community-based groups. Study participants, who already used an mHealth application (mUzima) during clinical care, were consented and equipped with an enhanced version of the application that captured usage logs. Three months of log data were used to determine work performance metrics, including: (a) number of patients seen; (b) days worked; (c) work hours; and (d) length of patient encounters. PRINCIPAL FINDINGS: Pearson correlation coefficient for days worked per participant as derived from logs as well as from records in the Electronic Medical Record system showed a strong positive correlation between the two data sources (r(11) = .92, p < .0005), indicating mUzima logs could be relied upon for analyses. Over the study period, only 13 (56.3%) participants used mUzima in 2,497 clinical encounters. 563 (22.5%) of encounters were entered outside of regular work hours, with five health providers working on weekends. On average, 14.5 (range 1-53) patients were seen per day by providers. CONCLUSIONS / SIGNIFICANCE: mHealth-derived usage logs can reliably inform work patterns and augment supervision mechanisms made particularly challenging during the COVID-19 pandemic. Derived metrics highlight variabilities in work performance between providers. Log data also highlight areas of suboptimal use, of the application, such as for retrospective data entry for an application meant for use during the patient encounter to best leverage built-in clinical decision support functionality.

Users' perception on factors contributing to electronic medical records systems use: a focus group discussion study in healthcare facilities setting in Kenya.

BACKGROUND: Electronic medical records systems (EMRs) adoption in healthcare to facilitate work processes have become common in many countries. Although EMRs are associated with quality patient care, patient safety, and cost reduction, their adoption rates are comparatively low. Understanding factors associated with the use of the implemented EMRs are critical for advancing successful implementations and scale-up sustainable initiatives. The aim of this study was to explore end users' perceptions and experiences on factors facilitating and hindering EMRs use in healthcare facilities in Kenya, a low- and middle-income country. METHODS: Two focus group discussions were conducted with EMRs users (n = 20) each representing a healthcare facility determined by the performance of the EMRs implementation. Content analysis was performed on the transcribed data and relevant themes derived. RESULTS: Six thematic categories for both facilitators and barriers emerged, and these related to (1) system functionalities; (2) training; (3) technical support; (4) human factors; (5) infrastructure, and (6) EMRs operation mode. The identified facilitators included: easiness of use and learning of the system complemented by EMRs upgrades, efficiency of EMRs in patient data management, responsive information technology (IT) and collegial support, and user training. The identified barriers included: frequent power blackouts, inadequate computers, retrospective data entry EMRs operation mode, lack of continuous training on system upgrades, and delayed IT support. CONCLUSIONS: Users generally believed that the EMRs improved the work process, with multiple factors identified as facilitators and barriers to their use. Most users perceived system functionalities and training as motivators to EMRs use, while infrastructural issues posed as the greatest barrier. No specific EMRs use facilitators and/or barriers could be attributed to facility performance levels. Continuous evaluations are necessary to assess improvements of the identified factors as well as determine emerging issues.

A multivariate statistical evaluation of actual use of electronic health record systems implementations in Kenya.

BACKGROUND: Health facilities in developing countries are increasingly adopting Electronic Health Records systems (EHRs) to support healthcare processes. However, only limited studies are available that assess the actual use of the EHRs once adopted in these settings. We assessed the state of the 376 KenyaEMR system (national EHRs) implementations in healthcare facilities offering HIV services in Kenya. METHODS: The study focused on seven EHRs use indicators. Six of the seven indicators were programmed and packaged into a query script for execution within each KenyaEMR system (KeEMRs) implementation to collect monthly server-log data for each indicator for the period 2012-2019. The indicators included: Staff system use, observations (clinical data volume), data exchange, standardized terminologies, patient identification, and automatic reports. The seventh indicator (EHR variable Completeness) was derived from routine data quality report within the EHRs. Data were analysed using descriptive statistics, and multiple linear regression analysis was used to examine how individual facility characteristics affected the use of the system. RESULTS: 213 facilities spanning 19 counties participated in the study. The mean number of authorized users who actively used the KeEMRs was 18.1% (SD = 13.1%, p<0.001) across the facilities. On average, the volume of clinical data (observations) captured in the EHRs was 3363 (SD = 4259). Only a few facilities(14.1%) had health data exchange capability. 97.6% of EHRs concept dictionary terms mapped to standardized terminologies such as CIEL. Within the facility EHRs, only 50.5% (SD = 35.4%, p< 0.001) of patients had the nationally-endorsed patient identifier number recorded. Multiple regression analysis indicated the need for improvement on the mode of EHRs use of implementation. CONCLUSION: The standard EHRs use indicators can effectively measure EHRs use and consequently determine success of the EHRs implementations. The results suggest that most of the EHRs use areas assessed need improvement, especially in relation to active usage of the system and data exchange readiness.

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.

Acceptability, Barriers and Facilitators of Mobile Text Message Reminder System Implementation in Improving Child Vaccination: A Qualitative Study in Northwest Ethiopia.

BACKGROUND: Mobile phone text message-based mHealth interventions have shown promise in improving health service delivery. Despite the promising findings at a small scale and few contexts, implementing new technologies as part of changes to health care services is inherently challenging. Though there is a potential to introduce mHealth initiatives to health systems of developing countries, existing evidence on the barriers and facilitators of implementation in different contexts is not adequate. Therefore, this study aimed to explore the acceptability, barriers and facilitators of implementing mobile text message reminder system for child vaccination in Ethiopia. METHODS: This study applied a phenomenological study design. The study was conducted in north-west, Ethiopia between July 28 and August 19, 2020. A total of 23 participants were purposively selected for the in-depth and key informant interviews. We used an interview guide to collect data and audio-records of interviews were transcribed verbatim. Coding was done to identify patterns and thematic analysis was conducted using ATLAS ti7 software. RESULTS: The findings indicated that mothers were receptive to mobile text message reminders for their child's vaccination. Low mobile phone ownership, access to mobile network, access to electricity and illiteracy among the target population were identified as barriers that would affect implementation. Confidentiality and security-related issues are not barriers to implementation of text message reminders for child vaccination service. Facilitators for implementation include stakeholder collaboration, providing orientation/training to users, and willingness to pay by clients. CONCLUSION: In this study, using mobile phone text message reminders for child vaccination services are acceptable by clients. Barriers identified were related to inadequate ICT infrastructure and other technical issues. Addressing the potential barriers and leveraging the existing opportunities could optimize the implementation in resource-limited settings. Before actual implementation, program implementers should also consider providing orientation to users on the proposed mHealth program.

Mothers intention and preference to use mobile phone text message reminders for child vaccination in Northwest Ethiopia.

OBJECTIVES: With the unprecedented penetration of mobile devices in the developing world, mHealth applications are being leveraged for different health domains. Among the different factors that affect the use of mHealth interventions is the intention and preference of end-users to use the system. This study aimed to assess mother's intention and preference to use text message reminders for vaccination in Ethiopia. METHODS: A cross-sectional study was conducted among 460 mothers selected through a systematic random sampling technique. Initially, descriptive statistics were computed. Binary logistic regression analysis was also used to assess factors associated with the outcome variable. RESULTS: In this study, of the 456 mothers included for analysis, 360 (78.9%) of mothers have intention to use text message reminders for vaccination. Of these, 270 (75%) wanted to receive the reminders a day before the vaccination due date. Mothers aged 35 years or more (AOR=0.35; 95% CI: 0.15 to 0.83), secondary education and above (AOR=4.43; 95% CI: 2.05 to 9.58), duration of mobile phone use (AOR=3.63; 95% CI: 1.66 to 7.94), perceived usefulness (AOR=6.37; 95% CI: 3.13 to 12.98) and perceived ease of use (AOR=3.85; 95% CI: 2.06 to 7.18) were predictors of intention to use text messages for vaccination. CONCLUSION: In conclusion, majority of mothers have the intention to use text message reminders for child vaccination. Mother's age, education, duration of mobile phone use, perceived usefulness and perceived ease of use were associated with intention of mothers to use text messages for vaccination. Considering these predictors and user's preferences before developing and testing text message reminder systems is recommended.

Development of standard indicators to assess use of electronic health record systems implemented in low-and medium-income countries.

BACKGROUND: Electronic Health Record Systems (EHRs) are being rolled out nationally in many low- and middle-income countries (LMICs) yet assessing actual system usage remains a challenge. We employed a nominal group technique (NGT) process to systematically develop high-quality indicators for evaluating actual usage of EHRs in LMICs. METHODS: An initial set of 14 candidate indicators were developed by the study team adapting the Human Immunodeficiency Virus (HIV) Monitoring, Evaluation, and Reporting indicators format. A multidisciplinary team of 10 experts was convened in a two-day NGT workshop in Kenya to systematically evaluate, rate (using Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) criteria), prioritize, refine, and identify new indicators. NGT steps included introduction to candidate indicators, silent indicator ranking, round-robin indicator rating, and silent generation of new indicators. 5-point Likert scale was used in rating the candidate indicators against the SMART components. RESULTS: Candidate indicators were rated highly on SMART criteria (4.05/5). NGT participants settled on 15 final indicators, categorized as system use (4); data quality (3), system interoperability (3), and reporting (5). Data entry statistics, systems uptime, and EHRs variable concordance indicators were rated highest. CONCLUSION: This study describes a systematic approach to develop and validate quality indicators for determining EHRs use and provides LMICs with a multidimensional tool for assessing success of EHRs implementations.

PEERNaija: A Gamified mHealth Behavioral Intervention to Improve Adherence to Antiretroviral Treatment Among Adolescents and Young Adults in Nigeria.

BACKGROUND: HIV is the leading cause of death for youth in Sub-Saharan Africa (SSA). The rapid proliferation of smart phones in SSA provides an opportunity to leverage novel approaches to promote adherence to life-saving antiretroviral therapy (ART) for adolescents and young adults living with HIV (AYA-HIV) that go beyond simple medication reminders. METHODS: Guided by the Integrate, Design, Assess and Share (IDEAS) framework, our multidisciplinary team developed a peer-based mHealth ART adherence intervention-PEERNaija. Grounded in Social Cognitive Theory, and principles of contingency management and supportive accountability, PEERNaija delivers a multi-faceted behavioral intervention within a smartphone application to address important obstacles to adherence. RESULTS: PEERNaija was developed as a gamified Android-based mHealth application to support the behavioral change goal of improving ART adherence among AYA-HIV within Nigeria, a low- and middle- income country (LMIC). Identified via foundational interviews with the target population and review of the literature, key individual (forgetfulness and poor executive functioning), environmental (poor social support) and structural (indirect cost of clinic-based interventions) barriers to ART adherence for AYA-HIV informed application features. Further informed by established behavioral theories and principles, the intervention aimed to improve self-efficacy and self-regulation of AYA-HIV, leverage peer relationships among AYA to incentivize medication adherence (via contingency management, social accountability), provide peer social support through an app-based chat group, and allow for outreach of the provider team through the incorporation of a provider application. Gamification mechanics incorporated within PEERNaija include: points, progress bar, leaderboard with levels, achievements, badges, avatars and targeted behavior change messages. PEERNaija was designed as a tethered mobile personal health record application, sharing data to the widely deployed OpenMRS electronic health record application. It also uses the secure opensource Nakama gamification platform, in line with Principles of Digital Development that emphasize use of opensource systems within LMICs. CONCLUSIONS: Theory-based gamified mHealth applications that incorporate social incentives have the potential to improve adherence to AYA-HIV. Ongoing evaluations of PEERNaija will provide important data for the potential role for a gamified, smartphones application to deliver multifaceted adherence interventions for vulnerable AYA-HIV in SSA.

mHealth spectroscopy of blood hemoglobin with spectral super-resolution.

Although blood hemoglobin (Hgb) testing is a routine procedure in a variety of clinical situations, noninvasive, continuous, and real-time blood Hgb measurements are still challenging. Optical spectroscopy can offer noninvasive blood Hgb quantification, but requires bulky optical components that intrinsically limit the development of mobile health (mHealth) technologies. Here, we report spectral super-resolution (SSR) spectroscopy that virtually transforms the built-in camera (RGB sensor) of a smartphone into a hyperspectral imager for accurate and precise blood Hgb analyses. Statistical learning of SSR enables us to reconstruct detailed spectra from three color RGB data. Peripheral tissue imaging with a mobile application is further combined to compute exact blood Hgb content without a priori personalized calibration. Measurements over a wide range of blood Hgb values show reliable performance of SSR blood Hgb quantification. Given that SSR does not require additional hardware accessories, the mobility, simplicity, and affordability of conventional smartphones support the idea that SSR blood Hgb measurements can be used as an mHealth method.

International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study.

BACKGROUND: Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare. OBJECTIVES: This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined "availability of patient data" as the ability to access data in and to add data to the patient record in the respective country. METHODS: The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators. RESULTS: Availability of patient-related information varies strongly by country. Health care professionals can access patients' most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden. CONCLUSION: Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.

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.

K-Means Clustering in Monitoring Facility Reporting of HIV Indicator Data: Case of Kenya.

Health management information systems (HMISs) in low- and middle-income countries have been used to collect large amounts of data after years of implementation, especially in support of HIV care services. National-level aggregate reporting data derived from HMISs are essential for informed decision-making. However, the optimal statistical approaches and algorithms for deriving key insights from these data are yet to be fully and adequately utilized. This paper demonstrates use of the k-means clustering algorithm as an approach in supporting monitoring of facility reporting and data-informed decision-making, using the case example of Kenya HIV national reporting data. Results reveal four homogeneous cluster categories that can be used in assessing overall facility performance and rating of that performance.

Assessment of HIV Data Reporting Performance by Facilities During EMR Systems Implementations in Kenya.

There is little evidence that implementations of Electronic Medical Record Systems (EMRs) are associated with better reporting completeness and timeliness of HIV routine data to the national aggregate system. We analyzed the reporting completeness and timeliness of HIV reports to Kenya's national aggregate reporting system from District Health Information Software 2 (DHIS2) for the period 2011 to 2018. On average, reporting completeness improved to 97% whilst timeliness increased to 83% in 2017 with similar performance for the facilities under study that implemented either KenyaEMR or IQCare. However, in 2018, the reporting rates dropped by 13% for completeness and 11% for timeliness most likely due to changed reporting procedures. This suggests that besides EMRs, there are other factors influencing reporting such as reporting routines, which need to be assessed separately. Nonetheless, the EMRs have facilitated the collection of HIV data for submission to the DHIS2, which in turn facilitates the reporting process for the data officers.

Health Facility Ownership Type and Performance on HIV Indicator Data Reporting in Kenya.

In low- and middle-income countries, private and public facilities tend to have highly variable characteristics, which might affect their performance in meeting reporting requirements mandated by ministries of health. There is conflicting evidence on which facility type performs better across various care dimensions, and only few studies exist to evaluate relative performance around nationally-mandated indicator reporting to Ministries of Health. In this study, we evaluated the relationship between facility ownership type and performance on HIV indicator data reporting, using the case of Kenya. We conducted Mann-Whitney U tests using HIV indicator data extracted from years 2011 to 2018 for all the counties in Kenya, from the District Health Information Software 2 (DHIS2). Results from the study reveal that public facilities have statistically significant better performance compared to private facilities, with an exception of year 2017 in reporting of counselling and testing, and prevention of mother-to-child transmission indicator categories.