Strategic Partnerships in e-Health in Low and Lower Middle-Income Countries in Africa

Strategic partnerships are very important for the successful deployment of e-health as they play a crucial role in achieving common goals and creating an added value for the involved partners. In this paper, we will provide relevant information about strategic partnerships in e-health deployment in four African countries, namely Ethiopia, Ghana, Malawi, and Tunisia. A Partnership Assessment Tool is developed to analyze different aspects of partnerships and classify them. According to the analysis, 11 partnerships were strategic amongst the 15 identified. Findings analysis also shows that certain aspects, mainly sustainability, have to be enhanced to guarantee the impact of partnerships after the ending of its actions. Increased governmental support is required in addition to international funding resources to the successful deployment of e-health in the participating countries.publishedVersio

The Effectiveness of the Capacity Building and Mentorship Program in Improving Evidence-Based Decision-making in the Amhara Region, Northwest Ethiopia: Difference-in-Differences Study

BackgroundWeak health information systems (HISs) hobble countries’ abilities to effectively manage and distribute their resources to match the burden of disease. The Capacity Building and Mentorship Program (CBMP) was implemented in select districts of the Amhara region of Ethiopia to improve HIS performance; however, evidence about the effectiveness of the intervention was meager. ObjectiveThis study aimed to determine the effectiveness of routine health information use for evidence-based decision-making among health facility and department heads in the Amhara region, Northwest Ethiopia. MethodsThe study was conducted in 10 districts of the Amhara region: five were in the intervention group and five were in the comparison group. We employed a quasi-experimental study design in the form of a pretest-posttest comparison group. Data were collected from June to July 2020 from the heads of departments and facilities in 36 intervention and 43 comparison facilities. The sample size was calculated using the double population formula, and we recruited 172 participants from each group. We applied a difference-in-differences analysis approach to determine the effectiveness of the intervention. Heterogeneity of program effect among subgroups was assessed using a triple differences method (ie, difference-in-difference-in-differences [DIDID] method). Thus, the β coefficients, 95% CIs, and P values were calculated for each parameter, and we determined that the program was effective if the interaction term was significant at P<.05. ResultsData were collected using the endpoint survey from 155 out of 172 (90.1%) participants in the intervention group and 166 out of 172 (96.5%) participants in the comparison group. The average level of information use for the comparison group was 37.3% (95% CI 31.1%-43.6%) at baseline and 43.7% (95% CI 37.9%-49.5%) at study endpoint. The average level of information use for the intervention group was 52.2% (95% CI 46.2%-58.3%) at baseline and 75.8% (95% CI 71.6%-80.0%) at study endpoint. The study indicated that the net program change over time was 17% (95% CI 5%-28%; P=.003). The subgroup analysis also indicated that location showed significant program effect heterogeneity, with a DIDID estimate equal to 0.16 (95% CI 0.026-0.29; P=.02). However, sex, age, educational level, salary, and experience did not show significant heterogeneity in program effect, with DIDID estimates of 0.046 (95% CI –0.089 to 0.182), –0.002 (95% CI –0.015 to 0.009), –0.055 (95% CI –0.190 to 0.079), –1.63 (95% CI –5.22 to 1.95), and –0.006 (95% CI –0.017 to 0.005), respectively. ConclusionsThe CBMP was effective at enhancing the capacity of study participants in using the routine HIS for decision-making. We noted that urban facilities had benefited more than their counterparts. The intervention has been shown to produce positive outcomes and should be scaled up to be used in other districts. Moreover, the mentorship modalities for rural facilities should be redesigned to maximize the benefits. Trial RegistrationPan African Clinical Trials Registry PACTR202001559723931; https://tinyurl.com/3j7e5ka

Sociodemographic profiling of tuberculosis hotspots in Ethiopia, 2014–2017

Tuberculosis (TB) notification rates vary across regions in Ethiopia and districts within the Amhara Region. The Amhara Region is one of the main TB hotspot regions in the country. In this study we identified the spatial distribution of TB and characterized the sociodemographic factors of spatial clusters in the Amhara Region.An ecological spatial analysis of TB notifications from 2014 to 2017 was conducted to quantify the presence and location of spatial clusters of TB notifications at the district level within the Amhara Region. Global Moran's I statistics and local indicators of spatial association were used to explore the spatial clustering of TB notifications. Notifications from hotspots and low-risk districts were compared to identify significant sociodemographic factors using analysis of variance and Classification and Regression Tree analysis. The geographic information system and 'sp' packages of R software were used for spatial analysis.From 2014 to 2017 the average notification rate of all forms of TB in the Amhara Region was 107/100 000 population (range 18-614 per 100 000 population). District-level TB notification rates were positively spatially autocorrelated, with Moran's I value ranging from 0.207 to 0.276 (p=0.01). Hotspot TB clusters were found in the northwest and central part of the region. The proportion of migrants (F(3,124)=23.21,

Lessons and Implementation Challenges of Community Health Information System in LMICs: A Scoping Review of Literature: CHIS

Background: Accurate and timely information on health intervention coverage, quality, and equity is the foundation of public health practice. To achieve this, countries have made efforts to improve the quality and availability of community health data by implementing the community health information system that is used to collect data in the field generated by community health workers and other community-facing providers. Despite all the efforts, evidence on the current state is scant in Low Middle Income Countries (LMICs).Objective: To summarize the available evidence on the current implementation status, lessons learned and implementation challenges of community health information system (CHIS) in LMICs.Methods: We conducted a scoping review that included studies searched using electronic databases like Pubmed/Medline, World Health Organization (WHO) Library, Science Direct, Cochrane Library. We also searched Google and Google Scholar using different combinations of search strategies. Studies that applied any study design, data collection and analysis methods related to CHIS were included. The review included all studies published until February 30, 2022. Two authors extracted the data and resolved disagreements by discussion consulting a third author.Results: A total of 1,552 potentially relevant articles/reports were generated from the initial search, of which 21 were considered for the final review. The review found that CHIS is implemented in various structures using various tools across different LMICs. For the CHIS implementation majority used registers, family folder/card, mobile technologies and chalk/white board. Community level information was fragmented, incomplete and in most cases flowed only one way, with a bottom-up approach. The review also indicated that, technology particularly Electronic Community Health Information System (eCHIS) and mobile applications plays a role in strengthening CHIS implementation in most LMICs. Many challenges remain for effective implementation of CHIS with unintegrated systems including existence of parallel recording &amp; reporting tools. Besides, lack of resources, low technical capacity, shortage of human resource and poor Information Communication Technology (ICT) infrastructure were reported as barriers for effective implementation of CHIS in LMICs.Conclusion: Generally, community health information system implementation in LMICs is in its early stage. There was not a universal or standard CHIS design and implementation modality across countries. There are also promising practices on digitalizing the community health information systems. Different organizational, technical, behavioural and economic barriers exist for effective implementation of CHIS. Hence, greater collaboration, coordination, and joint action are needed to address these challenges. Strong leadership, motivation, capacity building and regular feedback are also important to strengthen the CHIS in LMICs. Moreover, CHIS should be transformed in to eCHIS with integration of different technology solutions. Local ownership is also critical to the long-term sustainability of CHIS implementation

Facilitators and Barriers to the Sustainability of eHealth Solutions in Low- and Middle-Income Countries: Descriptive Exploratory Study

BackgroundDespite the widely anticipated benefits of eHealth technologies in enhancing health care service delivery, the sustainable usage of eHealth in transitional countries remains low. There is limited evidence supporting the low sustainable adoption of eHealth in low- and middle-income countries. ObjectiveThe aim of this study was to explore the facilitators and barriers to the sustainable use of eHealth solutions in low- and middle-income nations. MethodsA qualitative descriptive exploratory study was conducted in 4 African nations from September to December 2021. A semistructured interview guide was used to collect the data. Data were audio-recorded and transcribed from the local to the English language verbatim, and the audio data were transcribed. On the basis of the information gathered, we assigned codes to the data, searched for conceptual patterns, and created emerging themes. Data were analyzed thematically using OpenCode software. ResultsA total of 49 key informant interviews (10 from Tunisia, 15 from Ethiopia, 13 from Ghana, and 11 from Malawi) were conducted. About 40.8% (20/49) of the study participants were between the ages of 26 and 35 years; 73.5% (36/49) of them were male participants; and 71.4% (35/49) of them had a master’s degree or higher in their educational background. Additionally, the study participants' work experience ranged from 2 to 35 years. Based on the data we gathered, we identified 5 themes: organizational, technology and technological infrastructure, human factors, economy or funding, and policy and regulations. ConclusionsThis study explores potential facilitators and barriers to long-term eHealth solution implementation. Addressing barriers early in the implementation process can aid in the development of eHealth solutions that will better fulfill the demands of end users. Therefore, focusing on potential challenges would enhance the sustainability of eHealth solutions in low- and middle-income countries