Assessment of data demand for informed-decisions among health facility and department heads in public health facilities of Amhara Region, northwest Ethiopia.

BACKGROUND: Evidence-based decision-making is a foundation of health information systems; however, routine health information is not mostly utilized by decision makers in the Amhara region. Therefore, this study aimed to explore the facility and department heads' perceptions towards the demand for and use of routine health information for decision making. METHODS: A phenomenological qualitative study was done in eight districts of the Amhara region from June 10/2019 to July 30/2019. We obtained written informed consent and recruited 22 key informants purposively. The research team prepared a codebook, assigned codes to ideas, identified salient patterns, grouped similar ideas, and developed themes from the data. Thus, data were analyzed thematically using OpenCode software. RESULTS: The study revealed that health workers collected many data, but little was demanded and utilized to inform decisions. The majority of respondents perceived that data were collected merely for reporting. Lack of skills in data management, analysis, interpretation, and use were the technical attributes. Individual attributes included low staff motivation, carelessness, and lack of value for data. Poor access to data, low support for Health Information System, limited space for archiving, and inadequate finance were related to organizational attributes. The contextual (social-political) factors also influenced the use of eHealth applications for improved data demand and use among health care providers. CONCLUSION: In this study, health workers collect routine health data merely for reporting, and they did not demand and use it mostly to inform decisions and solve problems. Technical, individual, organizational, and contextual attributes were contributors to low demand and use of routine health data. Thus, we recommend building the technical capacity of health workers, introducing motivation mechanisms and ensuring accountability systems for better data use.

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

BACKGROUND: Despite 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. OBJECTIVE: The aim of this study was to explore the facilitators and barriers to the sustainable use of eHealth solutions in low- and middle-income nations. METHODS: A 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. RESULTS: A 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. CONCLUSIONS: This 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.

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

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 & 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.

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.

BACKGROUND: Weak 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. OBJECTIVE: This 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. METHODS: The 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 ß 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. RESULTS: Data 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. CONCLUSIONS: The 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 REGISTRATION: Pan African Clinical Trials Registry PACTR202001559723931; https://tinyurl.com/3j7e5ka5.

Routine health information system utilization for evidence-based decision making in Amhara national regional state, northwest Ethiopia: a multi-level analysis.

BACKGROUND: Health Information System is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it. METHOD: A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The single population proportion formula was applied to estimate the sample size taking into account the proportion of data use 0.69, margin of error 0.05, and the critical value 1.96 at the 95% CI. The final sample size was estimated at 394 by considering 1.5 as a design effect and 5% non-response. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p value < 0.05 were considered as predictors of routine health information system use. RESULT: Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR = 12.42, 95% CI [5.52, 27.98]) and performance (AOR = 1.68; 95% CI [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR = 2.29; 95% CI [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR = 3.53; 95% CI [1.61, 7.75]), receiving senior management directives (AOR = 3.56; 95% CI [1.76, 7.19]), supervision (AOR = 2.84; 95% CI [1.33, 6.07]), using HMIS data for target setting (AOR = 3.43; 95% CI [1.66, 7.09]), and work location (AOR = 0.16; 95% CI [0.07, 0.39]) were organizational (level-2) explanatory variables. CONCLUSION: The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.