Strengthening the national health information system through a capacity-building and mentorship partnership (CBMP) programme: a health system and university partnership initiative in Ethiopia

Utilization of health data and associated factors among department heads in public health facilities in Eastern Ethiopia: A cross-sectional study in Harari region

INTRODUCTION

Even though the information generated by routine health information systems is an essential element in the process of transforming the health sector, the information is systematically under-utilized by the health workers. Hence, this study was aimed to assess the utilization level and associated factors of routine health information system data among department heads in Eastern Ethiopia.

METHODS

The cross-sectional study design was conducted among heads of departments in the health facilities of Harari region. The source populations and the study populations were all department heads. The data were collected by standardized tools through interviews, observations, and document reviews. The data were entered into Epi Data version 3.1 and then exported to SPSS version 25 for analysis. Multivariable logistic regression was performed to identify the associated factors and P-value < 0.05 was used to declare the statistically significant association.

RESULT

Of the respondents, 51.8 % live in urban, 82.4 % participated in performance review meeting, 61.7 % received feedback, 80.6 % engage in HIS, and 91 % feel responsible to HIS. Routine health information system data utilization among department heads was 177 (79.7 %); 95 % CI: [73.8 %, 84.8 %] in the Harari region. Factors associated with data utilization were urban residence (AOR = 2.891; 95 %CI: 1.147-7.286), getting feedback (AOR = 3.136; 95 %CI: 1.311-7.499), active engagement in health information system activities (AOR = 2.560; 95 %CI: 1.010-6.490), participation in performance review meeting (AOR = 3.847; 95 %CI: 1.563-9.464), and feeling responsibility (AOR = 3.727; 95 %CI: 1.071-12.961).

CONCLUSION

Level of data use in this study was higher than the one in other studies in Ethiopia. Residence, feedback, level of engagement in health information system activities, sense of responsibility towards health information system, and performance review meeting were the determinants of data utilization. Important attention should be given by the officials at various levels to expand the information communication technology infrastructures and strengthen the feedback system.

Developing a patient flow visualization and prediction model using aggregated data for a healthcare network cluster in Southwest Ethiopia

A health information system has been created to gather, aggregate, analyze, interpret, and utilize data collected from diverse sources. In Ethiopia, the most popular digital tools are the Electronic Community Health Information System and the District Health Information System. However, these systems lack capabilities like real-time interactive visualization and a data-driven engine for evidence-based insights. As a result, it was challenging to observe and continuously monitor the flow of patients. To address the gap, this study used aggregated data to visualize and predict patient flow in a South Western Ethiopia healthcare network cluster. The South-Western Ethiopian healthcare network cluster was where the patient flow datasets were collected. The collected dataset encompasses a span of 41 months, from 2019 to 2022, and has been obtained from 21 hospitals and health centers. Python Sankey diagrams were used to develop and build patient flow visualizations. Then, using the random forest and K-Nearest Neighbors (KNN) algorithms, we achieved an accuracy of 0.85 and 0.83 for the outpatient flow modeling and prediction, respectively. The imbalance in the data was further addressed using the NearMiss Algorithm, Synthetic Minority Oversampling Technique (SMOTE), and SMOTE-Tomek methods. In conclusion, we developed a patient flow visualization and prediction model as a first step toward an end-to-end effective real-time patient flow data-driven and analytical dashboard in Ethiopia, as well as a plugin for the already-existing digital health information system. Moreover, the need for and amount of data created by these digital tools will grow along with their use, demanding effective data-driven visualization and prediction to support evidence-based decision-making.

Quality of routine health data at the onset of the COVID-19 pandemic in Ethiopia, Haiti, Laos, Nepal, and South Africa

BACKGROUND

During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19.

METHODS

We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency.

RESULTS

We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed.

CONCLUSIONS

While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

Electronic Medical Record System Use and Determinants in Ethiopia: Systematic Review and Meta-Analysis

BACKGROUND

The strategic plan of the Ethiopian Ministry of Health recommends an electronic medical record (EMR) system to enhance health care delivery and streamline data systems. However, only a few exhaustive systematic reviews and meta-analyses have been conducted on the degree of EMR use in Ethiopia and the factors influencing success. This will emphasize the factors that make EMR effective and increase awareness of its widespread use among future implementers in Ethiopia.

OBJECTIVE

This study aims to determine the pooled estimate of EMR use and success determinants among health professionals in Ethiopia.

METHODS

We developed a protocol and searched PubMed, Web of Sciences, African Journals OnLine, Embase, MEDLINE, and Scopus to identify relevant studies. To assess the quality of each included study, we used the Joanna Briggs Institute quality assessment tool using 9 criteria. The applicable data were extracted using Microsoft Excel 2019, and the data were then analyzed using Stata software (version 11; StataCorp). The presence of total heterogeneity across included studies was calculated using the index of heterogeneity I² statistics. The pooled size of EMR use was estimated using a random effect model with a 95% CI.

RESULTS

After reviewing 11,026 research papers, 5 papers with a combined total of 2439 health workers were included in the evaluation and meta-analysis. The pooled estimate of EMR usage in Ethiopia was 51.85% (95% CI 37.14%-66.55%). The subgroup study found that the northern Ethiopian region had the greatest EMR utilization rate (58.75%) and that higher (54.99%) utilization was also seen in publications published after 2016. Age groups <30 years, access to an EMR manual, EMR-related training, and managerial support were identified factors associated with EMR use among health workers.

CONCLUSIONS

The use of EMR systems in Ethiopia is relatively low. Belonging to a young age group, accessing an EMR manual, receiving EMR-related training, and managerial support were identified as factors associated with EMR use among health workers. As a result, to increase the use of EMRs by health care providers, it is essential to provide management support and an EMR training program and make the EMR manual accessible to health professionals.

Level of implementation of district health information system 2 at public health facilities in Eastern Ethiopia

Objective

The major aim of this study was to assess the level of District health information system 2 (DHIS 2) implementation in the public health facilities (HFs) in Dire Dawa City Administration.

Methods

This study was employed both quantitative (cross-sectional) and qualitative (phenomenological) study designs. All public HFs found in Dire Dawa City Administration and health workers were participated in the study. Quantitative data were collected using a pre-tested, structured, self-administered questionnaire. The collected data were entered into Epi-Data and analyzed using STATA version 14 software. A descriptive summary was computed using proportion and frequencies. Qualitative data were collected from in-depth interview with key informants (KIs), and the results were then analyzed thematically.

Results

The overall implementation level of DHIS 2 was 80%, which shows good implementation. The main difficulties encountered in implementing DHIS 2 were a lack of power backup (64.3%), unreliable internet connectivity (43%), and a lack of training (34.6%). According to an in-depth interview with a 32-year-old professional, "…there is offline and online DHIS 2 software for data collection and reporting that is an opportunity for the health center, but there is a challenge of interruption of electricity lost unsaved data and hinder data to enter and view for making a decision…."

Conclusion

The level of DHIS 2 implementation in this study was good compared to other studies in Ethiopia. However, more than half of the HFs require infrastructure maintenance and support.

Identifying Barriers to the Adoption of Information Communication Technology in Ethiopian Healthcare Systems. A Systematic Review

BACKGROUND

Ethiopia's government has planned to digitize the healthcare industry. However, most implementations fail due to various technological and personnel barriers. As a result, this systematic review aimed to comprehensively examine evidence regarding the barriers to adopting information communication technology in the Ethiopian healthcare system.

METHODS

This systematic review was conducted by searching the major databases, such as Medline, PubMed, Scopus, Science Direct, Google, Google Scholar, and other online databases. The authors looked for, analyzed, and summarized information about barriers to ICT adoption in the healthcare system. This study included nine articles that described barriers to ICT adoption in the Ethiopian healthcare system.

RESULTS

This systematic review identified 15 barriers to adopting ICT in the healthcare system. The reviewed articles looked into technological barriers to ICT adoption, such as ICT skill, ICT knowledge, a lack of training opportunities, a lack of computer literacy, a lack of computer access, inadequate internet connectivity, and a lack of experience with ICT were cited as barriers to ICT implementation in Ethiopia's healthcare system. Furthermore, organizational components such as Lack of job satisfaction, Lack of Refreshment training, poor staff initiation, management problem, poor infrastructure, and lack of resources remained barriers to ICT adoption in Ethiopia's healthcare system.

CONCLUSION

This review confirmed that lack of training in ICT, poor ICT knowledge, Poor ICT skill, and a lack of computer access were the most common barriers to adopting ICT in the Ethiopian healthcare system. Therefore, it is recommended that the emphasized barriers to ICT adoption be addressed in order to modernize the current Ethiopian healthcare system.