Evaluating utilization of health information management system for HIV/AIDS monitoring in Ethiopia

Abstract

A well-performing Health Information System (HIS) provides timely, complete, accurate and easily retrievable data. It also reflects the impact of guidelines and policies on the functioning of the health system. However, HIS in Low- and Middle-Income Countries (LMIC) is highly complex and influenced by pressures from donors, politics and the administration. Hence, these countries experience persistent challenges to produce quality data from their HIS. Studies in Ethiopia indicate challenges in the data management processes, poor data quality, a low information culture, and difficulties in using HMIS data. The purpose of this study was to evaluate the use of the HMIS in generating quality health information for monitoring and evaluating the HIV and AIDS program in Ethiopia. The aim was to develop a framework for strengthening the information culture and the generation of reliable and accurate data to support HIV and AIDS monitoring and evaluation. The study adopted the PRISM framework to inform the research methods. A qualitative evaluative case study was used to address the research questions. The research was implemented in three phases: Phase 1, a qualitative document analysis; Phase 2, focus group interviews; and Phase 3, developing a framework to strengthen data management processes for HIV/AIDS, using a modified Delphi technique. The study setting was public hospitals and health centres in Addis Ababa. These were selected due to their involvement with HIV/AIDS and sites for HMIS implementation. The population for the first phase was government policy documents. The data sources included country-level developed HIS and HMIS/M&E documents currently in use. The population for Phase 2 included stakeholders using the country HIS and implementing the HMIS, mainly those who produced and used data for HIV/AIDS monitoring. In the third phase, the population consisted of experts in HIS and HMIS. Non-probability sampling techniques, such as purposive criterion for Phase 1, purposive critical case sampling for Phase 2, and snowball for Phase 3, were used to select experts. Data were collected over six months, starting with qualitative document analysis. The QDA provided a broad historical context for the study, suggesting possibility to explore further through other forms of data collection. The second phase involved data collection through focus group discussions (FGD) to describe participants' views on data generation and information used for HIV/AIDS monitoring and evaluation. This phase included the integration of both data sets. Phase 3 used a questionnaire to elicit the views of experts on the proposed framework. Qualitative analytical techniques using Atlas.Ti version 8 were used to analyse data. Content analysis was used in Phase 1 and thematic analysis in Phase 2. Phase 3 used statistical analysis to quantify the level of consensus among experts. The trustworthiness of this study was safeguarded by applying credibility, transferability, dependability, and confirmability. The ethical measures in this study were followed to protect the rights of the institutions, the rights of participants, the dissemination of findings and scientific integrity. This study showed that Ethiopia had an adequate regulatory framework for implementing HIS and HMIS to monitor and evaluate the HIV/AIDS program. However, the implementation of these policies at the facility level was not optimal. Stakeholders experienced various difficulties accessing the policies but were aware of their role and what was expected of them. Availability of resources and the design of HIS were found to be not ideal for users. Timely reporting was hampered by parallel reporting systems such as DHIS2 and Smart Care, a lack of interoperability between these systems, and a hybrid system consisting of paper documents and electronic data. The study concluded that health facilities did not process information as expected. However, staff performed the HMIS tasks with the tools available to them as they tried to make sense of data coming out of the HMIS. Challenges of the system, such as a lack of human resources and specialized skills, and support, could be improved for the effective use of the HMIS for generating useful information for HIV monitoring. The proposed framework will hopefully strengthen data management processes.