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Utilization of health management information system for data driven decisions in maternal healthcare in Addis Ababa

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Utilization of health management information system for data driven decisions in maternal healthcare in Addis Ababa Kasu Tola Bifa A Health Management Information System (HMIS) is the essential component of the country's Health Information System (HIS) and is vital for the functioning of the country’s healthcare system. It consists of prescribed data management processes, including utilization of data for informed decisions. One of its key applications is the recording, storing, retrieval, and processing of maternal health data to enhance decision-making processes. The study intended to evaluate the utilization of the HMIS for data-driven decisions in maternal healthcare in Addis Ababa, Ethiopia. The study was conducted in six selected public hospitals. The hospitals were tertiary hospitals offering comprehensive curative and tertiary care, including maternal healthcare services, and they have implemented the Health Management Information System. All these facilities fall under the administration of the Addis Ababa City Administration Health Bureau. An explanatory sequential mixed method design was employed to evaluate the utilization of the HMIS. A modified Delphi technique was used to validate the proposed strategies to improve maternal HMIS data management. The population for the study was physicians, midwives and nurses. Multistage cluster and stratified sampling, purposive sampling using maximum variation, and purposive sampling were used to select the health facilities, healthcare professionals, and experts, respectively. Data collection methods included self-administered questionnaires, focus group interviews, and the modified Delphi technique. Quantitative data were analysed using the Statistical Package for Social Sciences (SPSS) software for Windows, while qualitative data underwent thematic analysis. Additionally, descriptive statistics were applied during Phase III of the study. The theoretical framework guided the data collection, analysis and interpretation. The results revealed dissatisfaction with the HMIS's ability to capture comprehensive maternal healthcare data. Some of the key issues were a lack of integration and seamless exchange of information between different systems. This had the potential to create silo data-generating units. The hybrid system appeared to be not well coordinated as participants seemed to struggle with some basic HMIS tasks such as data collection, analysis and using information for decision-making. Dissatisfaction with the level of HMIS training and the shortage of specialized HIS skills appeared to be a barrier to effective HMIS utilization, as healthcare professionals focused more on clinical care than HIS tasks. Some variations were observed in the utilization of HMIS among different professionals. Most participants generally believed that strengthening the HMIS and improving monitoring and evaluation was essential for accurate, timely information on healthcare interventions. The majority acknowledged ex- istence of guidelines that provided directives for data management processes. However, they lamented poor implementation. The findings confirmed the relationships between different concepts of the theoretical framework, including their impact on HMIS utilization, information use and decision- making. Strategies were developed to address the factors affecting the utilization of HMIS for data-driven decision-making, aiming to improve maternal HMIS data management. Text in English

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