1. Factors contributing to poor healthcare data quality: qualitative study from Southern Ethiopia
- Author
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Endriyas, Misganu, Alano, Abraham, Mekonnen, Emebet, Hailu, Samuel, Hailemariam, Tesfahun, Ayele, Sinafikish, Shiferaw, Mekonnen, Kelaye, Temesgen, Misganaw, Tebeje, and Samuel, Teka
- Abstract
Background: Although quality information is key to reliable healthcare, health management information system (HMIS) data in low-income countries are inaccurate and not reliable. So, health managers should monitor quality of data and factors affecting it for system improvements. Hence, this study explored factors affecting HMIS data quality in southern Ethiopia. Methods: This qualitative study was conducted in southern Ethiopia and included 15 key informants working at different levels of health system. Tools were developed following Performance of Routine Information System Management (PRISM) conceptual framework, which includes behavioral, technical and organizational factors. Data were analyzed manually using descriptive approach and framework analysis. Results: The complexity of reporting forms and registers, inflexibility and low coverage of electronic health management information system (eHMIS) and frequent failure of computer system were some of technical challenges reported. Knowledge gaps of indicators definition, data handling, data analysis and interpretation and maintaining computer system were noted as major challenges at all levels. Negligence, low commitment and political influences were also noted in some cases. Moreover, inappropriate personnel assignment to the positions responsible for HMIS is causing difficulties in data management and use. Organizational and managerial supports to solve the challenges were reported insignificant. Conclusion: Strengthening technical supports like training and mentorship is crucial to familiarize HMIS personnel with the system and address technical gaps. Negligence and low commitment needing administrative responses should be handled accordingly. Insufficient organizational efforts to maintain HMIS data quality and use show the need to advocate HMIS to decision-makers. Finally, in-depth investigation of reasons behind low commitment and political influence is needed to better understand root causes and links.
- Published
- 2023
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