Behavioral factors affecting data quality and information utilization in health facilities in ethiopia, 2023: an exploratory qualitative study.

Abstract

Background: A well-functioning Health Information System (HIS) is essential for evidence-based decision-making and improved health outcomes. In Ethiopia, the government's Information Revolution (IR) initiative, supported by programs like the Capacity Building and Mentorship Program (CBMP), aims to strengthen HIS performance by enhancing data quality and use. Despite progress, the behavioural factors influencing data quality and use remain underexplored. This study aimed to investigate behavioural barriers and enablers affecting data quality and information use in health facilities across Ethiopia.

Methods: An exploratory qualitative study was conducted in CBMP-supported health centers across four regions (Sidama, Amhara, Oromia, and Somali) and one city administration (Addis Ababa). Key informants included health service providers, Health Management Information System (HMIS) focal persons, facility heads, and case team leaders. Using semi-structured guides, data were collected through 43 key informant interviews and 15 focus group discussions (FGDs). Thematic analysis was conducted using Atlas.ti version 7.5 16.

Results: The study identified seven key behavioural themes influencing data quality and use: perceived data value, self-efficacy, motivation and commitment, competing priorities, teamwork, protocol adherence, and leadership/governance. While some providers appreciated the value of data in improving service delivery, others deprioritised it due to clinical demands. Self-efficacy was often limited by insufficient training and technical skill gaps. Motivation was negatively impacted by poor recognition and weak support systems. Clinical workloads and cognitive burden further reduced attention to data tasks. Although team collaboration existed, peer learning was limited and sometimes resisted. Adherence to data protocols such as the ESV-ICD-11 and PMT logbooks was inconsistent. Leadership support, role clarity, and accountability mechanisms were found to be weak, affecting overall HIS performance.

Conclusions: Behavioural factors, including inconsistent data valuation, low motivation, poor self-efficacy, limited peer collaboration, and weak leadership, are significant barriers to effective HIS practices in Ethiopia. Addressing these challenges will require integrated solutions: digital learning tools like Telegram-based bots to build skills, PMT optimisation strategies, and stronger leadership and accountability frameworks. These combined interventions can improve data quality, support evidence-informed decisions, and strengthen Ethiopia's primary healthcare system.