Data Quality in Health Information Systems: Healthcare Stakeholders’ Lived Experiences in Botswana

Introduction and Objectives: Health Information Systems (HIS) in Botswana and similar low- and middle-income countries (LMICs) struggle with persistent data quality issues. While technical constraints are well understood, the lived experiences of healthcare stakeholders (including frontline healthcare workers, data managers, and policymakers) who generate and use health data remain poorly understood. This study examines how these experiences shape professional practice and influence HIS performance and data quality.Materials and Methods: This qualitative study used Interpretative Phenomenological Analysis (IPA) to explore the lived experiences of 61 healthcare stakeholders in Botswana. Participants were recruited using purposive sampling. The study was conducted in four settings central to Botswana’s HIS landscape: an urban hospital [blinded for peer review], a peri-urban hospital [blinded for peer review], a specialty clinic [blinded for peer review], and a national health authority [blinded for peer review]. Data were collected through open-ended written prompts, one-to-one semi-structured individual interviews (for clarification probing of written responses), and focus groups and were analysed ideographically.Results: Four experiential themes were constructed: Opaque Hand, feeling subject to unilateral system changes without consultation; Fractured Whole, experiencing professional fragmentation and exclusion from HIS governance; Social Mirror, having adoption shaped by peer dynamics and cultural resistance; and finally, the Broken Bridge, working with misaligned, fragmented systems that hinder care delivery. All these themes undermined data quality and system engagement.Conclusions: HIS challenges are fundamentally human, eroding frontline agency and professional identity. Sustainable improvement requires a paradigm shift toward participatory, human-centred co-design that integrates health workers' expertise into the governance and policy, system development, and change management process to strengthen data quality and HIS engagement.