Surviving Institutional Contradictions: Routine Data Use Practices at the Subnational Levels

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ID: 329115
2026
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Abstract
Abstract Routine Health Information System (RHIS) data are widely promoted as a foundation for evidence-informed planning, supervision, and service improvement in low- and middle-income countries. Yet their use in decentralized health systems is often shaped by contradictory institutional logics. In this study, contradictory institutional logics refer to conflicting expectations about what actors should prioritize, how data should be used, and which resources are made available to do so. We examined how these contradictions shape routine data use at subnational levels of the Tanzanian health system and how local actors respond to them. We conducted a qualitative study in the Dodoma City Council and the Bahi District Council, Tanzania, between 2024 and 2025. Data were generated through 31 key informant interviews and non-participant observations across 12 purposively selected health facilities and two council health management teams. Participants included facility in-charges, health management information system focal persons, facility programme coordinators, and council programme coordinators. Data were analyzed thematically using institutional theory as an interpretive lens. The findings from the two councils reveal that routine data use was not absent; rather, it was improvised within a contradictory institutional environment. Strengthening data use, therefore, requires more than technical deployment. It requires institutionalized procedures for review and supervision, broader analytic capacity at the facility level, better alignment between DHIS2 and GoT-HOMIS, and target-setting and feedback practices that are meaningful to local service realities. These findings are analytically relevant to similar decentralized settings, although they are not statistically generalizable beyond the study context.
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openalex_W7213560217 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors
Journal Oxford Open Digital Health
Year 2026
DOI
10.1093/oodh/oqag036
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