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Routine use of DHIS2 data: a scoping review.

Elaine Byrne1, Johan Ivar Sæbø2

  • 1HISP Centre and Department of Informatics, University of Oslo, Gaustadalléen 30, N-0373, Oslo, Norway. elaineb@ifi.uio.no.

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|October 6, 2022
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Summary

While the DHIS2 platform is widely used, detailed documentation on its data utilization for decision-making is scarce. Further research is needed to understand and improve how health data are used in practice.

Keywords:
DHIS2Health information systemRoutine data useScoping review

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Area of Science:

  • Health Informatics
  • Public Health Data Management
  • Information Systems Research

Background:

  • Effective health service planning relies on data utilization across all system levels.
  • Despite widespread adoption of platforms like DHIS2, actual data use for decision-making remains a challenge.
  • A lack of rigorous review exists on how DHIS2 data are routinely used for health programming.

Purpose of the Study:

  • To conduct a scoping review of the literature on the routine use of DHIS2 data for decision-making and programming.
  • To identify gaps in the documentation and understanding of DHIS2 data utilization.

Main Methods:

  • A five-stage scoping review approach (Arksey & O'Malley, Levac et al., Peters) was employed.
  • Searches were conducted across PubMed, Web of Science, and Embase, supplemented by conference proceedings and theses.
  • Over 500 documents were screened, with data extracted from 19 relevant sources.

Main Results:

  • DHIS2 data are being utilized, but detailed descriptions in published literature are limited.
  • Common patterns of centralized versus decentralized data access and reporting were observed.
  • Explicit conceptualizations of data use and its underlying principles are often not detailed.

Conclusions:

  • There is a need for more detailed documentation and sharing of how DHIS2 data are used.
  • Further investigation into data creation processes and user identification is recommended.
  • Future system design should align with work practices and foster data-centric discussions.