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REVIEW
Open Access

Factors That Influence Data Use to Improve Health Service Delivery in Low- and Middle-Income Countries

Nicole Rendell, Kamalini Lokuge, Alexander Rosewell and Emma Field
Global Health: Science and Practice September 2020, 8(3):566-581; https://doi.org/10.9745/GHSP-D-19-00388
Nicole Rendell
aResearch School of Population Health, Australian National University, Canberra, Australia.
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  • For correspondence: nicole.rendell@anu.edu.au
Kamalini Lokuge
aResearch School of Population Health, Australian National University, Canberra, Australia.
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Alexander Rosewell
bUniversity of New South Wales, Kensington, Australia.
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Emma Field
aResearch School of Population Health, Australian National University, Canberra, Australia.
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    FIGURE.

    Screening Process Used for Systematic Literature Review of Evidence on Use of Health Service Delivery Data at the Primary Care Level in Low- and Middle-Income Countries

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    TABLE 1.

    Summary of Content Analysis on Factors That Influence Data Use To Improve Health Service Delivery in Low- and Middle-Income Countries

    Reference and LocationPeer-Reviewed Literature AnalysisGray Literature Analysis
    LeadershipParticipatory MonitoringPresentation of FindingsData QualityQualitative DataElectronic HMISOrganizational StructureContextual FactorsPBFRegular ReviewaTraininga
    Peer-reviewed literature analysis
    Björkman and Svensson37 – UgandaX
    Chukwuani et al32 – Enugu State, NigeriaX
    Edward et al33 – AfghanistanXX
    Edward et al39 – AfghanistanXX
    Holvoet and Inberg38 – Rwanda and UgandaXXXXX
    Jacobs et al40 – Kirivong Operational Health District, south east CambodiaXX
    Kananura et al41 – 3 districts in eastern UgandaXXXXX
    Khim et al34 – CambodiaXX
    Krishnan et al35 – Ballabgarh, IndiaXX
    Nutley et al42 – KenyaXX
    Nutley et al36 – Côte d’IvoireXXXXXX
    Wagenaar et al43 – Mozambique, Rwanda, and ZambiaXXX
    Gray literature analysis
    Afe et al44 – NigeriaXXXXX
    Anasel et al46 – TanzaniaXXXXX
    Li et al45 – TanzaniaXXX
    MEASURE Evaluation47 – MaliX
    MEASURE Evaluation48 – KenyaXXXXX
    Millar et al49 – KenyaXXX
    • Abbreviations: HMIS, Health Management Information System; PBF, performance-based financing.

    • ↵a Identified as potential factors following gray literature analysis.

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    TABLE 2.

    Classification of Influential Factors on Data Use to Improve Health Service Delivery

    GovernanceProduction of InformationHealth Information System Resources
    • Leadership

    • Participatory monitoring

    • Regular reviewa

    • Presentation of findings

    • Data quality

    • Qualitative data

    • Electronic HMIS

    • Organizational structure

    • Training (in data use)a

    • ↵a Factors identified through gray literature analysis.

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Global Health: Science and Practice: 8 (3)
Global Health: Science and Practice
Vol. 8, No. 3
September 30, 2020
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Factors That Influence Data Use to Improve Health Service Delivery in Low- and Middle-Income Countries
Nicole Rendell, Kamalini Lokuge, Alexander Rosewell, Emma Field
Global Health: Science and Practice Sep 2020, 8 (3) 566-581; DOI: 10.9745/GHSP-D-19-00388

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Factors That Influence Data Use to Improve Health Service Delivery in Low- and Middle-Income Countries
Nicole Rendell, Kamalini Lokuge, Alexander Rosewell, Emma Field
Global Health: Science and Practice Sep 2020, 8 (3) 566-581; DOI: 10.9745/GHSP-D-19-00388
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