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Measuring what matters - information systems for management of chronic disease in primary healthcare settings in low and middle-income countries: challenges and opportunities

Epidemiology and psychiatric sciences, 2020-01, Vol.29, p.e127-e127, Article e127 [Peer Reviewed Journal]

2020 This article is published under (https://creativecommons.org/licenses/by/3.0/) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 2020 The Author(s) ;ISSN: 2045-7960 ;EISSN: 2045-7979 ;DOI: 10.1017/S204579602000030X ;PMID: 32389151

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  • Title:
    Measuring what matters - information systems for management of chronic disease in primary healthcare settings in low and middle-income countries: challenges and opportunities
  • Author: Mayston, R ; Ebhohimen, K ; Jacob, K
  • Subjects: Chronic Disease ; Chronic illnesses ; Community Mental Health Services - organization & administration ; Comorbidity ; Decision making ; Delivery of Health Care - organization & administration ; Developing Countries ; Disease ; Electronic health records ; Health Services Administration ; Humans ; Information systems ; Management Information Systems ; Medical personnel ; Mental health ; Planning ; Population ; Primary care ; Primary Health Care - organization & administration ; Quality ; Quality of care ; Quality of Health Care ; R&D ; Research & development
  • Is Part Of: Epidemiology and psychiatric sciences, 2020-01, Vol.29, p.e127-e127, Article e127
  • Description: Effective health information systems are essential to the delivery of high-quality community-based care for chronic disease which will be needed to address the changing healthcare needs of populations in low and middle-income country settings. Health management information systems (health service data collected at facility level) and electronic health records (data organised by individual patients) may support the measurement-based, collaborative approach that is central to the chronic care model, which has been adopted as the basis for task-shared models of care for mental health and non-communicable disease. We used the performance of routine information systems management to guide our commentary on the evidence-base about information systems to support chronic care. We found that, despite an appetite for using the information to support decision-making around service planning, this rarely happens in practice, reasons include that data is not perceived to be of good quality or fit for purpose. There is often a mismatch between technology design and the availability of specialised knowledge and infrastructure. However, when data collection is designed in collaboration with local stakeholders, there is some evidence of success, demonstrated by completion and accuracy of data forms. Whilst there are global targets for the development of health information systems and progress on these is undoubtedly being made, indicators for chronic disease are seldom prioritised by national governments and there is insufficient decentralisation to facilitate local data-driven decision-making. Our recommendations for future research and development, therefore, focus upon the need to integrate context into the design of information systems: through building strong multisectoral partnerships, ensuring newly developed indicators are well aligned to service models and using technology that is a good fit with local infrastructure. This approach will be necessary if information systems are to deliver on their potential to drive improvements in care for chronic disease.
  • Publisher: England: Cambridge University Press
  • Language: English;Italian
  • Identifier: ISSN: 2045-7960
    EISSN: 2045-7979
    DOI: 10.1017/S204579602000030X
    PMID: 32389151
  • Source: ProQuest One Psychology
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    ProQuest Databases
    PubMed Central
    DOAJ: Directory of Open Access Journals
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