Performance Measurement and Management in Primary Care Delivery Systems

Published date: 28 September 2018
Last modified date: 28 September 2018

This map provides an overview of existing studies and gaps on the effects of performance measurement and management (PMM) systems interventions. These systems are designed to measure and improve the performance of healthcare delivery systems and their effective functioning is important for creating high-quality primary healthcare services in L&MICs.
Authors of this map identified published and unpublished studies between 2000 and mid-28, including 137 impact evaluations and 18 systematic reviews.

Main findings

  • Most of the evidence is concentrated in Sub- Saharan Africa (56%) and South Asia (19%).
  • Most of the impact evaluations are randomised (71%), followed by before-and-after studies (21%). Others use a mixed-methods approach.
  • The majority of available evidence focuses on implementation strategies (e.g. in-service training and continuous education) and financial arrangements (e.g. performance-based financing).
  • There is a lack of evidence on accountability arrangements, including audit and feedback, public release of performance information, and social accountability interventions.
  • The majority of studies focus on individual outcomes amongst health workers or patients, whilst few examine more complex organisational outcomes or equity effects of PPM interventions.

Implications for policy, programming and research investments

  • There is a need for a coordinated research and learning agenda, organised around a common multidisciplinary conceptual framework of PMM strategies as complex adaptive systems.
  • Filling evidence gaps should be driven by end-user needs and an improved consideration of the context for the health systems being researched.
  • Rigorous impact evaluations provide reliable evidence on effects, but a focus on effects is not sufficient. Future studies should adopt mixed-method impact evaluations, based on convincing theories of change, to address the range of questions relevant for policy and practice, including how and why change happens, for whom, and at what cost.
  • Future research needs to address a broader range of outcomes and adopt gender- and equity-sensitive study designs that go beyond subgroup analysis.
  • PMM strategies could create perverse incentives, and studies should therefore also pay attention to and measure potentially adverse effects.
  • Synthesis gaps remain for high-quality reviews of interventions on clinical practice guidelines, reminders, clinical incident reporting, continuous quality improvement, and organisational audits and feedback.
  • Researchers and commissioners should ensure future research meets commonly accepted standards for research transparency, including preregistration, data sharing and comprehensive reporting.

Original map publication date: N/A
Current map date of publication: 30 September 2019

Online map citation: Munar, W, Snilstveit, B, Aranda, LE, Biswas, N, Baffour, T and Stevenson, J, 2019. Performance measurement and management in primary healthcare systems in low-and middle-income countries. 3ie Evidence Gap Map [Online]. New Delhi: International Initiative for Impact Evaluation (3ie).

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