Evidence map›Paper›PMID 36410829›Full record

ArticleBMJ open2022

Characterising performance information use in the primary healthcare systems of El Salvador, Lebanon and Malawi: multiple qualitative case study protocol.

Wolfgang Munar, Syed Shabab Wahid, Martha Makwero, Fadi El-Jardali, Luckson Dullie, Wen-Chien Yang

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Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Wolfgang MunarGlobal Health, The George Washington University Milken Institute of Public Health, Washington, District of Columbia, USA wolfgangmunar@gwu.edu.ORCID 0000-0002-9234-987X
Syed Shabab WahidInternational Health, School of Health, Georgetown University, Washington, District of Columbia, USA.
Martha MakweroSchool of Public Health and Family Medicine, University of Malawi College of Medicine, Blantyre, Malawi.
Fadi El-JardaliDepartment of Health Management and Policy, American University of Beirut, Beirut, Lebanon.
Luckson DulliePartners In Health, Neno, Malawi.
Wen-Chien YangGlobal Health, The George Washington University Milken Institute of Public Health, Washington, District of Columbia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGovernments in low-income and middle-income countries (LMICs) and official development assistance agencies use a variety of performance measurement and management approaches to improve the performance of healthcare systems. The effectiveness of such approaches is contingent on the extent to which managers and care providers use performance information. To date, major knowledge gaps exist about the contextual factors that contribute, or not, to performance information use by primary healthcare (PHC) decision-makers in LMICs. This study will address three research questions: (1) How do decision-makers use performance information, and for what purposes? (2) What are the contextual factors that influence the use or non-use of performance information? and (3) What are the proximal outcomes reported by PHC decision-makers from performance information use? METHODS AND ANALYSIS: We present the protocol of a theory-driven, qualitative study with a multiple case study design to be conducted in El Salvador, Lebanon and Malawi.Data sources include semi structured in-depth interviews and document review. Interviews will be conducted with approximately 60 respondents including PHC system decision-makers and providers. We follow an interdisciplinary theoretical framework that draws on health policy and systems research, public administration, organisational science and health service research. Data will be analysed using thematic analysis to explore how respondents use performance information or not, and for what purposes as well as barriers and facilitators of use. ETHICS AND DISSEMINATION: The ethical boards of the participating universities approved the protocol presented here. Study results will be disseminated through peer-reviewed journals and global health conferences.

Indexed as

Delivery of Health CareEl SalvadorHumansLebanonMalawiQualitative ResearchHealth policyOrganisation of health servicesPRIMARY CARE

Identifiers

PMID36410829
PMCPMC9680164

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.