Evidence map›Paper›PMID 32680527›Full record

ReviewHealth research policy and systems2020

Measuring the resilience of health systems in low- and middle-income countries: a focus on community resilience.

Sudip Bhandari, Olakunle Alonge

Abstract readReview
In one paragraph

Review in Health research policy and systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. How Is Health System Resilience Being Assessed? A Scoping Review.International journal of health policy and management · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sudip BhandariDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, United States of America.
Olakunle AlongeDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, United States of America. oalonge1@jhu.edu.ORCID http://orcid.org/0000-0001-7642-2806

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The concept of community resilience has gained considerable attention in the global health discussions since the Ebola outbreak of West Africa in 2014-2015. However, there are no measurement models to quantify community resilience. Without measurement models, it is unclear how to test strategies for building community resilience or to describe their likely intended and unintended results and their impact on health outcomes. We propose a measurement model for community resilience with relevant constructs and indicators to measure these constructs. We conducted a scoping review, systematically searching, screening and selecting relevant articles from two bibliographic databases (PUBMED and Google Scholar) for literature using search terms such as "resilience", "community resilience" and "health systems resilience". We screened 500 papers, then completed a full text review of 112 identified as relevant based on their title and abstract. A total of 27 papers and reports were retained for analysis. We then aggregated and synthesised the various definitions of community resilience and the frameworks for understanding these definitions. We identified key constructs from these frameworks and organised these constructs into domains and sub-domains. We proposed indicators to capture aspects of these domains and sub-domains and operationalised these indicators as a measurement model for quantifying community resilience in health systems. We propose a model with 20 indicators to assess community resilience. These indicators tap into various constructs from different theoretical frameworks of community resilience and are useful for assessing the level of knowledge, financial resources, and human, social and physical capital that are needed (or lacking) to respond to any types of shock, including health shock at the community level. This is an initial attempt to describe a multilevel measurement model for quantifying community resilience. This model will help to guide the development and testing of strategies for strengthening community resilience and will require further work to assess its relevance, reliability and validity in different LMIC settings.

Indexed as

Developing CountriesHemorrhagic Fever, EbolaAfrica, WesternDelivery of Health CareHumansReproducibility of Resultscommunity resiliencehealth systemsmeasurement modelvulnerability

Identifiers

PMID32680527
PMCPMC7368738

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.