Evidence map›Paper›PMID 35090474›Full record

ArticleHuman resources for health2022

Applying WHO COVID-19 workforce estimate tools remotely in an African context: a case report from Mali and Kenya.

Pamela A McQuide, Amy Finnegan, Katherine M Terry, Andrew Brown, Cheick Oumar Toure, Jeanne Tessougue, Ibrahim Cisse, Mathew Kariuki Thuku, Janet Muriuki, Mary Ochola and 3 more

Abstract readCase Reports
In one paragraph

Article in Human resources for health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Pamela A McQuideIntraHealth International, Chapel Hill, NC, USA.
Amy FinneganIntraHealth International, Chapel Hill, NC, USA.
Katherine M TerryIntraHealth International, Chapel Hill, NC, USA.
Andrew BrownIntraHealth International, Chapel Hill, NC, USA. abrown@intrahealth.org.ORCID 0000-0002-7256-5997
Cheick Oumar ToureIntraHealth International, Bamako, Mali.
Jeanne TessougueIntraHealth International, Bamako, Mali.
Ibrahim CisseIntraHealth International, Bamako, Mali.
Mathew Kariuki ThukuIntraHealth International, Nairobi, Kenya.
Janet MuriukiIntraHealth International, Nairobi, Kenya.
Mary OcholaCoast General Teaching and Referral Hospital, County Government of Mombasa, Mombasa, Kenya.
Julius OgatoMinistry of Health, Nairobi, Kenya.
Etienne CoulibalyMinistry of Health, Bamako, Mali.
Toure Djeneba TogoraMinistry of Health, Bamako, Mali.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has increased the burden on health systems, particularly in low- and middle-income countries, where health systems already struggle. To meet health workforce planning needs during the pandemic, IntraHealth International used two tools created by the World Health Organization (WHO) Regional Office for Europe. The Health Workforce Estimator (HWFE) allows the estimation of the quantity of health workers needed to treat patients during a surge, and the Adaptt Surge Planning Support Tool helps to predict the timing of a surge in cases and the number of health workers and beds needed for predicted caseload. These tools were adapted to fit the African context in a rapid implementation over 5 weeks in one region in Mali and one region in Kenya with the objective to test the feasibility of adapting these tools, which use a Workload Indicators of Staffing Need (WISN)-inspired human resources management methodology, to obtain daily and surge projections of COVID-19 human resources for health needs. CASE PRESENTATION: Using a remote team in the US and in-country teams in Mali and Kenya, IntraHealth enacted a phased plan to gather stakeholder support, collect data related to health systems and COVID-19 cases, populate data into the tools, verify modeled results with results on the ground, enact policy measures to meet projected needs, and conduct national training workshops for the ministries of health.

conclusionsThis phased implementation in Mali and Kenya demonstrated that the WISN approach applied to the Health Workforce Estimator and Adaptt tools can be readily adapted to the local context for African countries to rapidly estimate the number of health workers and beds needed to respond to the predicted COVID-19 pandemic caseload. The results may also be used to give a proxy estimate for needed health supplies-e.g., oxygen, medications, and ventilators. Challenges included accurate and timely data collection and updating data. The success of the pilot can be attributed to the adapted WHO tools, the team composition in both countries, access to human resources data, and early support of the ministries of health, with the expectation that this methodology can be applied to other country contexts.

Indexed as

COVID-19HumansKenyaMaliPandemicsSARS-CoV-2WorkforceWorld Health OrganizationCOVID-19Health workforceKenyaMaliWISNWorkload modelling

Identifiers

PMID35090474
PMCPMC8795299

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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.