Evidence map›Paper›PMID 39334127›Full record

ArticleHuman resources for health2024

Health workforce needs in Malawi: analysis of the Thanzi La Onse integrated epidemiological model of care.

Bingling She, Tara D Mangal, Margaret L Prust, Stephanie Heung, Martin Chalkley, Tim Colbourn, Joseph H Collins, Matthew M Graham, Britta Jewell, Purava Joshi and 12 more

Abstract read
In one paragraph

Article in Human resources for health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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

22 authors.

Bingling SheDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK. b.she@imperial.ac.uk.ORCID 0000-0001-5976-8987
Tara D MangalDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Margaret L PrustClinton Health Access Initiative, Inc., Boston, USA.
Stephanie HeungClinton Health Access Initiative, Inc., Lilongwe, Malawi.
Martin ChalkleyCentre for Health Economics, University of York, York, UK.
Tim ColbournInstitute for Global Health, University College London, London, UK.
Joseph H CollinsInstitute for Global Health, University College London, London, UK.
Matthew M GrahamUCL Centre for Advanced Research, University College London, London, UK.
Britta JewellDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Purava JoshiClinton Health Access Initiative, Inc., Lilongwe, Malawi.
Ines Li LinInstitute for Global Health, University College London, London, UK.
Emmanuel MnjoweCollege of Medicine, University of Malawi, Lilongwe, Malawi.
Sakshi MohanCentre for Health Economics, University of York, York, UK.
Margherita MolaroDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Andrew N PhillipsInstitute for Global Health, University College London, London, UK.
Paul RevillCentre for Health Economics, University of York, York, UK.
Robert Manning SmithInstitute for Global Health, University College London, London, UK.
Asif U TamuriDepartment of Genetics, Evolution and Environment, University College London, London, UK.
Pakwanja D TweaDepartment of Planning and Policy Development, Ministry of Health, Lilongwe, Malawi.
Gerald ManthaluDepartment of Planning and Policy Development, Ministry of Health, Lilongwe, Malawi.
Joseph Mfutso-BengoSchool of Public Health-College of Medicine, University of Malawi, Blantyre, Malawi.
Timothy B HallettDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.

Funding

Medical Research Council MR/R015600/1Medical Research Council MR/X020258/1Medical Research Council UKMRC Centre for Global Infectious Disease Analysis MR/R015600/1Wellcome TrustWellcome Trust 223120/Z/21/Z
6 · The paper itself

Abstract

backgroundTo make the best use of health resources, it is crucial to understand the healthcare needs of a population-including how needs will evolve and respond to changing epidemiological context and patient behaviour-and how this compares to the capabilities to deliver healthcare with the existing workforce. Existing approaches to planning either rely on using observed healthcare demand from a fixed historical period or using models to estimate healthcare needs within a narrow domain (e.g., a specific disease area or health programme). A new data-grounded modelling method is proposed by which healthcare needs and the capabilities of the healthcare workforce can be compared and analysed under a range of scenarios: in particular, when there is much greater propensity for healthcare seeking.

methodsA model representation of the healthcare workforce, one that formalises how the time of the different cadres is drawn into the provision of units of healthcare, was integrated with an individual-based epidemiological model-the Thanzi La Onse model-that represents mechanistically the development of disease and ill-health and patients' healthcare seeking behaviour. The model was applied in Malawi using routinely available data and the estimates of the volume of health service delivered were tested against officially recorded data. Model estimates of the "time needed" and "time available" for each cadre were compared under different assumptions for whether vacant (or established) posts are filled and healthcare seeking behaviour.

resultsThe model estimates of volume of each type of service delivered were in good agreement with the available data. The "time needed" for the healthcare workforce greatly exceeded the "time available" (overall by 1.82-fold), especially for pharmacists (6.37-fold) and clinicians (2.83-fold). This discrepancy would be largely mitigated if all vacant posts were filled, but the large discrepancy would remain for pharmacists (2.49-fold). However, if all of those becoming ill did seek care immediately, the "time needed" would increase dramatically and exceed "time supply" (2.11-fold for nurses and midwives, 5.60-fold for clinicians, 9.98-fold for pharmacists) even when there were no vacant positions.

conclusionsThe results suggest that services are being delivered in less time on average than they should be, or that healthcare workers are working more time than contracted, or a combination of the two. Moreover, the analysis shows that the healthcare system could become overwhelmed if patients were more likely to seek care. It is not yet known what the health consequences of such changes would be but this new model provides-for the first time-a means to examine such questions.

Indexed as

Health Services Needs and DemandHealth WorkforceAdultDelivery of Health CareFemaleHealth PersonnelHumansMalawiMaleModels, TheoreticalNursesPatient Acceptance of Health CareHealth care needsHealthcare workforceHealth servicesHealth system interactionsModel design

Identifiers

PMID39334127
PMCPMC11437829

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.