Evidence map›Paper›PMID 31139448›Full record

ReviewBMJ global health2019

Health system modelling research: towards a whole-health-system perspective for identifying good value for money investments in health system strengthening.

Stéphane Verguet, Isabelle Feldhaus, Xiaoxiao Jiang Kwete, Anwer Aqil, Rifat Atun, David Bishai, Michele Cecchini, Augusto Afonso Guerra Junior, Mahlet Kifle Habtemariam, Abdulrahman Jbaily and 8 more

Abstract readReview
In one paragraph

Review in BMJ global health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

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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

18 authors.

Stéphane VerguetDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0003-4128-0849
Isabelle FeldhausDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Xiaoxiao Jiang KweteDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Anwer AqilOffice of Health Systems, USAID Bureau for Global Health, Arlington, Virginia, USA.
Rifat AtunDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
David BishaiDepartment of Family and Population Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Michele CecchiniOECD, Paris, France.
Augusto Afonso Guerra JuniorSchool of Pharmacy, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Mahlet Kifle HabtemariamDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Abdulrahman JbailyDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Ozge KaranfilDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Margaret E KrukDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Sebastien HaneuseDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Ole Frithjof NorheimDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Peter C SmithImperial College Business School, London, UK.
Mieraf Taddesse TollaDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Solomon ZewduBill and Melinda Gates Foundation, Global Development, Addis Ababa, Ethiopia.
Jesse BumpDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0003-1014-0456

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global health research has typically focused on single diseases, and most economic evaluation research to date has analysed technical health interventions to identify 'best buys'. New approaches in the conduct of economic evaluations are needed to help policymakers in choosing what may be good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments for health system strengthening (HSS) that tend to be programmatic. We posit that these economic evaluations of HSS interventions will require developing new analytic models of health systems which recognise the dynamic connections between the different components of the health system, characterise the type and interlinks of the system's delivery platforms; and acknowledge the multiple constraints both within and outside the health sector which limit the system's capacity to efficiently attain its objectives. We describe priority health system modelling research areas to conduct economic evaluation of HSS interventions and ultimately identify good value for money investments in HSS.

Indexed as

economic evaluationhealth system modellinghealth system strengthening

Identifiers

PMID31139448
PMCPMC6509611

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.