Evidence map›Paper›PMID 37081227›Full record

ArticleNature medicine2023

A simulation-based comparative effectiveness analysis of policies to improve global maternal health outcomes.

Zachary J Ward, Rifat Atun, Gary King, Brenda Sequeira Dmello, Sue J Goldie

Abstract read
In one paragraph

Article in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

5 authors.

Zachary J WardCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA. zward@hsph.harvard.edu.ORCID http://orcid.org/0000-0002-4007-2207
Rifat AtunDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-1531-5983
Gary KingInstitute for Quantitative Social Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-5327-7631
Brenda Sequeira DmelloMaternal and Newborn Healthcare, Comprehensive Community Based Rehabilitation in Tanzania, Dar es Salaam, Tanzania.ORCID http://orcid.org/0000-0002-1550-248X
Sue J GoldieCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) to less than 70 maternal deaths per 100,000 live births by 2030, with no individual country exceeding 140. However, on current trends the goals are unlikely to be met. We used the empirically calibrated Global Maternal Health microsimulation model, which simulates individual women in 200 countries and territories to evaluate the impact of different interventions and strategies from 2022 to 2030. Although individual interventions yielded fairly small reductions in maternal mortality, integrated strategies were more effective. A strategy to simultaneously increase facility births, improve the availability of clinical services and quality of care at facilities, and improve linkages to care would yield a projected global MMR of 72 (95% uncertainty interval (UI) = 58-87) in 2030. A comprehensive strategy adding family planning and community-based interventions would have an even larger impact, with a projected MMR of 58 (95% UI = 46-70). Although integrated strategies consisting of multiple interventions will probably be needed to achieve substantial reductions in maternal mortality, the relative priority of different interventions varies by setting. Our regional and country-level estimates can help guide priority setting in specific contexts to accelerate improvements in maternal health.

Indexed as

Delivery of Health CareMaternal MortalityComputer SimulationFemaleGlobal HealthHumansOutcome Assessment, Health CarePolicy

Identifiers

PMID37081227
PMCPMC10202805

What OpenQuestion holds

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Registered trials

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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.