Evidence map›Paper›PMID 39882493›Full record

ArticleBulletin of the World Health Organization2025

Digitalization of health care in low- and middle-income countries.

Dominique J Monlezun, Lillian Omutoko, Patience Oduor, Donald Kokonya, John Rayel, Claudia Sotomayor, Maria Ines Girault, María Elizabeth De Los Ríos Uriarte, Oleg Sinyavskiy, Timothy Aksamit and 3 more

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 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

13 authors.

Dominique J MonlezunDivision of Hospital Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN55905, United States of America (USA).
Lillian OmutokoDepartment of Educational Management, Policy and Curriculum Studies, University of Nairobi, Nairobi, Kenya.
Patience OduorClinical Trials Unit, University of Global Health Equity, Kigali, Rwanda.
Donald KokonyaSchool of Medicine, Masinde Muliro University, Kakamega, Kenya.
John RayelCollege of Science, Bicol University, Legazpi City, Philippines.
Claudia SotomayorPellegrino Center for Clinical Bioethics, Georgetown University, WashingtonDC, USA.
Maria Ines GiraultFaculty of Bioethics, Universidad Anahuac México, Mexico City, Mexico.
María Elizabeth De Los Ríos UriarteFaculty of Bioethics, Universidad Anahuac México, Mexico City, Mexico.
Oleg SinyavskiyDepartment of Public Health, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
Timothy AksamitDivision of Pulmonary Medicine and Critical Care Medicine, Mayo Clinic, Rochester, USA.
Sagar B DuganiDivision of Hospital Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN55905, United States of America (USA).
Alberto GarciaSchool of Bioethics, Ateneo Pontificio Regina Apostolorum, Rome, Italy.
Colleen GallagherFaculty of Bioethics, Universidad Anahuac México, Mexico City, Mexico.

Funding

Rural Patient Risks and Exposures for Diabetes ConTrol (Rural PREDICT)K23MD016230 · NIMHD · MAYO CLINIC ROCHESTER · PI DUGANI, CHANDRASAGAR · 2021 to 2025
$763k
NIMHD NIH HHS K23 MD016230
6 · The paper itself

Abstract

The rising incidence of noncommunicable diseases, combined with the costs of mitigating climate change, sovereign debt and regional conflicts, is undermining global health security and threatening progress towards achieving the sustainable development goals of the United Nations. The negative impact of these polycrises is disproportionately borne by low- and middle-income countries, which have the highest disease burden and lowest health-care spending. Health digitalization is emerging as a promising countermeasure, accelerated by artificial intelligence (AI) software and quantum computing hardware. We provide a multisector critical analysis of the three key enablers - governance, infrastructure and security - of the responsible AI-enabled digitalization for safe, affordable, equitable and sustainable health-care systems in low- and middle-income countries. We consider leading use cases in public-private partnerships, democratized sovereign AI and embedded human security. Our analysis proposes that these use cases demonstrate how digital AI-accelerated global health may be advanced as human-centred managed strategic competition. We conducted our analysis through an inclusive range of theoretical perspectives and practical experience spanning academia, industry and practice across the world. We provide recommendations for the responsible management of the key enablers to accelerate global health for all. We anticipate that this paper will be useful for public health decision-makers, both in low- and middle-income countries leading local health digitalization, and in high-income countries supporting this transaction through their technologies, funding and knowledge exchange.

Indexed as

Artificial IntelligenceDelivery of Health CareDeveloping CountriesDigital TechnologyGlobal HealthHumansPublic-Private Sector Partnerships

Identifiers

PMID39882493
PMCPMC11774219

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.