Evidence map›Paper›PMID 40230965›Full record

ReviewOxford open digital health2024

Exploring the effects of digital technologies in health financing for universal health coverage: a synthesis of country experiences and lessons.

Maarten Oranje, Inke Mathauer

Abstract readReview
In one paragraph

Review in Oxford open digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  5. Review
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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

2 authors.

Maarten OranjeWHO Consultant, Department of Health Financing and Economics, World Health Organization, 1211 Geneva, Switzerland.
Inke MathauerDepartment of Health Financing and Economics, World Health Organization, 1211 Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

The use of digital technologies (DTs) for health financing receives increased attention in policy, practice and research. However, not much robust evidence exists on their effects on the intermediate and final universal health coverage objectives. This paper seeks to contribute to evidence gathering, by synthesizing the findings from nine country case studies which covered diverse applications of DTs and identified their effects on health financing and universal health coverage objectives. This paper also draws on review papers on the use of DTs for health financing. Our synthesis reveals that DTs can support and simplify health financing tasks and thus contribute to enhanced efficiency and transparency and more equitable resource distribution. If well designed, DTs can help overcome challenges inherent in paper-based data systems and enable otherwise hardly implementable policy options, especially options that rely on near real-time exchange of data. Yet, the studies also point to various risks. Caution is for instance required when the use of DTs enhances inequities between population groups due to various digital divides. The findings point to a number of policy orientations. There is need to include the application of DTs for health financing in national digital health strategies and to develop health financing specific guidance and regulation. This is for instance necessary to avoid that DTs negatively affect financial protection. Clear stipulations related to equity will serve to ensure that positive effects accrue to vulnerable population groups. The future research agenda calls for more and methodologically robust evidence generation with a clear universal health coverage orientation.

Indexed as

digital technologieshealth financinghealth insurancemachine learningpoolingpurchasingrevenue raisinguniversal health coverage

Identifiers

PMID40230965
PMCPMC11932407

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.