Evidence map›Paper›PMID 42516116›Full record

ArticleBulletin of the World Health Organization2026

Third-party governance and artificial intelligence for diabetes management in primary health care, China.

Wenxi Tang, Qian Peng, Minlin Li, Na Zheng, Tao Zhang, Yipeng Guo, Xing Lin Feng

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Wenxi TangDepartment of Public Administration, China Pharmaceutical University, Nanjing, China.
Qian PengDepartment of Public Administration, China Pharmaceutical University, Nanjing, China.
Minlin LiDepartment of Public Administration, China Pharmaceutical University, Nanjing, China.
Na ZhengDepartment of Public Administration, China Pharmaceutical University, Nanjing, China.
Tao ZhangTianjin Medical Insurance Bureau, Tianjin, China.
Yipeng GuoTianjin Health Commission, Tianjin, China.
Xing Lin FengDepartment of Health Policy and Management, Peking University School of Public Health, 38 Xueyuan Road, Beijing, 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Problem: Fragmented primary health care in China fails to tackle the growing burden of noncommunicable diseases. Despite substantial investment, fewer than half of patients with diabetes achieve glycaemic control. Approach: Tianjin's 2020-2023 reform established a public-private partnership model where WeDoctor managed community health centres under a capitation scheme. This strategy integrated: (i) monthly prepaid capitation covering all diabetes-related outpatient services; (ii) claims auditing and clinical decision support using artificial intelligence (AI); (iii) dedicated health managers for care coordination; and (iv) redesigned services incorporating complication screening and digital medication management. A pilot study including 494 945 patients with diabetes compared three care models from 2022 to 2023: WeDoctor-community health centre care, hospital care and usual care. Local setting: Tianjin city serves 15 million residents through 177 hospitals and 266 community health centres. Chronic disease management is fragmented: the Health Commission regulates care standards, while the Insurance Bureau controls funding. Relevant changes: Visits for diabetes at WeDoctor health centres increased 2.6% (0.7/26.6) but declined 10.6% (-3.8/35.7) for hospital-based care and 2.3% (-0.8/34.1) for usual care. All groups reduced outpatient expenditure. The WeDoctor model generated a 37.62 million United States dollars (US$) surplus, boosted health centre diabetes revenue by 65% (US$ 154 577/237 805) and raised physician annual salaries by 30% (US$ 5172/17 241). More than three quarters of patients expressed satisfaction with and trust in the WeDoctor model. Lessons learnt: Integrating capitation financing with third-party governance and AI support can strengthen primary health care, contain costs and enhance patient-centred care.

Indexed as

Artificial IntelligenceDiabetes MellitusPrimary Health CareCapitation FeeChinaDigital HealthHumansPilot ProjectsPublic-Private Sector Partnerships

Identifiers

PMID42516116
PMCPMC13404216

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.