Evidence map›Paper›PMID 42286116›Full record

ArticleScientific reports2026

A collaboration mechanism for medical insurance settlement based on isolation forest and Fleiss kappa smart contract.

Chuanjia Yao, Zhihui Jiang, Xufeng Su, Xinchun Ma, Li Li, Siya Zhao, Ye Zhu, Hongyu Nie, Yi Deng, Weida Shi

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

10 authors.

Chuanjia Yao *School of Economics and Management, Tarim University, Alaer, 843300, China.
Zhihui Jiang *School of Economics and Management, Tarim University, Alaer, 843300, China.
Xufeng SuSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Xinchun MaSchool of Economics and Management, Tarim University, Alaer, 843300, China. 1534897220@qq.com.
Li LiSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Siya ZhaoSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Ye ZhuSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Hongyu NieSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Yi DengSchool of Economics and Management, Tarim University, Alaer, 843300, China.
Weida ShiSchool of Economics and Management, Tarim University, Alaer, 843300, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The management of medical insurance funds is pivotal to the development of medical consortia. These funds serve as the operational lifeline of medical consortia and constitute critical public resources essential for public welfare. Medical expense settlement involves multiple stakeholders, including patients, tiered healthcare institutions, and insurance administrative agencies. However, disputes frequently arise between medical insurance authorities and hospitals regarding expense legitimacy due to information asymmetry and interpretative discrepancies. Such conflicts impede smoothness of payment mechanism, thereby undermining consortium operations and inter-institutional collaboration. To address these challenges, this study proposes a blockchain-based framework integrating medical expense investigation with insurance settlement. The system employs two core components: Anomaly detection via the Isolation Forest (IF) algorithm to identify potentially irregular expenses. Consensus-driven adjudication using Fleiss Kappa-based smart contracts facilitated by an anonymous panel of medical experts. This design enhances coordination between expense oversight and settlement processes, thus streamlining dispute resolution for medical expense anomalies and improving the scientific governance of insurance funds. Experimentally, the statistical validity demonstrated for unsupervised anomaly detection of IF and potential engineering applicability indicated in the analysis of healthcare cost. The healthcare consortium blockchain based on a Delegated Proof-of-Stake (DPoS) consensus mechanism and smart contract batch processing achieved a peak throughput of 229.64 transactions per second (TPS) and reduced transaction costs by up to 3,095 gwei. This demonstrates scalability for real-world medical insurance collaborative settlement systems.

Indexed as

ContractsInsurance, HealthAlgorithmsBlockchainHealth Care CostsHumansFleiss kappaIsolation forestMedical expensesMedical insurance fundSmart contract

Identifiers

PMID42286116
PMCPMC13518787

What OpenQuestion holds

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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.