Evidence map›Paper›PMID 37670832›Full record

ArticleFrontiers in public health2023

Does the disclosure of medical insurance information affect patients' willingness to adopt the diagnosis related groups system.

Zhenni Shi, Qilin Zhang, Xiaofeng Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 8% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

3 authors at 2 institutions in 1 country.

Zhenni ShiSchool of Political Science and Public Management, Wuhan University, Wuhan, China.
Qilin ZhangSchool of Political Science and Public Management, Wuhan University, Wuhan, China.
Xiaofeng WangCollege of Management, Shenzhen University, Shenzhen, China.
Wuhan University · CNShenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Medical insurance information disclosure is not only a direct way for the public to understand and master social insurance information and resource use benefits, but also an important way for the public to participate in medical service governance and supervision. Some studies have shown that information disclosure can significantly reduce the risk perception of user groups, strengthen their trust and reduce the negative impact of information asymmetry. Methods: Based on risk perception and trust perception theories, this paper focuses on the mechanisms influencing patients' attitudes in the process of implementing a Diagnosis Related Groups payment system. Using medical insurance information disclosure from a governance perspective as the research object, the impact of medical insurance information disclosure on patients' willingness to adopt the Diagnosis Related Groups payment system was analyzed by means of a questionnaire survey, Data analysis and hypothesis testing Results: It was found that medical insurance information disclosure had a significant positive effect on patients' trust perceptions and a significant negative effect on patients' risk perceptions. The more comprehensive information patients received, the stronger their trust and the lower their perceived risk. Discussion: This paper conducts an empirical study from patients' perspective, broadens the scope of research on medical insurance Diagnosis related groups, enriches the application of risk perception and trust perception theories in the medical field, and provides management suggestions for medical institutions in the management of medical insurance information disclosure.

Indexed as

DisclosureInsuranceData AnalysisDiagnosis-Related GroupsHumansPatientsDRGmedical insurance informationpatients’ willingnessrisk perceptiontrust perception

Identifiers

PMID37670832
PMCPMC10475549
OpenAlexW4386030902

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.