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Record W4392823734 · doi:10.2196/53898

Practice Standards in International Medical Departments of Public Academic Hospitals in China: Cross-Sectional Study

2024· article· en· W4392823734 on OpenAlexvenueno aff
Yaxu Zhou, Ying Zhou, Di Xu, J. Min, Yu Du, Qi Duan, Bao Wen, Yingying Sun, Huiqin Xi, Chunming Wang, Evelyne Bischof

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
FundersDuke Kunshan UniversityShanghai Jiao Tong UniversityNational Natural Science Foundation of China
KeywordsCross-sectional studyChinaFamily medicineMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Improving health care in cities with a diverse, international population is crucial for ensuring health equity, particularly for foreigners facing challenges due to cultural and language barriers. This situation is especially relevant in China, a major destination for expatriates and travelers, where optimizing health care services and incorporating international standards in the public sector are vital. Achieving this involves understanding the operational details, cultural and linguistic nuances, and advancing medical digitalization. A strategic approach focusing on cultural competence and awareness of health care systems is essential for effectively navigating health care for foreigners and expatriates in China. OBJECTIVE: The aim of this study was to perform an in-depth analysis of the subjective and objective experiences of local and international patients in public hospitals in China to provide a basis for enhancing the medical experience of all patients. METHODS: A structured questionnaire was provided to patients at an international outpatient service of a top-tier university hospital in China. Qualitative analysis of the survey responses was performed to methodically categorize and analyze medical treatment, focusing on patient demand and satisfaction across four main category elements ("high demand, high satisfaction"; "high demand, low satisfaction"; "low demand, high satisfaction"; and "low demand, low satisfaction"), enabling a detailed cross-sectional analysis to identify areas for improvement. RESULTS: Elements falling under "high demand, high satisfaction" for both Chinese and international patients were primarily in the realms of medical quality and treatment processes. In contrast, elements identified as "high demand, low satisfaction" were significantly different between the two patient groups. CONCLUSIONS: The findings highlight the importance of systematic, objective research in advancing the quality of international health care services within China's leading academic medical centers. Key to this improvement is rigorous quality control involving both patients and providers. This study highlights the necessity of certifying such centers and emphasizes the role of digital platforms in disseminating information about medical services. This strategy is expected to cater to diverse patient needs, enhancing the overall patient experience. Furthermore, by developing comprehensive diagnosis and treatment services and highlighting the superior quality and costs associated with international health care, these efforts aim to foster a sense of belonging among international patients and increase the attractiveness of China's medical services for this demographic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.159
GPT teacher head0.643
Teacher spread0.485 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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