Evidence map›Paper›PMID 42730311›Full record

ArticleInternational journal of women's health2026

Analysis of Key Driving Factors for Inpatient Service Experience in Obstetrics and Gynecology Specialized Hospitals Based on Random Forest Algorithm.

Li Binxia, Yin Lina, Lv Xingxing, Yuan Yufan

Abstract read
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Article in International journal of women's health, 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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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Li Binxia *Department of Nursing, The Fourth Hospital of Shijiazhuang/Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, People's Republic of China.ORCID 0009-0004-4481-5831
Yin Lina *Department of Nursing, The Fourth Hospital of Shijiazhuang/Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, People's Republic of China.
Lv XingxingDepartment of Obstetrical, The Fourth Hospital of Shijiazhuang/Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, People's Republic of China.
Yuan YufanDepartment of Nursing, The Fourth Hospital of Shijiazhuang/Shijiazhuang Obstetrics and Gynecology Hospital, Shijiazhuang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the key drivers influencing the service experience of inpatients in obstetrics and gynecology specialty hospitals, thereby providing a reference for further enhancing the inpatient service experience. Methods: From April to October 2025, a questionnaire survey on inpatient service experience was conducted among 405 inpatients at a tertiary Grade A obstetrics and gynecology specialty hospital. Using the Sklearn package in Python 3.13.3 software, the random forest algorithm was applied to calculate the importance of each questionnaire item. A data-driven importance matrix was constructed based on patients' evaluation scores to conduct key driver analysis. The random forest model exhibited favorable predictive performance (R Results: A total of 365 valid questionnaires were collected, with an effective response rate of 90.12%. The overall score of the inpatient service experience was (3.84 ± 0.18). Through IPA, the 20 experience elements were categorized into four quadrants: 3 items in the urgent improvement zone (pain management, discharge health guidance, meal quality), 4 items in the key strength zone, 2 items in the secondary improvement zone, and 11 items in the maintenance zone. Conclusion: Admission/discharge procedures and information, pain management, and meal quality are key drivers of the service experience in obstetrics and gynecology specialty hospitals. The driving logic of patient experience can be summarized as a "three-tier pyramid" model: environmental cleanliness forms the foundation, doctor-patient communication constitutes the middle layer, and pain management, discharge guidance, and meal quality represent the apex.

Indexed as

critical factorshospital managementimportance-performance analysisinpatientspatient experienceservice experience

Identifiers

PMID42730311
PMCPMC13564465

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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.