Evidence map›Paper›PMID 41341012›Full record

ArticlePatient preference and adherence2025

Exploring Patient Satisfaction and Determinants in VIP Outpatient: A SERVQUAL-Based Latent Class Analysis.

Huilin Wang, Hao Wang, Sinan Guan, Jing Li

Abstract read
In one paragraph

Article in Patient preference and adherence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Huilin WangOutpatient Department of Peking University First Hospital, Beijing, People's Republic of China.
Hao WangOutpatient Department of Peking University First Hospital, Beijing, People's Republic of China.
Sinan GuanSchool of Nursing, Peking University, Beijing, People's Republic of China.
Jing LiOutpatient Department of Peking University First Hospital, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To address the diverse needs of patients at different levels, VIP (Very Important Person) outpatient services function as a personalized approach and are of significant importance in the healthcare system. Additionally, patient satisfaction serves as a critical tool for understanding and improving the quality of healthcare services. Therefore, this study aimed to classify VIP outpatients based on satisfaction levels and identified its determinants, hypothesizing that distinct satisfaction segmentations exist and are influenced by several factors. Methods: A total of 4068 patients who attended the VIP outpatient at a tertiary hospital were enrolled between June and July 2025. The SERVQUAL model was used in this study. Descriptive statistical analyses were conducted and quantitative data were gathered using a 5-point Likert scale tailored to assess patient satisfaction. Latent Class Analysis (LCA) was used to delineate heterogeneous satisfaction groups, while a chi-square test and binary logistic regression were employed to investigate satisfaction levels and potential influencing factors. Results: Two latent classes were identified using Mplus 8.4: the overall high satisfaction group (73.1%) and the high medical care-low support service group (26.9%). All Conclusion: For non-local patients registered as outpatients with VIP, priority should be given to addressing their core clinical needs and strengthening doctor-patient interactions. Furthermore, measures such as implementing a cap on registrations and assigning doctor assistants can be introduced to reduce waiting times and extend the length of communication.

Indexed as

latent class analysispatient satisfactionSERVQUAL modelVIP outpatient

Identifiers

PMID41341012
PMCPMC12672155

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