Previously submitted to: Interactive Journal of Medical Research (no longer under consideration since Jul 10, 2026)
Date Submitted: Jul 3, 2026
Open Peer Review Period: Jul 6, 2026 - Jul 10, 2026
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Beyond Demographics: Service Quality–Based Patient Segmentation and Its Links to Satisfaction and Behavioural Intentions in Urban Hospital Care
ABSTRACT
Background:
To deliver effective healthcare services, hospitals need to understand how patients experience service delivery in a holistic way apart from clinical treatment part. Hospitals generally use demographic characteristics of patients like age, gender, education, occupation etc. to design and deliver healthcare services. However, this demographic segmentation may not fully capture how patients perceive care. Patients can also be segmented and understood more meaningfully segmenting based on how they perceive healthcare service quality. It is interesting to study how these new patient segments or profiles differ in satisfaction and behavioural intentions with healthcare service by hospitals.
Objective:
The main objective of this study is to identify perceived service quality based patient segments and study how these segments differ in patient satisfaction and behavioural intention with respect to hospitals’ healthcare services.
Methods:
Cross sectional online survey was conducted in May 2026. This survey was conducted on health care users in Gujarat, India. Questionnaire was circulated in English and Gujarati languages through Google Forms. Total 464 responses were received. 402 respondents who visited hospital in last 6 months were included in further analysis for this study. Patient segments were identified from twenty two perceived hospital service quality indicators. These indicators included five dimensions of service quality namely tangibles, reliability, responsiveness, assurance and empathy. For inferential statistics, hierarchical cluster analysis was used first to explore cluster solutions and it was then followed by k-means clustering for final cluster solutions. Cluster/segment differences were measured using ANOVA and post hoc tests. Also, demographic differences were tested for comparison with cluster based segmentation.
Results:
A five-cluster solution was retained for managerial usefulness. Analysis classified all 402 respondents into five patient profiles. These profiles were; 1) operationally satisfied but relationally dissatisfied patients (73/402, 18.2%), 2) functionally mixed patients (80/402, 19.9%), 3) highly satisfied patients (59/402, 14.7%), 4) relationally positive but system doubtful patients (88/402, 21.9%) and 5) average patients with limited emotional connection (102/402, 25.4%). Clusters differed significantly with respect to patient satisfaction and behavioural intention. However, demographic variables showed weak or non-significant differences for satisfaction and behavioural intention. Results indicated that patient heterogeneity is better explained through service-quality profiles than through demographic categories.
Conclusions:
Service quality based patient segmentation identified meaningful and actionable patient profiles. These segments also differed in satisfaction and behavioral intention. Results suggest that hospitals can improve patient experience management by targeted management for perceived service deficits rather than relying only on demographics.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.