Modeling the Determinants of Satisfaction with Health Care Services in Türkiye Using Machine Learning

Cuma Çakmak

doi:10.31067/acusaglik.1866468

Modeling the Determinants of Satisfaction with Health Care Services in Türkiye Using Machine Learning

Abstract

Purpose: Patient satisfaction is a fundamental indicator for evaluating the quality of healthcare services and is of great importance for the sustainability of healthcare systems. Methods: In this study, machine learning methods were used to identify factors affecting individuals' levels of satisfaction with healthcare services and to predict their satisfaction levels. The Turkish Statistical Institute (TÜİK) life satisfaction dataset was used; the data were split into training (70%) and test (30%) sets, and the SMOTE method was applied to address class imbalance. Results: Logistic Regression, SVM, Decision Trees, Random Forest, and Naive Bayes models were tested, and Logistic Regression was determined to be the most suitable model. According to the findings, married individuals with a high level of education and those who are employed are more satisfied. In contrast, hygiene issues, insufficient healthcare personnel, long waiting times, and high insurance costs reduce satisfaction. Conclusion: Ultimately, machine learning approaches are practical for analyzing healthcare satisfaction. Keywords: Patient Satisfaction, Machine Learning, Healthcare Service Quality, Classification, Data Analytics

Keywords

Supporting Institution

None

Ethical Statement

This study does not require ethical committee approval, as it used secondary data. Permission to use the data was obtained from the Turkish Statistical Institute with application number 588938.

Thanks

None

References

1. Birinci S, Guven SC, Ata N, Ulgu MM, Kucuksahin O. Patient satisfaction with health care services in Türkiye: A glimpse from nationwide Ministry of Health database. North Clin Istanb. 2024;11(6). doi:10.14744/nci.2024.84584
2. Batbaatar E, Dorjdagva J, Luvsannyam A, Savino MM, Amenta P. Determinants of patient satisfaction: A systematic review. Perspect Public Health. 2017;137(2):89–101. doi:10.1177/1757913916634136
3. Ferreira DC, Vieira I, Pedro MI, Caldas P, Varela M. Patient satisfaction with healthcare services and the techniques used for its assessment: A systematic literature review and a bibliometric analysis. Healthcare (Basel). 2023;11(5):639. doi:10.3390/healthcare11050639
4. Schmid L, Roidl M, Kirchheim A, Pauly M. Comparing statistical and machine learning methods for time series forecasting in datadriven logistics—A simulation study. Entropy (Basel). 2024;27(1):25. doi:10.3390/e27010025
5. Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380:1347–1358. doi:10.1056/NEJMra1814259
6. Javaid M, Haleem A, Singh RP, Suman R, Rab S. Significance of machine learning in healthcare: Features, pillars and applications. Int J Intell Netw. 2022;3:58–73. doi:10.1016/j.ijin.2022.05.002
7. Çakmak MA, Kurt ME, Çakmak C. Makine öğrenmesi algoritmaları ile COVID-19 hastalarının mortalite risklerinin hesaplanması. Süleyman Demirel Üniv Vizyoner Derg. 2022;13(35):994–1011. doi:10.21076/ vizyoner.1074212
8. Kourou K, Exarchos TP, Exarchos KP, Karamouzis MV, Fotiadis DI. Machine learning applications in cancer prognosis and prediction. Comput Struct Biotechnol J. 2015;13:8–17. doi:10.1016/j. csbj.2014.11.005

9. Obermeyer Z, Emanuel EJ. Predicting the future—Big data, machine learning, and clinical medicine. N Engl J Med. 2016;375:1216–1219. doi:10.1056/NEJMra1606181
10. Oraini B. The effect of artificial intelligence capability on patient satisfaction. Int J Data Netw Sci. 2024;8(3):1429–1436. doi:10.5267/j. ijdns.2024.3.022
11. Chen J. A machine learning approach grounded in empathy theory. J Med Internet Res. 2024;26(4):e11686637. doi:10.2196/11686637
12. Uğurluoğlu Ö, Ürek D, Demir İB. Evaluation of individuals’ satisfaction with health care services in Turkey. Health Policy Technol. 2019;8(1):24–29. doi:10.1016/j.hlpt.2019.02.003
13. Polatlı LÖ. Sağlık hizmetlerinde güncel makine öğrenmesi algoritmaları. DergiPark. 2023. Available from: https://dergipark.org. tr/en/download/article-file/2432612
14. O’Brien RM. A caution regarding rules of thumb for variance inflation factors. Qual Quant. 2007;41(5):673–690. doi:10.1007/ s11135-006-9018-6
15. Mahesh B. Machine learning algorithms – a review. International Journal of Science and Research (IJSR). 2018;7(6):381–386. ISSN: 2319-7064..
16. Raj A, D’Souza R. A review on machine learning algorithms. International Journal of Science and Engineering Development Research (IJRASET). 2019;7(4):792-796. Accessed February 10, 2026
17. Ezugwu AE, Ho YS, Egwuche OS, Ekundayo OS, Van Der Merwe A, Saha AK, Pal J. Classical machine learning: seventy years of algorithmic learning evolution. Data Intelligence. 2024. doi:10.3724/2096-7004. di.2024.0051
18. Cohen G. Age and health status in a patient satisfaction survey. Soc Sci Med. 1996;42(7):1085–1093.
19. Jaipaul CK, Rosenthal GE. Are older patients more satisfied with hospital care than younger patients? J Gen Intern Med. 2003 Jan;18(1):23-30.
20. Tian Y, Wong ELY, Qiu H, Wang H, Cheung AWL, Yeoh EK. Gender differences in healthcare experience: evidence from Hong Kong hospital surveys (2010-2020). Eur J Public Health. 2025 Oct 27;35(Suppl 4)
21. Alhasan MS, Alahmadi IM, Alhilali HF, Alyoubi NM, Alkhoriji NA, Aljazairi AM, Othman BM, Alshehri AM, Alhejaili MO, Alhejaili B, Alanazi OI, Azzam AY, Alhasan AS. Determinants of patient satisfaction among outpatients with chronic illnesses in the region of medina, Saudi Arabia: a cross-sectional study. BMC Health Serv Res. 2025 Jul 14;25(1):953. doi: 10.1186/s12913-025-13116-7. PMID: 40660224; PMCID: PMC12257647.
22. Hall JA, Dornan MC. Patient sociodemographic characteristics as predictors of satisfaction with medical care: A meta-analysis. Soc Sci Med. 1990;30(7):811–818. doi:10.1016/0277-9536(90)90205-7
23. Thi HM, Lee WY, Lin CC. Factors determining patient satisfaction with nursing care in a teaching hospital. J Nurs Res. 2002;10(3):169–178. doi:10.1016/S0277-9536(01)00045-4
24. Paul P, Hakobyan M, Valtonen H. The association between selfperceived health status and satisfaction with healthcare services: Evidence from Armenia. BMC Health Serv Res. 2016;16(1):67. doi:10.1186/s12913-016-1309-6
25. Mosleh SM, Alsereidi AR, Aldhanhani AA, Alnaqbi HM, Alhouti RS, Alshehhi SS. A descriptive study on patient satisfaction with waiting time in emergency departments: Insights from hospitals in the Northern Emirates. Int Emerg Nurs. 2025;78:101564. doi:10.1016/j. ienj.2024.101564
26. Alarcon-Ruiz CA, Heredia P, Taype-Rondan A. Association of waiting and consultation time with patient satisfaction: Secondarydata analysis of a national survey in Peruvian ambulatory care facilities. BMC Health Serv Res. 2019;19(1):439. doi:10.1186/ s12913-019-4288-6
27. Semiz BB, Semiz T, Güneş K. Sağlık kurumlarında algılanan hizmet kalitesinin ve hasta memnuniyetinin ölçülmesine yönelik bir araştırma. Bus Manag Stud Int J. 2023;11(3):1130–1151. doi:10.15295/bmij.v11i3.2289
28. Senić V, Marinković V. Patient care, satisfaction and service quality in health care. Int J Consum Stud. 2013;37(3):312–319. doi:10.1111/j.1470-6431.2012.01132.x
29. Vatica JR, Nur’aini NA, Lubis M. Effect of health service quality toward patients satisfaction. J La Medihealtico. 2021;2(1):63–72. doi:10.37899/journallamedihealtico.v2i1.308
30. Nguyen T, Nguyen H, Dang A. Determinants of patient satisfaction: Lessons from large-scale inpatient interviews in Vietnam. PLoS One. 2020;15(9):e0239306. doi:10.1371/journal.pone.0239306

Details

Primary Language

English

Subjects

Health Care Administration

Journal Section

Research Article

Authors

Cuma Çakmak ^*
0000-0002-4409-9669
Türkiye

Publication Date

April 30, 2026

Submission Date

January 18, 2026

Acceptance Date

March 28, 2026

Published in Issue

Year 2026 Volume: 17 Number: April, May, June 2026

DOI

https://doi.org/10.31067/acusaglik.1866468

IZ

https://izlik.org/JA87TC53GX

Cite

RIS / Bibtex

EndNote

Çakmak C (April 1, 2026) Modeling the Determinants of Satisfaction with Health Care Services in Türkiye Using Machine Learning. Acıbadem Üniversitesi Sağlık Bilimleri Dergisi 17 April, May, June 2026