Optimum modeling of patient satisfaction with the doctor based on machine learning methods
Subject Areas : General- شادمهر 1 , Zainabolhoda Heshmati 2 , Fatemeh saghafi 3 * , Hadi Veisi 4
1 -
2 -
3 - Associate Prof. of University of Tehran
4 -
Keywords:
Abstract :
The patient-centered approach in the field of health has recently been proposed in the field of the medical system of our country, but until now there is no published scientific research on the factors of patient satisfaction with doctors. The present article aims to cover the stated gap with a scientific evaluation based on the real information obtained from the field study. A questionnaire was designed for the health sector and was approved by the opinion of experts. In order to get the opinions of patients, a questionnaire was distributed among 500 people who underwent rhinoplasty in Tehran, and 395 questionnaires were collected. Three methods of decision tree, support vector machine and neural networks were used for data analysis. The analysis of the results according to the accuracy criteria showed that the most efficient method, in priority, the importance of the factors affecting the patient's satisfaction; Neural network method. The results of the analysis with this method indicate that the most effective feature in the patient's satisfaction with the doctor is the information that the patient expects the doctor to provide. The results of ranking factors in comparison with other studies that only used statistical methods for analysis showed that the results were relatively similar and confirmed each other. But the strengths of the neural network method in modeling is the strength of this method compared to the mentioned studies.
1. Deng, W. J., Chen, W. C., & Pei, W. Back-propagation neural network based importance–performance analysis for determining critical service attributes. Expert Systems with Applications, 2008, 34(2), 1115-1125.
2. Seibold, D. R., Cantrill, J. G., & Meyers, R. A. Communication and interpersonal influence. Handbook of interpersonal communication, 1985, 551-611.
3. Shannon, C. E., & Weaver, W. The mathematical theory of communication (Urbana, IL. University of Illinois Press, 1949.
4. Myers, G. The social construction of two biologists' proposals. Written Communication, 1985, 2(3), 219-245.
5. Barnlund, D. C. Communication: The context of change. Basic readings in communication theory, 2008, 6-25.
6. Loewy, E. H., & Loewy, R. S. (2004). Textbook of healthcare ethics. Springer. New York, 96-105.
7. Ganesh, K. Patient-doctor relationship: Changing perspectives and medical litigation. Indian journal of urology: IJU: journal of the Urological Society of India, 2009, 25(3), 356.
8. Silverman, J., Kurtz, S. M., Draper, J., van Dalen, J., & Platt, F. W. Skills for communicating with patients. Oxford, UK: Radcliffe Pub, 2005.
9. Drossman, D. A. David Sun Lecture: Helping Your Patient by Helping Yourself—How to Improve the Patient–Physician Relationship by Optimizing Communication Skills. The American journal of gastroenterology, 2013.
10. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. A conceptual model of service quality and its implications for future research. The Journal of Marketing, 1985, 41-50.
11. Thomas, L. H., & Bond, S. Measuring patients' satisfaction with nursing: 1990–1994. Journal of Advanced Nursing, 1996, 23(4), 747-756.
12. Parasuraman, A., Zeithaml, V. A., & Berry, L.L. Servqual. Journal of retailing,1988, 64(1), 12-40.
13. Najafi, S., Saati, S., Kazem Bighami, M., & Abdi, F. How do customers evaluate hotel service quality? An empirical study in Tehran hotels.Management Science Letters, 2013, 3(12), 3019-3030.
14. Babakus, E., & Mangold, W. G. Adapting the SERVQUAL scale to hospital services: an empirical investigation. Health services research, 1992, 26(6), 767.
15. Zifko-Baliga, G. M., & Krampf, R. F. Managing perceptions of hospital quality. Negative emotional evaluations can undermine even the best clinical quality. Marketing Health Services, 1997, 17(1), 28-35.
16. Tucker, J. L., & Adams, S. R. Incorporating patients’ assessments of satisfaction and quality: an integrative model of patients’ evaluations of their care. Managing Service Quality, 2001, 11(4), 272-287.
17. Sohail, MS. Service quality in hospitals: more favorable than you might think. Managing Service Quality, 2003, 13(3), 197-206
18. Elleuch, A. Patient satisfaction in Japan. International Journal of Health Care Quality Assurance, 2008, 21(7), 692-705.
19. Behara, R. S., Fisher, W. W., & Lemmink, J. G. Modelling and evaluating service quality measurement using neural networks. International journal of operations & production management, 2002, 22(10), 1162-1185.
20. Shih, Y. Y., & Fang, K. Customer defections analysis: an examination of online bookstores. The TQM Magazine, 2005, 17(5), 425-439.
21. McKinley, R. K., & Roberts, C. Patient satisfaction with out of hour’s primary medical care. Quality in Health Care, 2001, 10(1), 23-28.
22. Harazi, M. A., & Askari, J. Assessment of the most important factors influencing physician choice. Hakim research journal, 2007, 10(3), 22-27 , (In Persian).
23. Hill, C. J., & Garner, S. J. Factor’s influencing physician choice. Hospital & health services administration, 1991, 36(4), 491.
24. Harazi, M. A., & Askari, J. Assessment of the most important factors influencing physician choice. Hakim research journal, 2007, 10(3), 22-27, (In Persian).
25. Zolnierek, K. B. H., & DiMatteo, M. R. Physician communication and patient adherence to treatment: a meta-analysis. Medical care, 2009, 47(8), 826-834.
26. Hamelin, N. D., Nikolis, A., Armano, J., Harris, P. G., & Brutus, J. P. Evaluation of factors influencing confidence and trust in the patient-physician relationship: A survey of patient in a hand clinic. Chirurgie de la main, 2012, 31(2), 83-90.
27. Sekaran, U., & Bougie, R. Research Methods for Business: A Skill Building Approach. John Wiley & Sons, 2010.
28. Kalliainen, L. K., & Lichtman, D. M. Current issues in the physician–patient relationship. The Journal of hand surgery,2010, 35(12), 2126-2129.
29. Entwistle, V. A., Carter, S. M., Cribb, A., & McCaffery, K. Supporting patient autonomy: the importance of clinician-patient relationships. Journal of general internal medicine,2010, 25(7), 741-745.
30. Emanuel, E. J., & Emanuel, L. L. Four models of the physician-patient relationship. JAMA: the journal of the American Medical Association, 1992, 267(16), 2221-2226.
31. Kowalski, C., Nitzsche, A., Scheibler, F., Steffen, P., Albert, U. S., & Pfaff, H. Breast cancer patients’ trust in physicians: The impact of patients’ perception of physicians’ communication behaviors and hospital organizational climate. Patient education and counseling, 2009, 77(3), 344-348.
32. Asemani, O. Review of physician-patient models and related challenges. Iranian Journal of Medical Ethics and History of Medicine, 2012, 5(4), 36-50(In Persian).
33. Tubbs, S. L., Moss, S., & Papastefanou, N. Human communication: principles and contexts. McGraw-Hill Higher Education, 2008.
34. Kaba, R., & Sooriakumaran, P. The evolution of the doctor-patient relationship. International Journal of Surgery, 2007, 5(1), 57-65.
35. Loewy, E. H., & Loewy, R. S. Textbook of healthcare ethics. Springer. New York, 2004, 96-105.
36. Hafezi, F., Kouchakzadeh, K., Naghibzadeh, B. History and Status of Nose Surgery. Iranian Journal of Surgery, 2009, 17(2): 88-94(In Persian).
37. Ozar, D. T. Patients' autonomy: Three models of the professional-lay relationship in medicine. Theoretical medicine, 1984, 5(1), 61-68.
38. Craig, R. T. Communication theory as a field. Communication theory, 1999, 9(2), 119-161.
39. Ferguson, W. J., & Candib, L. M. Culture, language, and the doctor-patient relationship. FMCH Publications and Presentations, 2002, 61.
40. Witten, I. H., Frank, E., & Hall, M. A. Data Mining: Practical Machine Learning Tools and Techniques, Elsevier, 2011.
41. Borovicka, T., Jirina Jr, M., Kordik, P., & Jirina, M. Selecting representative data sets. Advances in Data Mining Knowledge Discovery and Applications. Intech, Associate Prof. Adem Karahoca, Available 0n 2012 from: http://www.intechopen.com/books/advances-in-data-mining-knowledge-discovery-and-applications/selecting-representative-data-sets
42. Liu, H., Yu, L., Toward integrating feature selection algorithms for
43. classification and clustering. Knowledge and Data Engineering, IEEE Transactions on , 2005, 17(4), 491-502.
44. Yu, N. Y., Yamauchi, T., Yang, H. F., Chen, Y. L., & Gutierrez‐Osuna, R. Feature selection for inductive generalization. Cognitive science, 2010, 34(8), 1574-1593