Patients' satisfaction and public and private sectors' health care service quality in Pakistan: Application of grey decision analysis approaches

Saad Ahmed Javed, Sifeng Liu, Amin Mahmoudi and Muhammad Nawaz

International Journal of Health Planning and Management, 2019, vol. 34, issue 1, e168-e182

Abstract: Purpose The study aims to evaluate the comprehensive relationship between patient satisfaction and five dimensions of health care service quality in Pakistani public/private health care sectors, using a novel grey relational analysis (GRA) models and the Hurwicz criteria of decision making under uncertainty. Design/methodology/approach Data were collected from private and public health care facilities of Pakistan through an improved SERVQUAL instrument. Deng's GRA, absolute GRA, and the second synthetic GRA models were applied to address the problem under study. Findings Grey relational analysis models revealed that reliability and responsiveness are most strongly predicting patient satisfaction in public and private health care sectors, respectively. The Hurwicz criteria showed that patients are more likely to be satisfied from private health care facilities. Limitations/implications Limitations of SERVQUAL model are also the limitations of the study; eg, the study suggests that because of the absence of “cost,” which is a key quality indicator of Pakistani public sector health care facilities, the model was unable to comprehensively evaluate the health care situation in light of the observations of price‐focused Pakistani patients. The study recommends tailoring of SERVQUAL model for the resource‐scant and underdeveloped countries where people's evaluation of the quality of the hospitals is likely to be influenced by the price of services. Originality/value The study is a pioneer in health care evaluation of public and private sectors of Lahore and Rawalpindi while using GRA models, in general, and the second synthetic GRA model, in particular. It presents an alternative method to the statistical way of analyzing data by successfully demonstrating the use of grey methods, which can make reasonable decisions even through small samples.

Date: 2019
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