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Comparative Study
. 2009;22(4):382-410.
doi: 10.1108/09526860910964843.

Healthcare quality and moderators of patient satisfaction: testing for causality

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Comparative Study

Healthcare quality and moderators of patient satisfaction: testing for causality

Masood A Badri et al. Int J Health Care Qual Assur. 2009.

Abstract

Purpose: The purpose of this article is to present a comprehensive structural equation based service quality and patient satisfaction model taking into account the patient's condition before and after discharge. The authors aim to test for causality in a sample of patients from United Arab Emirates public hospitals.

Design/methodology/approach: Data were collected using questionnaires completed by adults discharged (n = 244) from UAE public hospitals. The proposed model consists of five main constructs. Three represent service quality: quality of care (four variables); process and administration (four variables) and information (four variables). There is also one construct that represents patient's status (two variables--health status before admission and after discharge). Finally, there is one construct that represents patient's satisfaction with care (two variables--general and relative satisfaction). Structural equation modeling and LISREL using maximum likelihood estimation was used to test hypothesized model(s)/parameters(s) derived deductively from the literature.

Findings: The structural equation modeling representation provides a comprehensive picture that allows healthcare constructs and patient satisfaction causality to be tested. The goodness-of-fit statistics supported the healthcare quality-patient status-satisfaction model.

Originality/value: The model has been found to capture attributes that characterize healthcare quality in a developing country and could represent other modern healthcare systems. Also, it can be used to evaluate other healthcare practices from patients' viewpoints. The study highlights the importance of healthcare quality as patient satisfaction predictors by capturing other effects such as patient status.

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