The Effects of Perceived Service Quality on Patient Satisfaction at a Public Hospital in State of Pahang, Malaysia

• Main Authors: Noor Azlinna, Azizan, Bahari, Mohamed
• Format: Article
• Language: English; English
• Published: Leena and Luna International, Oyama, Japan 2013
• Subjects: T Technology (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/6329/1/The_Effects_of_Perceived_Service_Quality_on_Patient_Satisfaction_at_a_Public_Hospital_in_State_of_Pahang%2C_Malaysia.pdf; http://umpir.ump.edu.my/id/eprint/6329/4/ftech-2013-azlinna-effect%20of%20perceived%20services.pdf; http://umpir.ump.edu.my/id/eprint/6329/; http://www.ajssh.leena-luna.co.jp/AJSSHPDFs/Vol.2%283%29/AJSSH2013%282.3-34%29.pdf

This study focuses on the effects of perceived service quality on patient satisfaction in a public hospital. Data was collected from 109 respondents that experienced the hospital service. Using a PLS-SEM tool, the hypothesized effects among the constructs were tested empirically. No statistically significant relationships were found between perceived service quality construct and (i) the hospital infrastructure constructs and it did not support the hypothesis H1 (beta= 0.000 and t-value= 0.004,ρ > 05.0 ) (ii) interaction with care providers construct and it did not support the hypothesis H2 (beta= -0.045 and t-value= 0.443, ρ > 05.0 ). However, the results indicate that the path coefficients were significant between perceived service quality construct and (iii) patients’ perception of administrative procedure construct and it supported the hypothesis H3 (beta= 0.317, t-value= 3.026, ρ < 01.0 ), (iv) patients‘ perception of medical care construct and it supported the hypothesis H4 (beta=0.182, t-value= 2.150, ρ < 05.0 ) and (v) patients’ perception of nursing care construct and it supported the hypothesis H5 (beta= 0.481, t-value= 5.190, ρ < 01.0). The constructs were considered the key factors that influence the perceived service quality in the current study. The path coefficient from perceived service quality to patient satisfaction was very significant and it supported the hypothesis H6 (beta= 0.816, t-value= 19.460, ρ < 01.0 ). The antecedents of service quality demonstrated considerable power in explaining variance in perceived service quality. The infrastructure, interaction, administrative, medical care, and nursing care constructs explained 69.7% ( 2 R = 0.697) of the variance in perceived service quality and overall the model explained 66.6% ( 2 R =0.666) of the variance in patient satisfaction. Therefore, it can be concluded that the model is suitable in determining the health care service quality.