Prediction of Inpatient Satisfaction with Service Quality with SEM Method

Maria Sinaga, Chrismis Novalinda Ginting, Ali Napiah Nasution, Ermi Girsang

Abstract

Patient satisfaction is an indicator of the hospital services quality. In fact, hospital services often make patients dissatisfied like convoluted, boring, inhospitable, less dexterous. This is allegedly because the provided quality services is out of the patient expectations. The purpose of this study is to model the relationship between service quality and inpatient satisfaction, which can then be used to predict satisfaction with various variables. Modeling was conducted on questionnaire measurement data from 2,071 respondents with 250 samples. Analysis of questionnaire data was processed using univariate, bivariate with chi-square tests, and multivariate with multiple logistic regression at 95% confidence level ( = 0.05). The modeling accuracy above 90% was obtained with an input and output relationships in the form of satisfaction. Statistically there was a relationship between physical evidence, reliability, quick response, and empathy with inpatient satisfaction, p <0.05. The most significant variable related to inpatient satisfaction was reliability, where patients who state good reliability will be satisfied with hospital services by 7.6 times higher than those that are less good.

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Paper Citation


in Harvard Style

Sinaga M., Ginting C., Nasution A. and Girsang E. (2020). Prediction of Inpatient Satisfaction with Service Quality with SEM Method.In Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP, ISBN 978-989-758-500-5, pages 126-132. DOI: 10.5220/0010291301260132


in Bibtex Style

@conference{himbep20,
author={Maria Sinaga and Chrismis Novalinda Ginting and Ali Napiah Nasution and Ermi Girsang},
title={Prediction of Inpatient Satisfaction with Service Quality with SEM Method},
booktitle={Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP,},
year={2020},
pages={126-132},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010291301260132},
isbn={978-989-758-500-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical - Volume 1: HIMBEP,
TI - Prediction of Inpatient Satisfaction with Service Quality with SEM Method
SN - 978-989-758-500-5
AU - Sinaga M.
AU - Ginting C.
AU - Nasution A.
AU - Girsang E.
PY - 2020
SP - 126
EP - 132
DO - 10.5220/0010291301260132