Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook
Social media sites, dubbed patient online reviews (POR), have been proposed as new methods for assessing patient satisfaction and monitoring quality of care. However, the unstructured nature of POR data derived from social media creates a number of challenges. The objectives of this research were to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/9/10/1369 |
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| author | Afiq Izzudin A. Rahim Mohd Ismail Ibrahim Kamarul Imran Musa Sook-Ling Chua Najib Majdi Yaacob |
| author_facet | Afiq Izzudin A. Rahim Mohd Ismail Ibrahim Kamarul Imran Musa Sook-Ling Chua Najib Majdi Yaacob |
| author_sort | Afiq Izzudin A. Rahim |
| collection | DOAJ |
| description | Social media sites, dubbed patient online reviews (POR), have been proposed as new methods for assessing patient satisfaction and monitoring quality of care. However, the unstructured nature of POR data derived from social media creates a number of challenges. The objectives of this research were to identify service quality (SERVQUAL) dimensions automatically from hospital Facebook reviews using a machine learning classifier, and to examine their associations with patient dissatisfaction. From January 2017 to December 2019, empirical research was conducted in which POR were gathered from the official Facebook page of Malaysian public hospitals. To find SERVQUAL dimensions in POR, a machine learning topic classification utilising supervised learning was developed, and this study’s objective was established using logistic regression analysis. It was discovered that 73.5% of patients were satisfied with the public hospital service, whereas 26.5% were dissatisfied. SERVQUAL dimensions identified were 13.2% reviews of tangible, 68.9% of reliability, 6.8% of responsiveness, 19.5% of assurance, and 64.3% of empathy. After controlling for hospital variables, all SERVQUAL dimensions except tangible and assurance were shown to be significantly related with patient dissatisfaction (reliability, <i>p</i> < 0.001; responsiveness, <i>p</i> = 0.016; and empathy, <i>p</i> < 0.001). Rural hospitals had a higher probability of patient dissatisfaction (<i>p</i> < 0.001). Therefore, POR, assisted by machine learning technologies, provided a pragmatic and feasible way for capturing patient perceptions of care quality and supplementing conventional patient satisfaction surveys. The findings offer critical information that will assist healthcare authorities in capitalising on POR by monitoring and evaluating the quality of services in real time. |
| first_indexed | 2024-03-10T06:32:06Z |
| format | Article |
| id | doaj.art-c6749371da464b8cb8cd3470f1ca1313 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-10T06:32:06Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-c6749371da464b8cb8cd3470f1ca13132023-11-22T18:26:00ZengMDPI AGHealthcare2227-90322021-10-01910136910.3390/healthcare9101369Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and FacebookAfiq Izzudin A. Rahim0Mohd Ismail Ibrahim1Kamarul Imran Musa2Sook-Ling Chua3Najib Majdi Yaacob4Department of Community Medicine, School of Medical Science, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, MalaysiaDepartment of Community Medicine, School of Medical Science, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, MalaysiaDepartment of Community Medicine, School of Medical Science, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, MalaysiaFaculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, Cyberjaya 63100, Selangor, MalaysiaUnit of Biostatistics and Research Methodology, Health Campus, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, MalaysiaSocial media sites, dubbed patient online reviews (POR), have been proposed as new methods for assessing patient satisfaction and monitoring quality of care. However, the unstructured nature of POR data derived from social media creates a number of challenges. The objectives of this research were to identify service quality (SERVQUAL) dimensions automatically from hospital Facebook reviews using a machine learning classifier, and to examine their associations with patient dissatisfaction. From January 2017 to December 2019, empirical research was conducted in which POR were gathered from the official Facebook page of Malaysian public hospitals. To find SERVQUAL dimensions in POR, a machine learning topic classification utilising supervised learning was developed, and this study’s objective was established using logistic regression analysis. It was discovered that 73.5% of patients were satisfied with the public hospital service, whereas 26.5% were dissatisfied. SERVQUAL dimensions identified were 13.2% reviews of tangible, 68.9% of reliability, 6.8% of responsiveness, 19.5% of assurance, and 64.3% of empathy. After controlling for hospital variables, all SERVQUAL dimensions except tangible and assurance were shown to be significantly related with patient dissatisfaction (reliability, <i>p</i> < 0.001; responsiveness, <i>p</i> = 0.016; and empathy, <i>p</i> < 0.001). Rural hospitals had a higher probability of patient dissatisfaction (<i>p</i> < 0.001). Therefore, POR, assisted by machine learning technologies, provided a pragmatic and feasible way for capturing patient perceptions of care quality and supplementing conventional patient satisfaction surveys. The findings offer critical information that will assist healthcare authorities in capitalising on POR by monitoring and evaluating the quality of services in real time.https://www.mdpi.com/2227-9032/9/10/1369patient satisfactionservice qualitySERVQUALFacebookmachine learningpatient online review |
| spellingShingle | Afiq Izzudin A. Rahim Mohd Ismail Ibrahim Kamarul Imran Musa Sook-Ling Chua Najib Majdi Yaacob Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook Healthcare patient satisfaction service quality SERVQUAL machine learning patient online review |
| title | Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook |
| title_full | Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook |
| title_fullStr | Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook |
| title_full_unstemmed | Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook |
| title_short | Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook |
| title_sort | patient satisfaction and hospital quality of care evaluation in malaysia using servqual and facebook |
| topic | patient satisfaction service quality SERVQUAL machine learning patient online review |
| url | https://www.mdpi.com/2227-9032/9/10/1369 |
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