Indian Journal of Science and Technology
DOI: 10.17485/IJST/v16i21.2506
Year: 2023, Volume: 16, Issue: 21, Pages: 1603-1613
Original Article
D S Panchal1*, M B Shelke1, S S Kawathekar2, S N Deshmukh3
1Research Scholar, Department of C. S. and I.T, DR. B. A. M. U, Aurangabad, India
2Assistant Professor, Department of C. S. and I.T, DR. B. A. M. U, Aurangabad, India
3Professor, Department of C. S. and I.T, DR. B. A. M. U, Aurangabad, India
*Corresponding Author
Email: [email protected]
Received Date:31 December 2022, Accepted Date:18 May 2023, Published Date:03 June 2023
Objectives: To examine the quality of healthcare services and the features (aspects) of those services, as well as the variation in those services’ quality over a time. Methods: The study presents a method which includes firstly by collecting patient feedback data from the internet, and then follows preprocessing, extracting aspects of healthcare, and finally performing aspectbased sentiment analysis of healthcare. This aspect-based sentiment analysis is created to determine the pattern of aspect in a sentence using the BERT model. Healthcare services and their aspect-quality service analysis are performed here date-wise, i.e., timestamp-wide. A total of 69 physician are selected to collect the feedback and analyzed the feedback using an aspect-based sentiment analysis technique. Findings: The quality of healthcare services is frequently changing. In healthcare, for example, sometimes there is good quality service and sometimes there is worst quality service. All 69 physicians’ total of 300 sentences with aspect-based sentiment scores are extracted separately after preprocessing and normalization. The aspect-wise results are shown in percentages. After that, the extracted aspect-wise percentages are shown as per date. Out of a total of 69 physicians, sample of D9, i.e., Doctor 9, patient feedback results, are shown in this paper. Novelty: This study made the aspect-based sentiment analysis score, which demonstrates the datewise, i.e., timestamp-wide variation in healthcare services. Previous research has made healthcare predictions using feedback ratings; no study has yet performed a date-wise analysis. The features, such as diagnosis, treatment, cleanliness, appointment, advice, medicine, staff service, etc., are included for analysis.
Keywords: Patient; Hospital; Patient feedback; Aspect based sentiment analysis; Healthcare Service; Healthcare Quality
© 2023 Panchal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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