• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology

Article

Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 21, Pages: 1603-1613

Original Article

Prediction of Healthcare Quality Using Sentiment Analysis

Received Date:31 December 2022, Accepted Date:18 May 2023, Published Date:03 June 2023

Abstract

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

References

  1. Ramírez-Tinoco FJ, Alor-Hernández G, Sánchez-Cervantes JL, Salas-Zárate MDP, Valencia-García R. Use of Sentiment Analysis Techniques in Healthcare Domain. In: Studies in Computational Intelligence. (Vol. 815, pp. 189-212) Springer International Publishing. 2019.
  2. Panchal DS, Kawathekar SS, Deshmukh SN. Sentiment Analysis of Healthcare Quality. International Journal of Innovative Technology and Exploring Engineering. 2020;9(3):3369–3376. Available from: https://doi.org/10.35940/ijitee.L2532.019320
  3. Godara J, Aron R, Shabaz MR. Sentiment analysis and sarcasm detection from social network to train health-care professionals. World Journal of Engineering. 2022;19(1):124–133. Available from: https://doi.org/10.1108/WJE-02-2021-0108
  4. Aattouchi I, Elmendili S, Elmendili F. Sentiment Analysis of Health Care: Review. E3S Web of Conferences. 2021. Available from: https://doi.org/10.1051/e3sconf/202131901064
  5. Bhatt R, Gupta P. Sentiment Analysis. Indian Journal of Science and Technology. 2019;12(41):1–6. Available from: https://dx.doi.org/10.17485/ijst/2019/v12i41/145556
  6. Bhatia PO, Nath RA. Using sentiment analysis in Patient Satisfaction: A Survey. Advances in Mathematics: Scientific Journal. 2019;9(6):3803–3812. Available from: https://doi.org/10.37418/amsj.9.6.59
  7. Kamakshi P. Sentiment analysis on Healthcare Tweets. Indian Journal of Public Health Research & Development. 2020;11(6):566–568. Available from: https://medicopublication.com/index.php/ijphrd/article/view/9841
  8. Lai ST, Mafas R. Sentiment Analysis in Healthcare: Motives, Challenges & Opportunities pertaining to Machine Learning. 2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE), Ballari, India. 2022;p. 1–4. Available from: https://doi.org/10.1109/ICDCECE53908.2022.9792766
  9. Shi T, Rakesh V, Wang S, Chandan K, Reddy. Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts. Proceedings of the 28th ACM International Conference on Information and Knowledge Management. 2019;p. 2723–2731. Available from: https://doi.org/10.1145/3357384.3357828
  10. Zhang W, Li X, Deng Y, Bing L, Lam W. A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges. IEEE Transactions on Knowledge and Data Engineering. 2022;p. 1–20. Available from: https://doi.org/10.1109/TKDE.2022.3230975
  11. Wu Z, Ong DC. Context-Guided BERT for Targeted Aspect-Based Sentiment Analysis. Proceedings of the AAAI Conference on Artificial Intelligence. 2021;35(16):14094–14102. Available from: https://doi.org/10.1609/aaai.v35i16.17659
  12. Bansal A, Kumar N. Aspect-Based Sentiment Analysis Using Attribute Extraction of Hospital Reviews. New Generation Computing. 2022;40(4):941–960. Available from: https://doi.org/10.1007/s00354-021-00141-3
  13. Augustyniak Ł, Kajdanowicz T, Kazienko P. Comprehensive analysis of aspect term extraction methods using various text embeddings. Computer Speech & Language. 2021;69:101217. Available from: https://doi.org/10.1016/j.csl.2021.101217

Copyright

© 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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