Tracking patients healthcare experiences during the COVID-19 outbreak : Topic modeling and sentiment analysis of doctor reviews
المؤلفون المشاركون
Yan, Xiangbin
Shah, Adnan M.
Tariq, Samiyah
Shah, Sayyid Asad A.
المصدر
Journal of Engineering Research
العدد
المجلد 9، العدد 3 A (30 سبتمبر/أيلول 2021)، ص ص. 219-239، 21ص.
الناشر
جامعة الكويت مجلس النشر العلمي
تاريخ النشر
2021-09-30
دولة النشر
الكويت
عدد الصفحات
21
التخصصات الرئيسية
العلوم الطبية والصيدلة والعلوم الصحية
الملخص EN
Emerging voices of patients in the form of opinions and expectations about the quality of care can improve healthcare service quality.
A large volume of patients' opinions as online doctor reviews (ODRs) are available online to access, analyze, and improve patients' perceptions.
This paper aims to explore COVID-19-related conversations, complaints, and sentiments using ODRs posted by users of the physician rating website.
We analyzed 96,234 ODRS of 5,621 physicians from a prominent health rating website in the United Kingdom (Iwantgreatcare.org) in three time slices (i.e., from February 01 to October 31, 2020).
We employed machine learning approach, dynamic topic modeling, to identify prominent bigrams, salient topics and labels, sentiments embedded in reviews and topics, and patient-perceived root cause and strengths, weaknesses, opportunities, and threats (SWOT) analyses to examine SWOT for healthcare organizations.
This method finds a total of 30 latent topics with 10 topics across each time slice.
The current study identified new discussion topics about COVID-19 occurring from time slice 1 to time slice 3, such as news about the COVID-19 pandemic, violence against the lockdown, quarantine process and quarantine centers at different locations, and vaccine development/treatment to stop virus spread.
Sentiment analysis reveals that fear for novel pathogen prevails across all topics.
Based on the SWOT analysis, our findings provide a clue for doctors, hospitals, and government officials to enhance patients' satisfaction and minimize dissatisfaction by satisfying their needs and improve the quality of care during the COVID-19 crisis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shah, Adnan M.& Yan, Xiangbin& Tariq, Samiyah& Shah, Sayyid Asad A.. 2021. Tracking patients healthcare experiences during the COVID-19 outbreak : Topic modeling and sentiment analysis of doctor reviews. Journal of Engineering Research،Vol. 9, no. 3 A, pp.219-239.
https://search.emarefa.net/detail/BIM-1494911
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shah, Adnan M.…[et al.]. Tracking patients healthcare experiences during the COVID-19 outbreak : Topic modeling and sentiment analysis of doctor reviews. Journal of Engineering Research Vol. 9, no. 3 A (Sep. 2021), pp.219-239.
https://search.emarefa.net/detail/BIM-1494911
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shah, Adnan M.& Yan, Xiangbin& Tariq, Samiyah& Shah, Sayyid Asad A.. Tracking patients healthcare experiences during the COVID-19 outbreak : Topic modeling and sentiment analysis of doctor reviews. Journal of Engineering Research. 2021. Vol. 9, no. 3 A, pp.219-239.
https://search.emarefa.net/detail/BIM-1494911
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 237-239
رقم السجل
BIM-1494911
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر