Utilizing online reviews for analyzing digital healthcare consultation services: Examining perspectives of both healthcare customers and healthcare professionals

• Published in: International journal of medical informatics (Shannon, Ireland) Ireland), 2024-11, Vol.191, p.105587, Article 105587
• Main Authors: Bellary, Sreevatsa, Kumar Bala, Pradip, Chakraborty, Shibashish
• Format: Article
• Language: English
• Subjects: Health services; Online customer reviews; Structural topic modeling; Telemedicine; Text mining
• ISSN: 1386-5056; 1872-8243; 1872-8243
• DOI: 10.1016/j.ijmedinf.2024.105587

•The COVID-19 pandemic accelerated the global adoption of telemedicine.•In developing countries like India, telemedicine addresses significant healthcare infrastructure challenges.•Analysis of 44,440 patient reviews and 4748 doctor reviews provided comprehensive insights into satisfaction determinants. Digital healthcare consultation services, also known as telemedicine, have seen a surge in their usage, especially after the COVID-19 pandemic. The purpose of this study is to investigate the satisfaction determinants of healthcare customers (patients) and healthcare professionals (doctors), providing digital healthcare consultation services. The analysis involved scraping online reviews of 11 telemedicine apps meant for patients and 7 telemedicine apps meant for doctors, yielding a total of 44,440 patient reviews and 4748 doctor reviews. A structural topic modeling analysis followed by regression, dominance, correspondence, and emotion analysis was conducted to derive insights. The study identified ten determinants of satisfaction from patients’ and eight from doctors’ perspectives. For patients, ’service variety and quality’ (β = 0.5527) was the top positive determinant, while ’payment disputes’ (β = -0.1173) and ’in-app membership’ (β = -0.031) negatively impacted satisfaction. For doctors, ’patient consultation management’ (β = 0.2009) was the leading positive determinant, with ’profile management’ (β = -0.1843), ’subscription’ (β = -0.183), and ’customer care support’ (β = -0.0908) being the negative ones. The most influential negative emotion for patients, anger, was closely associated with ’customer care service’ and ’in-app memberships,’ while joy was tied to ’service variety and quality’ and ’offers and discounts.’ For doctors, anger was associated with ’cost-effectiveness,’ and joy with ’app responsiveness.’ This study offers new insights by examining patient and doctor determinants at a granular level which can be used by telemedicine app developers and managers to build customer-centric services.