Exploring UK doctors’ attitudes towards online patient feedback: Thematic analysis of survey data

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Abstract

Introduction: Patients are increasingly using online platforms to give feedback about their health-care experiences. Online feedback has been proposed as a way to drive transformative change in the health service through informing choice and improving quality. Attitudes held by health-care professionals influence the uptake of new technologies. Understanding these attitudes is essential in exploring the potential of online patient feedback as a standard feedback mechanism. This study explores the content of free-text comments left by doctors responding to a survey with the aim of understanding their attitudes towards online feedback. Methods: A cross-sectional online questionnaire was completed by 1001 UK primary and secondary-care doctors. Doctors were given the opportunity to leave a free-text comment about online patient feedback. Doctors’ attitudes towards online patient feedback were identified and explored using thematic analysis. Descriptive statistics and chi-square tests were used to examine demographic differences between those doctors who left a comment and those who did not. Results: Thematic analysis identified five key interrelated themes: anonymity, confidentiality, representativeness, moderation/regulation of online feedback and platform type. The characteristics of those leaving a comment very closely matched those of the entire survey sample. Conclusion: Across the comments, the most prominent finding was a general scepticism and caution towards online feedback, with most of the key themes relating to the perceived limitations and challenges. Further work exploring ways of addressing and verifying online comments without breaching confidentiality could provide valuable information to health systems seeking to drive improvement through patient online feedback.

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APA

Turk, A., Fleming, J., Powell, J., & Atherton, H. (2020). Exploring UK doctors’ attitudes towards online patient feedback: Thematic analysis of survey data. Digital Health, 6. https://doi.org/10.1177/2055207620908148

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