Revealing Patient-Reported Experiences in Healthcare from Social Media using the DAPMAV Framework

• URL: http://arxiv.org/abs/2210.04232v2
• Date: Mon, 11 Dec 2023 03:52:57 GMT
• Title: Revealing Patient-Reported Experiences in Healthcare from Social Media using the DAPMAV Framework
• Authors: Curtis Murray, Lewis Mitchell, Jonathan Tuke, Mark Mackay
• Abstract summary: We introduce the Design-Acquire-Process-Model-Analyse-Visualise (DAPMAV) framework to provide an overview of techniques and an approach to capture patient-reported experiences from social media data. We apply this framework in a case study on prostate cancer data from /r/ProstateCancer.
• Score: 0.04096453902709291
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Understanding patient experience in healthcare is increasingly important and desired by medical professionals in a patient-centered care approach. Healthcare discourse on social media presents an opportunity to gain a unique perspective on patient-reported experiences, complementing traditional survey data. These social media reports often appear as first-hand accounts of patients' journeys through the healthcare system, whose details extend beyond the confines of structured surveys and at a far larger scale than focus groups. However, in contrast with the vast presence of patient-experience data on social media and the potential benefits the data offers, it attracts comparatively little research attention due to the technical proficiency required for text analysis. In this paper, we introduce the Design-Acquire-Process-Model-Analyse-Visualise (DAPMAV) framework to provide an overview of techniques and an approach to capture patient-reported experiences from social media data. We apply this framework in a case study on prostate cancer data from /r/ProstateCancer, demonstrate the framework's value in capturing specific aspects of patient concern (such as sexual dysfunction), provide an overview of the discourse, and show narrative and emotional progression through these stories. We anticipate this framework to apply to a wide variety of areas in healthcare, including capturing and differentiating experiences across minority groups, geographic boundaries, and types of illnesses.

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