Authors
Mona Al-Amin, Suzanne C Makarem, Mahed Maddah
Published in
Journal of healthcare management / American College of Healthcare Executives. Volume 71. Issue 5. Pages 307-321.
Abstract
In an era of rapidly expanding healthcare data-much of it generated by consumers-healthcare organizations face both opportunities and challenges. This article presents a framework, a classification of data sources, and a set of analytical methods to establish more robust, timely, and impactful approaches to listening to consumers and capturing their voice.
We conducted an extensive review of the literature on data sources that carry the voice of healthcare consumers, including sources that organizations have not fully used. Through this review and team discussions, we systematically classified data sources and matched them to appropriate analytical methods.
We categorized three sources of consumer voice data: (1) traditional, (2) organic, and (3) observational or behavioral. We also identified three corresponding categories of analytical methods: (1) conventional analytical techniques, (2) machine learning and natural language approaches, and (3) real-time insights with user-centric analyses. Together, these sources and methods provide multiple pathways to generate timely and actionable insights into consumers' needs, preferences, and experiences.
Healthcare organizations should develop a system that harnesses consumer-generated and observational data alongside traditional sources and apply the appropriate analytical methods to each. Doing so enables leaders to deepen their understanding of consumer experiences and preferences, incorporate the voice of the consumer into decision-making, and ultimately, improve the delivery of patient-centered care.
PMID:
42706814
Bibliographic data and abstract were imported from PubMed on 08 Sep 2026.
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