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Health Aff (Millwood). 2014 Jul;33(7):1220-8. doi: 10.1377/hlthaff.2014.0225.

Assessing the value of patient-generated data to comparative effectiveness research.

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Lynn Howie is a fellow in medical oncology at Duke University, in Durham, North Carolina.
Bradford Hirsch is an assistant professor in the Center for Learning Health Care, Duke Clinical Research Institute, in Durham.
Tracie Locklear is research coordinator at the Center for Learning Health Care, Duke Clinical Research Institute.
Amy P. Abernethy ( is director of the Center for Learning Health Care, Duke Clinical Research Institute, and a professor in the Duke University School of Medicine, in Durham.


The goal of comparative effectiveness research is to assess medical therapies and allow patients, health care providers, payers, and policy makers to make evidence-based decisions about the most appropriate therapies in routine clinical practice. To conduct this type of research and to inform health care delivery, data about the impact of interventions on patient outcomes are needed. Methods of generating evidence for comparative effectiveness research provide opportunities to engage patients and understand their experiences with illness and its treatment. In this article we assess the need for, uses of, and strengths and weaknesses of patient-generated data. We also review in brief federal and medical society efforts to create new streams of patient-generated data for clinical and research use. We observe that the key to high-quality patient-generated data is to have immediate and actionable data so that patients experience the importance of the data for their own care as well as research purposes. We conclude that leveraging the emerging wealth of "big data" being generated by patient-facing technologies such as systems to collect patient-reported outcomes data and patient-worn sensors is critical to developing the evidence base that informs decisions made by patients, providers, and policy makers in pursuit of high-value medical care.


Evidence-Based Medicine; Information Technology; Medical technology; Organization and Delivery of Care; Quality Of Care

[Indexed for MEDLINE]

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