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Assessing the value of patient-generated data to comparative effectiveness research.
Lynn Howie1, Bradford Hirsch2, Tracie Locklear3
1Lynn Howie is a fellow in medical oncology at Duke University, in Durham, North Carolina.
Health Affairs (Project Hope)
|July 10, 2014
Summary
Patient-generated data, including patient-reported outcomes and data from wearable sensors, is vital for comparative effectiveness research. High-quality, actionable data empowers patients and informs evidence-based medical decisions.
Area of Science:
- Health Services Research
- Medical Informatics
Background:
- Comparative effectiveness research (CER) requires robust data on intervention impacts.
- Patient engagement in data generation offers insights into treatment experiences.
Purpose of the Study:
- Assess the need, uses, strengths, and weaknesses of patient-generated data in CER.
- Review efforts to create new patient-generated data streams for clinical and research applications.
Main Methods:
- Analysis of patient-generated data sources.
- Review of federal and medical society initiatives for data generation.
- Evaluation of data quality and actionability.
Main Results:
- Patient-generated data is crucial for informing evidence-based decisions.
- Immediate and actionable data enhances patient engagement and research value.
- Leveraging big data from patient-facing technologies is key for high-value care.
Conclusions:
- Patient-generated data is essential for advancing comparative effectiveness research.
- The integration of patient-reported outcomes and sensor data is critical for informed medical decision-making.
- Harnessing big data from patients supports the development of high-value healthcare.
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