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Using electronic health record data to identify comparator populations for comparative effectiveness research.
Scott D Ramsey1, Blythe J Adamson2,3, Xiaoliang Wang2
1Fred Hutchinson Cancer Center, Hutchinson Institute for Cancer Outcomes Research, Seattle, WA, USA.
Journal of Medical Economics
|October 21, 2020
Summary
Electronic health records (EHRs) provide specific patient data for comparative effectiveness research. However, creating homogenous cohorts from EHRs can reduce representativeness, impacting real-world applicability.
Area of Science:
- Health Informatics
- Clinical Research Methodology
- Real-World Evidence
Background:
- Electronic health records (EHRs) offer detailed clinical data for real-world data (RWD) analysis.
- EHR-derived RWD can define patient populations with high clinical specificity for medical technology evaluation.
Purpose of the Study:
- To discuss the trade-offs between clinical specificity and representativeness in EHR-derived RWD for comparative effectiveness research.
- To illustrate these concepts using non-small cell lung cancer patient data.
Main Methods:
- Utilizing EHR-derived real-world data.
- Analyzing patient cohorts for comparative effectiveness research.
- Examining non-small cell lung cancer as a case study.
Main Results:
- EHR data allows for highly specific patient subpopulation creation.
- Overly homogenous cohorts derived from EHRs may lack representativeness of clinical practice.
- Significant outcome variations were observed among different comparator cohorts in the non-small cell lung cancer example.
Conclusions:
- Balancing clinical specificity and representativeness is crucial when selecting patient populations from EHRs for comparative effectiveness studies.
- Recommendations are provided for optimizing comparator population selection from EHRs to reflect both clinical guidelines and practice variability.
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