Using a Frailty Index with Electronic Health Records
Author Information
Author(s): Kwak Min Ji, Schaefer Caroline, Kim Youngran, Fu Sunyang, Dhoble Abhjieet, Rianon Nahid, Holmes Holly, Kim Dae Hyun
Primary Institution: McGovern Medical School, Houston, Texas, United States
Hypothesis
Can the claim-based frailty index (CFI) be effectively applied to structured electronic health record (EHR) data?
Conclusion
The study suggests that the CFI can be implemented in EHR data to predict adverse clinical events in heart failure patients.
Supporting Evidence
- The CFI from Medicare claims showed a right-skewed distribution with a mode of 0.210.
- The CFI from Explorys data had a mode of 0.186 and a narrower distribution.
- When frailty was defined as CFI ≥0.25, Explorys data identified fewer cases of frailty (18.1% vs 42.4% in Medicare claims).
- CFI from Explorys data had better discrimination in predicting hospital admission or emergency room visits (C-statistic: 0.636 vs 0.608 in Medicare claims).
Takeaway
Researchers wanted to see if a tool for measuring frailty could work with electronic health records, and they found it can help predict health problems in older patients with heart failure.
Methodology
The study compared the CFI calculated from structured EHR data with that from Medicare claims for older adults with heart failure.
Limitations
The study only focused on older adults with heart failure and may not be generalizable to other populations.
Participant Demographics
Older adults (≥65 years old) with heart failure.
Digital Object Identifier (DOI)
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