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Adaptation of the Risk Analysis Index for Frailty Assessment Using Diagnostic Codes
Alis J Dicpinigaitis1,2, Yekaterina Khamzina3, Daniel E Hall1,4,5,6
1Department of Neurology, New York Presbyterian-Weill Cornell Medical Center, New York, New York.
JAMA Network Open
|May 24, 2024
Summary
The Risk Analysis Index (RAI) can now quantify patient frailty using administrative data (RAI-ICD). This new method accurately predicts adverse outcomes in hospitalized adults, improving care.
Area of Science:
- Gerontology
- Health Services Research
- Medical Informatics
Background:
- Frailty is a significant predictor of adverse outcomes following physiological stress.
- Existing Risk Analysis Index (RAI) methods are limited to in-person interviews or specific quality datasets.
- There is a need to expand frailty quantification to widely available administrative data.
Purpose of the Study:
- To adapt and validate the Risk Analysis Index (RAI) for use with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) administrative data.
- To create a novel frailty assessment tool, RAI-ICD, applicable to large-scale inpatient datasets.
- To evaluate the association of RAI-ICD with in-hospital mortality and other adverse outcomes.
Main Methods:
- Systematic adaptation of RAI parameters to ICD-10-CM codes (RAI-ICD).
- Derivation and validation of RAI-ICD using the National Inpatient Sample (NIS) datasets (2019-2020).
- External validation in a multihospital health care system (UPMC) and across operative/nonoperative hospitalizations.
- Logistic regression modeling to associate RAI-ICD with in-hospital mortality; C statistics for discrimination.
Main Results:
- RAI-ICD was derived and validated in over 9.5 million hospitalized patients, demonstrating excellent discrimination for in-hospital mortality (C statistic, 0.810).
- The adapted RAI-ICD parameters utilized 323 ICD-10-CM codes.
- External validation in large datasets (NIS, UPMC) confirmed good to excellent discrimination (C statistics ranging from 0.778 to 0.860).
- Defined frailty strata (robust, normal, frail, very frail) showed increasing adverse outcomes with higher frailty levels.
Conclusions:
- The RAI-ICD represents a rigorously adapted, derived, and validated tool for quantifying frailty.
- This novel approach extends frailty assessment to large inpatient datasets coded with ICD-10-CM.
- RAI-ICD facilitates broader application of frailty assessment in clinical practice and research.
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