Adaptation of the Risk Analysis Index for Frailty Assessment Using Diagnostic Codes

Author:

Dicpinigaitis Alis J.12,Khamzina Yekaterina3,Hall Daniel E.1456,Nassereldine Hasan3,Kennedy Jason78,Seymour Christopher W.78,Schmidt Meic2,Reitz Katherine M.3789,Bowers Christian A.2

Affiliation:

1. Department of Neurology, New York Presbyterian–Weill Cornell Medical Center, New York, New York

2. Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Albuquerque, New Mexico

3. Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania

4. Department of Surgery, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania

5. Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania

6. Wolff Center, UPMC, Pittsburgh, Pennsylvania

7. Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, Pennsylvania

8. Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania

9. Division of Vascular Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania

Abstract

ImportanceFrailty is associated with adverse outcomes after even minor physiologic stressors. The validated Risk Analysis Index (RAI) quantifies frailty; however, existing methods limit application to in-person interview (clinical RAI) and quality improvement datasets (administrative RAI).ObjectiveTo expand the utility of the RAI utility to available International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) administrative data, using the National Inpatient Sample (NIS).Design, Setting, and ParticipantsRAI parameters were systematically adapted to ICD-10-CM codes (RAI-ICD) and were derived (NIS 2019) and validated (NIS 2020). The primary analysis included survey-weighed discharge data among adults undergoing major surgical procedures. Additional external validation occurred by including all operative and nonoperative hospitalizations in the NIS (2020) and in a multihospital health care system (UPMC, 2021-2022). Data analysis was conducted from January to May 2023.ExposuresRAI parameters and in-hospital mortality.Main Outcomes and MeasuresThe association of RAI parameters with in-hospital mortality was calculated and weighted using logistic regression, generating an integerized RAI-ICD score. After initial validation, thresholds defining categories of frailty were selected by a full complement of test statistics. Rates of elective admission, length of stay, hospital charges, and in-hospital mortality were compared across frailty categories. C statistics estimated model discrimination.ResultsRAI-ICD parameters were weighted in the 9 548 206 patients who were hospitalized (mean [SE] age, 55.4 (0.1) years; 3 742 330 male [weighted percentage, 39.2%] and 5 804 431 female [weighted percentage, 60.8%]), modeling in-hospital mortality (2.1%; 95% CI, 2.1%-2.2%) with excellent derivation discrimination (C statistic, 0.810; 95% CI, 0.808-0.813). The 11 RAI-ICD parameters were adapted to 323 ICD-10-CM codes. The operative validation population of 8 113 950 patients (mean [SE] age, 54.4 (0.1) years; 3 148 273 male [weighted percentage, 38.8%] and 4 965 737 female [weighted percentage, 61.2%]; in-hospital mortality, 2.5% [95% CI, 2.4%-2.5%]) mirrored the derivation population. In validation, the weighted and integerized RAI-ICD yielded good to excellent discrimination in the NIS operative sample (C statistic, 0.784; 95% CI, 0.782-0.786), NIS operative and nonoperative sample (C statistic, 0.778; 95% CI, 0.777-0.779), and the UPMC operative and nonoperative sample (C statistic, 0.860; 95% CI, 0.857-0.862). Thresholds defining robust (RAI-ICD <27), normal (RAI-ICD, 27-35), frail (RAI-ICD, 36-45), and very frail (RAI-ICD >45) strata of frailty maximized precision (F1 = 0.33) and sensitivity and specificity (Matthews correlation coefficient = 0.26). Adverse outcomes increased with increasing frailty.Conclusion and RelevanceIn this cohort study of hospitalized adults, the RAI-ICD was rigorously adapted, derived, and validated. These findings suggest that the RAI-ICD can extend the quantification of frailty to inpatient adult ICD-10-CM–coded patient care datasets.

Publisher

American Medical Association (AMA)

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