Evaluating linked ICD-10 Medicare claims data as a method of dementia case ascertainment in research settings

Authors

Joya Bhattacharyya, Department of Epidemiology, George Washington University, Washington, District of Columbia, USA.
Lisa L. Barnes, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
Yi Chen, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
Kan Z. Gianattasio, NORC at the University of Chicago, Bethesda, Maryland, USA.
Francine Grodstein, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
Bryan D. James, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
David X. Marquez, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
Ali Moghtaderi, Department of Health Policy and Management, George Washington University, Washington, District of Columbia, USA.
Christina Prather, Department of Internal Medicine, School of Medicine and Health Sciences, George Washington University, Washington, District of Columbia, USA.
David B. Rein, NORC at the University of Chicago, Bethesda, Maryland, USA.
Raj C. Shah, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.
Emma K. Stapp, Department of Epidemiology, George Washington University, Washington, District of Columbia, USA.
Melinda C. Power, Department of Epidemiology, George Washington University, Washington, District of Columbia, USA.

Document Type

Journal Article

Publication Date

5-1-2025

Journal

Alzheimer's & dementia : the journal of the Alzheimer's Association

Volume

21

Issue

5

DOI

10.1002/alz.70200

Keywords

International Classification of Diseases 10th Revision; Medicare; administrative data; algorithm; dementia; epidemiology

Abstract

INTRODUCTION: US Medicare claims can be used to identify dementia cases for research. Our objective was to evaluate the performance of International Classification of Diseases, 10th Revision (ICD-10) code definitions versus research-based dementia ascertainment. METHODS: Participants of five Rush Alzheimer's Disease Center (RADC) cohorts with study visits between October 2015 and December 2019 and fee-for-service Medicare contributed observations. For each observation, we compared research-based dementia status to dementia status based on six ICD-10 code definitions. RESULTS: A total of 1869 participants contributed 5309 observations (mean age 82.9 years, 21.0% Black, 9.3% met research-based dementia criteria). The accuracy of ICD-10 code definitions was high (87%-90%); five of six code definitions favored specificity over sensitivity. All ICD-10 code definitions were less accurate among subgroups defined by older age, minoritized race, increased depressive symptoms, and history of stroke. DISCUSSION: Performance of ICD-10 code definitions mirrored that of ICD-9 code definitions. Awareness of differential performance by participant characteristics can improve the robustness of research. HIGHLIGHTS: We report the performance of the International Classification of Diseases, 10th Revision (ICD-10) code versus research-based dementia ascertainment. ICD-10 performed worse with age, depressive symptoms, minoritized race, and stroke. Awareness of accuracy and differential performance can improve research robustness.

APA Citation

Bhattacharyya, Joya; Barnes, Lisa L.; Chen, Yi; Gianattasio, Kan Z.; Grodstein, Francine; James, Bryan D.; Marquez, David X.; Moghtaderi, Ali; Prather, Christina; Rein, David B.; Shah, Raj C.; Stapp, Emma K.; and Power, Melinda C., "Evaluating linked ICD-10 Medicare claims data as a method of dementia case ascertainment in research settings" (2025). GW Authored Works. Paper 7316.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/7316

Department

Epidemiology