Prevalence of Mild Cognitive Impairment and Alzheimer’s Disease Identified in Veterans in the United States

Author:

Aguilar Byron J.12,Jasuja Guneet K.345,Li Xuyang26,Shishova Ekaterina7,Palacios Natalia17,Berlowitz Dan7,Morin Peter8,O’Connor Maureen K.18,Nguyen Andrew12,Reisman Joel9,Leng Yue10,Zhang Raymond11,Monfared Amir Abbas Tahami1112,Zhang Quanwu11,Xia Weiming1913

Affiliation:

1. Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, Bedford, MA, USA

2. The Bedford VA Research Corporation, Inc., Bedford, MA, USA

3. Center for Healthcare Organization & Implementation Research, VA Bedford Healthcare System, Bedford, MA, USA

4. Section of General Internal Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA

5. Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA, USA

6. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

7. Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA

8. Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

9. Department of Biological Science, Kennedy College of Sciences, University of Massachusetts Lowell, Lowell, MA, USA

10. Department of Psychiatry, University of California San Francisco Weill Institute for Neurosciences, San Francisco, CA, USA

11. Alzheimer’s Disease and Brain Health, Eisai Inc., Nutley, NJ, USA

12. Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada

13. Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA

Abstract

Background: Diagnostic codes can be instrumental for case identification in Alzheimer’s disease (AD) research; however, this method has known limitations and cannot distinguish between disease stages. Clinical notes may offer more detailed information including AD severity and can complement diagnostic codes for case identification. Objective: To estimate prevalence of mild cognitive impairment (MCI) and AD using diagnostics codes and clinical notes available in the electronic healthcare record (EHR). Methods: This was a retrospective study in the Veterans Affairs Healthcare System (VAHS). Health records from Veterans aged 65 years or older were reviewed during Fiscal Years (FY) 2010–2019. Overall, 274,736 and 469,569 Veterans were identified based on a rule-based algorithm as having at least one clinical note for MCI and AD, respectively; 201,211 and 149,779 Veterans had a diagnostic code for MCI and AD, respectively. During FY 2011–2018, likely MCI or AD diagnosis was defined by≥2 qualifiers (i.e., notes and/or codes)≥30 days apart. Veterans with only 1 qualifier were considered as suspected MCI/AD. Results: Over the 8-year study, 147,106 and 207,225 Veterans had likely MCI and AD, respectively. From 2011 to 2018, yearly MCI prevalence increased from 0.9% to 2.2%; yearly AD prevalence slightly decreased from 2.4% to 2.1%; mild AD changed from 22.9% to 26.8%, moderate AD changed from 26.5% to 29.1%, and severe AD changed from 24.6% to 30.7% Conclusions: The relative distribution of AD severities was stable over time. Accurate prevalence estimation is critical for healthcare resource allocation and facilitating patients receiving innovative medicines.

Publisher

IOS Press

Reference13 articles.

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