Healthcare Utilization Among Veterans with Alzheimer's Disease Identified from Clinical Notes
Speaker(s)
Aguilar BJ1, Li M2, Wang Y2, Morin PJ3, Berlowitz D4, Tahami A5, Zhang Q6, Xia W3
1Veterans Affairs Bedford, Bedford, MA, USA, 2Bentley University, Waltham, MA, USA, 3Boston University, Boston, MA, USA, 4University of Massachusetts Lowell, Lowell, MA, USA, 5Eisai, Inc, Nutley, NJ, USA, 6Eisai, Inc, woodcliff lake, NJ, USA
Presentation Documents
OBJECTIVES: To assess healthcare utilization among Veterans with Alzheimer's disease (AD) in the Department of Veterans Affairs (VA) healthcare system.
METHODS: Veterans with AD were identified from clinical notes in the VA electronic health record. A control group was propensity score matched on age, sex, and race. Healthcare utilization was assessed one year before and two years after AD index date. A linear mixed-effects model was used to compare hospitalizations and outpatient visits, adjusting for patient demographics and select comorbidities.
RESULTS: The AD and control group included 21,442 and 85,684 Veterans, respectively. Annual outpatient visits were roughly 2.3-2.8 times greater in the AD group than the control group during the 3-year study period. Annual hospitalization rates for AD and control groups were comparable. However, the average length of stay for AD patients was 1.8-2.1 times longer than control. The mixed-effects model showed significantly increased hospitalizations and outpatient visits (p<0.001) in the AD group compared to control, after controlling for age, sex, race, ethnicity, and select comorbidities.
CONCLUSIONS: Healthcare utilization of AD patients identified via clinical notes is higher than the matched control group. Identification of AD patients via clinical notes is a viable method for patient identification. Incorporation of clinical notes with diagnostic codes such as International Classification of Diseases may address issues related to undercoding and produce more comprehensive patient registries.
Code
SA33
Topic
Study Approaches
Topic Subcategory
Electronic Medical & Health Records
Disease
Geriatrics, Mental Health (including addition), Neurological Disorders