Dementia in health claims data: The influence of different case definitions on incidence and prevalence estimates

Abstract

Objectives: The epidemiology of dementia subtypes including Alzheimer's disease (AD) and vascular dementia (VD) and their reliance on different case definitions ("algorithms") in health claims data are still understudied.

Methods: Based on health claims data, prevalence estimates (per 100 persons), incidence rates (IRs, per 100 person-years), and proportions of AD, VD, and other dementias (oD) were calculated. Five algorithms of increasing strictness considered inpatient/outpatient diagnoses (#1, #2), antidementia drugs (#3) or supportive diagnostics (#4, #5).

Results: Algorithm 1 detected 213,409 cases (#2: 197,400; #3: 48,688; #4: 3033; #5: 3105), a prevalence for any dementia of 3.44 and an IR of 1.39 (AD: 0.80/0.21, VD: 0.79/0.31). The prevalence decreased by algorithms for any dementia (#2: 3.19; #3: 0.75; #4: 0.04; #5: 0.05) as did IRs (#2: 1.13; #3: 0.18; #4: 0.05, #5: 0.05). Algorithms 1-2, and 4-5 revealed similar proportions of AD (23.3%-26.6%), VD (19.9%-23.2%), and oD (53.1%-53.8%), algorithm 3 estimated 45% (AD), 12.1% (VD), and 43.0% (oD).

Conclusions: Health claims data show lower estimates of AD than previously reported, due to markedly lower prevalent/incident proportions of patients with corresponding codes. Using medication in defining dementia potentially improves estimating the proportion of AD while supportive diagnostics were of limited use.

Keywords: Alzheimer's disease; dementia; epidemiology; health claims data; vascular dementia.