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. 2019 Nov;15(11):1412-1419.
doi: 10.1016/j.jalz.2019.06.4945. Epub 2019 Sep 25.

Differences in service utilization at an urban tribal health organization before and after Alzheimer's disease or related dementia diagnosis: A cohort study

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Differences in service utilization at an urban tribal health organization before and after Alzheimer's disease or related dementia diagnosis: A cohort study

Krista R Schaefer et al. Alzheimers Dement. 2019 Nov.

Abstract

Introduction: The prevalence, mortality, and healthcare impact of Alaska Native and American Indian (ANAI) people with Alzheimer's disease and related dementias (ADRD) are unknown.

Methods: We conducted a cohort study of electronic health record data that compared healthcare service utilization in patients with and without an ADRD diagnosis. Zero-inflated negative binomial regression with robust standard errors was used to estimate utilization rates.

Results: Compared with patients without ADRD, utilization rates were similar before but higher after ADRD diagnosis. For those with diagnosed ADRD, utilization increased gradually over time with sharp upward change during the year of diagnosis.

Discussion: This is the only study quantifying changes in healthcare service utilization before and after ADRD diagnosis among ANAI people, which is crucial for tailoring geriatric care for ANAI populations.

Keywords: Alaska Native; Alzheimer disease; American Indian; Delivery of healthcare; Dementia; Geriatrics; Health services.

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Figures

Figure 1.
Figure 1.
Patient eligibility flow chart from EHR to study sample
Figure 2.
Figure 2.
Average adjusted prediction* for primary care visits per year according to time since ADRD diagnosis * Calculated from zero-inflated negative binomial model with robust standard error estimation; adjusted for age, gender, and an indicator for death during the observation period (2011–2017)
Figure 3.
Figure 3.
Average adjusted prediction* for other healthcare visits per year according to time since ADRD diagnosis * Calculated from zero-inflated negative binomial model with robust standard error estimation; adjusted for age, gender, and an indicator for death during the observation period (2011–2017)

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