Restricted accessResearch articleFirst published online 2016-8-23
Identification of Physician-Diagnosed Alzheimer’s Disease and Related Dementias in Population-Based Administrative Data: A Validation Study Using Family Physicians’ Electronic Medical Records
Background: Population-based surveillance of Alzheimer’s and related
dementias (AD-RD) incidence and prevalence is important for chronic disease management and
health system capacity planning. Algorithms based on health administrative data have been
successfully developed for many chronic conditions. The increasing use of electronic
medical records (EMRs) by family physicians (FPs) provides a novel reference standard by
which to evaluate these algorithms as FPs are the first point of contact and providers of
ongoing medical care for persons with AD-RD.
Objective: We used FP EMR data as the reference standard to evaluate the
accuracy of population-based health administrative data in identifying older adults with
AD-RD over time.
Methods: This retrospective chart abstraction study used a random sample of
EMRs for 3,404 adults over 65 years of age from 83 community-based FPs in Ontario, Canada.
AD-RD patients identified in the EMR were used as the reference standard against which
algorithms identifying cases of AD-RD in administrative databases were compared.
Results: The highest performing algorithm was “one hospitalization code OR
(three physician claims codes at least 30 days apart in a two year period) OR a
prescription filled for an AD-RD specific medication” with sensitivity 79.3% (confidence
interval (CI) 72.9–85.8%), specificity 99.1% (CI 98.8–99.4%), positive predictive value
80.4% (CI 74.0–86.8%), and negative predictive value 99.0% (CI 98.7–99.4%). This resulted
in an age- and sex-adjusted incidence of 18.1 per 1,000 persons and adjusted prevalence of
72.0 per 1,000 persons in 2010/11.
Conclusion: Algorithms developed from health administrative data are
sensitive and specific for identifying older adults with AD-RD.
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