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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 1 of 1 Research Studies DisplayedColey RY, Smith JJ, Karliner L RY, Smith JJ, Karliner L
External validation of the eRADAR risk score for detecting undiagnosed dementia in two real-world healthcare systems.
Drupal date: Feb, 2023
It is estimated that half of the individuals with dementia remain undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was designed to detect older adults at risk of undiagnosed dementia using routinely gathered clinical information. The purpose of this retrospective cohort study was to externally validate eRADAR in two real-world healthcare systems, examining its performance over time and across race/ethnicity. The study found a total of 7631 dementia diagnoses were observed at KPWA and 216 at UCSF. The area under the curve was 0.84 (95% confidence interval: 0.84-0.85) at KPWA and 0.79 (0.76-0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53-56%) at KPWA and 44% (38-51%) at UCSF. Performance was consistent over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (although small samples limited precision in some groups). The study concluded that eRADAR demonstrated strong external validity for identifying undiagnosed dementia in two healthcare systems with diverse patient populations and varying availability of external healthcare data for risk calculations. This study showed that eRADAR is generalizable from a research sample to real-world clinical populations, transportable across health systems, resilient to temporal changes in healthcare, and exhibits similar performance across major racial/ethnic groups.
It is estimated that half of the individuals with dementia remain undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was designed to detect older adults at risk of undiagnosed dementia using routinely gathered clinical information. The purpose of this retrospective cohort study was to externally validate eRADAR in two real-world healthcare systems, examining its performance over time and across race/ethnicity. The study found a total of 7631 dementia diagnoses were observed at KPWA and 216 at UCSF. The area under the curve was 0.84 (95% confidence interval: 0.84-0.85) at KPWA and 0.79 (0.76-0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53-56%) at KPWA and 44% (38-51%) at UCSF. Performance was consistent over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (although small samples limited precision in some groups). The study concluded that eRADAR demonstrated strong external validity for identifying undiagnosed dementia in two healthcare systems with diverse patient populations and varying availability of external healthcare data for risk calculations. This study showed that eRADAR is generalizable from a research sample to real-world clinical populations, transportable across health systems, resilient to temporal changes in healthcare, and exhibits similar performance across major racial/ethnic groups.
AHRQ-funded; HS026369.
Citation: Coley RY, Smith JJ, Karliner L RY, Smith JJ, Karliner L .
External validation of the eRADAR risk score for detecting undiagnosed dementia in two real-world healthcare systems.
J Gen Intern Med 2023 Feb; 38(2):351-60. doi: 10.1007/s11606-022-07736-6..
Keywords: Dementia, Neurological Disorders, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT)