The electronic health record Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) Brain Health Trial: Protocol for an embedded, pragmatic clinical trial of a low-cost dementia detection algorithm.

BACKGROUND: About half of people living with dementia have not received a diagnosis, delaying access to treatment, education, and support. We previously developed a tool, eRADAR, which uses information in the electronic health record (EHR) to identify patients who may have undiagnosed dementia. This paper provides the protocol for an embedded, pragmatic clinical trial (ePCT) implementing eRADAR in two healthcare systems to determine whether an intervention using eRADAR increases dementia diagnosis rates and to examine the benefits and harms experienced by patients and other stakeholders. METHODS: We will conduct an ePCT within an integrated healthcare system and replicate it in an urban academic medical center. At primary care clinics serving about 27,000 patients age 65 and above, we will randomize primary care providers (PCPs) to have their patients with high eRADAR scores receive targeted outreach (intervention) or usual care. Intervention patients will be offered a "brain health" assessment visit with a clinical research interventionist mirroring existing roles within the healthcare systems. The interventionist will make follow-up recommendations to PCPs and offer support to newly-diagnosed patients. Patients with high eRADAR scores in both study arms will be followed to identify new diagnoses of dementia in the EHR (primary outcome). Secondary outcomes include healthcare utilization from the EHR and patient, family member and clinician satisfaction assessed through surveys and interviews. CONCLUSION: If this pragmatic trial is successful, the eRADAR tool and intervention could be adopted by other healthcare systems, potentially improving dementia detection, patient care and quality of life.

External Validation of the eRADAR Risk Score for Detecting Undiagnosed Dementia in Two Real-World Healthcare Systems.

BACKGROUND: Fifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data. OBJECTIVE: To externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity. DESIGN: Retrospective cohort study PARTICIPANTS: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication. MAIN MEASURES: Performance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months. KEY RESULTS: A total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). 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 similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups). CONCLUSIONS: eRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups.

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

OBJECTIVES: Early recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]). DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Washington (KPWA), an integrated healthcare delivery system. PARTICIPANTS: A total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples. MEASUREMENTS: EHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills). RESULTS: Overall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia. CONCLUSION: The eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019.

Making Function Part of the Conversation: Clinician Perspectives on Measuring Functional Status in Primary Care.

OBJECTIVES: Although there is increasing interest in using functional status to guide clinical decision making, function is seldom routinely assessed in primary care. We explored clinician perspectives on barriers and facilitators to routine measurement of older adults' functional status in primary care settings. DESIGN: Qualitative study using semistructured interviews. SETTING: Primary care and geriatrics clinics at six Veterans Affairs Medical Centers. PARTICIPANTS: Twenty-four primary care providers, including 17 from primary care clinics and 7 from geriatrics clinics. MEASUREMENTS: We conducted interviews to elicit clinician perspectives about functional status measurement, including barriers and facilitators to routine assessment. We analyzed transcripts iteratively using a hybrid inductive and deductive thematic approach. RESULTS: Interviews revealed three distinct aspects to measuring function: screening and assessment, documentation, and use of data to inform care. Barriers and facilitators to screening and assessment included time availability, clinic processes, and degree of interdisciplinary environment. Barriers and facilitators to documentation included the usability and integration of electronic instruments into workflows and the availability of a standardized location to document function in the electronic medical record. Barriers and facilitators to use of data included the availability of a standardized location to retrieve data on function, the availability of appropriate referrals and services, and provider knowledge of available resources to address functional impairments. To address these barriers, providers emphasized the critical importance of connecting measurement of function directly to improved patient care. CONCLUSION: Although clinicians emphasized the importance of measuring function, they also cautioned against additional workload burdens, cumbersome electronic documentation, and measurement of function without ensuring that these data are used to improve care. Approaches to functional status measurement must address these barriers to improve care and outcomes for older adults. J Am Geriatr Soc 67:493-502, 2019.

Impact of age and comorbidity on colorectal cancer screening among older veterans.

BACKGROUND: The Veterans Health Administration, the American Cancer Society, and the American Geriatrics Society recommend colorectal cancer screening for older adults unless they are unlikely to live 5 years or have significant comorbidity that would preclude treatment. OBJECTIVE: To determine whether colorectal cancer screening is targeted to healthy older patients and is avoided in older patients with severe comorbidity who have life expectancies of 5 years or less. DESIGN: Cohort study. SETTING: Veterans Affairs (VA) medical centers in Minneapolis, Minnesota; Durham, North Carolina; Portland, Oregon; and West Los Angeles, California, with linked national VA and Medicare administrative claims. PATIENTS: 27 068 patients 70 years or older who had an outpatient visit at 1 of 4 VA medical centers in 2001 or 2002 and were due for screening. MEASUREMENTS: The main outcome was receipt of fecal occult blood testing (FOBT), colonoscopy, sigmoidoscopy, or barium enema in 2001 or 2002, on the basis of national VA and Medicare claims. Charlson-Deyo comorbidity scores at the start of 2001 were used to stratify patients into 3 groups ranging from no comorbidity (score of 0) to severe comorbidity (score > or =4), and 5-year mortality was determined for each group. RESULTS: 46% of patients were screened from 2001 through 2002. Only 47% of patients with no comorbidity were screened despite having life expectancies greater than 5 years (5-year mortality, 19%). Although the incidence of screening decreased with age and worsening comorbidity, it was still 41% for patients with severe comorbidity who had life expectancies less than 5 years (5-year mortality, 55%). The number of VA outpatient visits predicted screening independent of comorbidity, such that patients with severe comorbidity and 4 or more visits had screening rates similar to or higher than those of healthier patients with fewer visits. LIMITATIONS: Some tests may have been performed for nonscreening reasons. The generalizability of findings to persons who do not use the VA system is uncertain. CONCLUSION: Advancing age was inversely associated with colorectal cancer screening, whereas comorbidity was a weaker predictor. More attention to comorbidity is needed to better target screening to older patients with substantial life expectancies and avoid screening older patients with limited life expectancies. primary funding source: VA Health Services Research and Development.