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BackgroundFifty 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.ObjectiveTo externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity.DesignRetrospective 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 measuresPerformance 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 resultsA 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).ConclusionseRADAR 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.

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. [ABSTRACT FROM AUTHOR]

Background. Between 1995 and 1998, tribally owned Southcentral Foundation (SCF) incrementally assumed responsibility from the Indian Health Service (IHS) for primary care services on the Alaska Native Medical Center (ANMC) campus in Anchorage, Alaska. In 1999, SCF began implementing components of a Patient- Centered Medical Home (PCMH) model to improve access and continuity of care. Objective. To evaluate hospitalisation trends before, during and after PCMH implementation. Design. Time series analysis of aggregated medical record data. Methods. Regression analysis with correlated errors was used to estimate trends over time for the percent of customer-owners hospitalised overall and for specific conditions during 4 time periods (March 1996-July 1999: SCF assumes responsibility for primary care; August 1999-July 2000: PCMH implementation starts; August 2000-April 2005: early post-PCMH implementation; May 2005-December 2009: later post-PCMH implementation). Analysis was restricted to individuals residing in Southcentral Alaska and receiving health care at ANMC. Results. The percent of SCF customer-owners hospitalised per month for any reason was steady before and during PCMH implementation, declined steadily immediately following implementation and subsequently stabilised. The percent hospitalised per month for unintentional injury or poisoning also declined during and after the PCMH implementation. Among adult asthma patients, the percent hospitalised annually for asthma declined prior to and during implementation and remained lower thereafter. The percent of heart failure patients hospitalised annually for heart failure remained relatively constant throughout the study period while the percent of hypertension patients hospitalised for hypertension shifted higher between 1999 and 2002 compared to earlier and later years. Conclusion. Implementation of PCMH at SCF was accompanied by decreases in the percent of customerowners hospitalised monthly for any reason and for unintentional injury and in the percent of asthma patients hospitalised annually for asthma. Increased accessibility to empanelled care teams may have contributed to decreased need for hospitalisation. [ABSTRACT FROM AUTHOR]

Background. Recent reports indicate a decline in rates of Fetal Alcohol Syndrome (FAS) among Alaska Native and American Indian (AN/AI) infants. Nevertheless, AN/AI infants remain disproportionately impacted by the effects of prenatal alcohol exposure. Methods. AN/AI pregnant women in their 3rd trimester completed a questionnaire on demographic data and the amount and frequency of their alcohol consumption in the month prior to conception and during pregnancy. Differences across demographics and trimesters were tested with the Chi-square, Fisher's exact or McNemar's test as appropriate. Results. Of the 125 participants, 56% (n=71) reported no alcohol consumption in the 1st through 3rd trimesters of pregnancy; 30% (n=38) of the 125 participants also reported no alcohol consumption in the month before pregnancy. Of the 43% (n=54) who reported consuming alcohol during pregnancy (1st, 2nd and/or 3rd trimester), most (35%) reported alcohol use only in the 1st trimester. Binge drinking in the 1st or 2nd trimester was reported amongst 20% (n=25) of participants with an additional 18% (n=29) reporting binge drinking in the month prior to pregnancy. Women who reported pre-conception binge drinking were significantly more likely to report binge drinking during their 1st trimester (pB0.0001) and 2nd trimester (pB0.0001). A history of tobacco use (p=0.0403) and cigarette smoking during pregnancy (pB0.0001) were also associated with binge drinking during pregnancy. Conclusion. Among study participants, reported use of alcohol was primarily limited to pre-conception and the 1st trimester, with a dramatic decrease in the 2nd and 3rd trimesters. Prevention programmes, such as the Alaska FAS Prevention Project, may have contributed to observed decreases in the 2nd and 3rd trimesters. Additional study and focus on pre-conception, the 1st trimester and binge drinking, as well as tobacco use might augment Fetal Alcohol Spectrum Disorder prevention efforts. [ABSTRACT FROM AUTHOR]