Background/Objectives No data exist regarding the validity of International Classification of Disease (ICD)‐10 dementia diagnoses against a clinician‐adjudicated reference standard within Medicare claims data. We examined the accuracy of claims‐based diagnoses with respect to expert clinician adjudication using a novel database with individual‐level linkages between electronic health record (EHR) and claims. Design In this retrospective observational study, two neurologists and two psychiatrists performed a standardized review of patients' medical records from January 2016 to December 2018 and adjudicated dementia status. We measured the accuracy of three claims‐based definitions of dementia against the reference standard. Setting Mass‐General‐Brigham Healthcare (MGB), Massachusetts, USA. Participants From an eligible population of 40,690 fee‐for‐service (FFS) Medicare beneficiaries, aged 65 years and older, within the MGB Accountable Care Organization (ACO), we generated a random sample of 1002 patients, stratified by the pretest likelihood of dementia using administrative surrogates. Intervention None. Measurements We evaluated the accuracy (area under receiver operating curve [AUROC]) and calibration (calibration‐in‐the‐large [CITL] and calibration slope) of three ICD‐10 claims‐based definitions of dementia against clinician‐adjudicated standards. We applied inverse probability weighting to reconstruct the eligible population and reported the mean and 95% confidence interval (95% CI) for all performance characteristics, using 10‐fold cross‐validation (CV). Results Beneficiaries had an average age of 75.3 years and were predominately female (59%) and non‐Hispanic whites (93%). The adjudicated prevalence of dementia in the eligible population was 7%. The best‐performing definition demonstrated excellent accuracy (CV‐AUC 0.94; 95% CI 0.92–0.96) and was well‐calibrated to the reference standard of clinician‐adjudicated dementia (CV‐CITL <0.001, CV‐slope 0.97). Conclusion This study is the first to validate ICD‐10 diagnostic codes against a robust and replicable approach to dementia ascertainment, using a real‐world clinical reference standard. The best performing definition includes diagnostic codes with strong face validity and outperforms an updated version of a previously validated ICD‐9 definition of dementia.

IMPORTANCE Neighborhood disadvantage is a novel social determinant of health that could adversely affect the functional well-being of older persons. Deficiencies in resource-poor environments can potentially be addressed through social and public health interventions. OBJECTIVE To evaluate whether estimates of active and disabled life expectancy differ on the basis of neighborhood disadvantage after accounting for individual-level socioeconomic characteristics and other prognostic factors. DESIGN, SETTING, AND PARTICIPANTS This prospective longitudinal cohort study included 754 nondisabled community-living persons, aged 70 years or older, who were members of the Precipitating Events Project in south central Connecticut from March 1998 to June 2020.MAIN OUTCOMES AND MEASURES Disability in 4 essential activities of daily living (bathing, dressing, walking, and transferring) was assessed each month. Scores on the Area Deprivation Index, a census-based socioeconomic measure with 17 education, employment, housing quality, and poverty indicators, were obtained through linkages with the 2000 Neighborhood Atlas. Area Deprivation Index scores were dichotomized at the 80th state percentile to distinguish neighborhoods that were disadvantaged (81-100) from those that were not (1-80). RESULTS Among the 754 participants, the mean (SD) age was 78.4 (5.3) years, and 487 (64.6%) were female. Within 5-year age increments from 70 to 90, active life expectancy was consistently lower in participants from neighborhoods that were disadvantaged vs not disadvantaged, and these differences persisted and remained statistically significant after adjustment for individual-level race and ethnicity, education, income, and other prognostic factors. At age 70 years, adjusted estimates (95% CI) for active life expectancy (in years) were 12.3 (11.5-13.1) in the disadvantaged group and 14.2 (13.5-14.7) in the nondisadvantaged group. At each age, participants from disadvantaged neighborhoods spent a greater percentage of their projected remaining life disabled, relative to those from nondisadvantaged neighborhoods, with adjusted values (SE) ranging from 17.7 (0.8) vs 15.3 (0.5) at age 70 years to 55.0 (1.7) vs 48.1 (1.3) at age 90 years. CONCLUSIONS AND RELEVANCEIn this prospective longitudinal cohort study, living in a disadvantaged neighborhood was associated with lower active life expectancy and a greater percentage of projected remaining life with disability. By addressing deficiencies in resource-poor environments, new or expanded social and public health initiatives have the potential to improve the functional well-being of community-living older persons and, in turn, reduce health disparities in the US.

Background: Prior to national spread, the Department of Veterans Affairs implemented a pilot of the life-sustaining treatment decisions initiative (LSTDI) to promote proactive goals of care conversations (GoCC) with seriously ill patients, including policy and practice standards, an electronic documentation template and order set, and implementation support. Aim: To describe a 2-year pilot of the LSTDI at 4 demonstration sites. Design: Prospective observational study. Setting/Participants: A total of 6664 patients who had at least one GoCC. Results: Descriptive statistics characterized patient demographics, goals of care, LST decisions, and risk of hospitalization or mortality among patients with at least one GoCC. Participants were on average 71.4 years old, 93.2% male, 87.1% white, and 64.7% urban; 27.3% died by the end of the pilot period. Fifteen percent lacked decision-making capacity (DMC). Nonmutually exclusive goals included to be cured (7.6%), to prolong life (34%), to improve/maintain quality of life (61.5%), to be comfortable (53%), to obtain support for family/caregiver (8.4%), to achieve life goals (2.1%), and other (10.5%). Many GoCCs resulted in a do not resuscitate (DNR) order (58.8%). Patients without DMC were more likely to have comfort-oriented goals (77.3% vs 48.8%) and a DNR (84% vs 52.6%). Chart abstraction supported content validity of GoCC documentation. Conclusion: The pilot demonstrated that standardizing practices for eliciting and documenting GoCCs resulted in customized documentation of goals of care and LST decisions of a large number of seriously ill patients and established the feasibility of spreading standardized practices throughout a large integrated health care system.

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Background Capturing frailty within administrative claims data may help to identify high-risk patients and inform population health management strategies. Although it is common to ascertain frailty status utilizing claims-based surrogates (e.g. diagnosis and health service codes) selected according to clinical knowledge, the accuracy of this approach has not yet been examined. We evaluated the accuracy of claims-based surrogates against two clinical definitions of frailty. Methods This cross-sectional study was conducted in a Health and Retirement Study subsample of 3097 participants, aged 65 years or older and with at least 12-months of continuous fee-for-service Medicare enrollment. We defined 18 previously utilized claims-based surrogates of frailty from Medicare data and evaluated each against clinical reference standards, ascertained from a direct examination: a deficit accumulation frailty index (FI) (range: 0–1) and frailty phenotype. We also compared the accuracy of the total count of 18 claims-based surrogates with that of a validated claims-based FI model, comprised of 93 claims-based variables. Results 19% of participants met clinical criteria for the clinical frailty phenotype. The mean clinical FI for our sample was 0.20 (standard deviation 0.13). Hospital Beds and associated supplies was the claims-based surrogate associated with the highest clinical FI (mean FI 0.49). Claims-based surrogates had low sensitivity ranging from 0.01 (cachexia, adult failure to thrive, anorexia) to 0.38 (malaise and fatigue) and high specificity ranging from 0.79 (malaise and fatigue) to 0.99 (cachexia, adult failure to thrive, anorexia) in discriminating the clinical frailty phenotype. Compared with a validated claims-based FI, the total count of claims-based surrogates demonstrated lower Spearman correlation with the clinical FI (0.41 [95% CI 0.38–0.44] versus 0.59 [95% CI, 0.56–0.61]) and poorer discrimination of the frailty phenotype (C-statistics 0.68 [95% CI, 0.66–0.70] versus 0.75 [95% CI, 0.73–0.77]). Conclusions Claims-based surrogates, selected according to clinical knowledge, do not accurately capture frailty in Medicare claims data. A simple count of claims-based surrogates improves accuracy but remains inferior to a claims-based FI model.