Gipson, Katrina

ABSTRACT Objectives Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data. Methods The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age‐friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa. Results 999 participants were recruited from 5 EDs (3/25/2021–6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two‐thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity ( K = 0.73); excellent for sex ( K = 1.00), age ( K = 1.00), and race ( K = 0.98); fair for disposition ( K = 0.53); slight for ED observation status ( K = 0.33) and dementia diagnosis ( K = 0.24); poor for delirium presence ( K = 0.07). Conclusion In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. Choice of measures using these data should be driven by GED research questions.

ABSTRACT Background Existing risk scores assessing geriatric vulnerability in the emergency department (ED) have shown limited predictive power, especially in diverse populations. We investigated the relationship of a quick and easy‐to‐administer geriatric vulnerability scoring system with functional decline and mortality in older patients admitted to multiple hospitals through the ED in the United States (US) and Brazil (BR). Method Federated, international, multicenter observational study of hospitalized ED patients aged ≥ 65 from US and BR. The six criteria from the PRO‐AGE score (Physical impairment, Recent hospitalization, Older age [≥ 90], Acute mental alteration, Getting thinner, and Exhaustion; 0–8; higher scores = greater vulnerability) were assessed on admission. We used proportional hazards models to investigate the relationships between PRO‐AGE score groups and 90‐day mortality and functional decline, defined as new dependence in activities of daily living (ADL) and instrumental ADL (IADL), after adjusting for age, sex, race and ethnicity, education, Charlson comorbidity score, and study site. Death was considered a competing event for the functional decline outcome. Results A total of 1390 patients were included (US = 560; Brazil = 830). The 90‐day risk of death was higher for the upper compared with the lower (reference) PRO‐AGE group in both cohorts (US: HR = 11.76; 95% confidence interval [CI] = 2.56–54.04; BR: HR = 12.29; 95% CI = 3.54–42.59), whereas the risk of new 90‐day ADL disability was higher for upper (HR = 2.08; 95% CI = 1.21–3.56) and middle groups (HR = 2.10; 95% CI = 1.35–3.27) in the US but only the upper group in BR (HR = 1.70; 95% CI = 1.02–2.85). Conclusion A higher PRO‐AGE score was associated with mortality and functional decline in older ED patients admitted to hospitals in the US and BR, demonstrating its generalizability as a geriatric vulnerability risk score.