Faculty Bibliography

OBJECTIVES/OBJECTIVE: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/CONCLUSIONS: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.

BACKGROUND:Care transitions from the emergency department (ED) to the community represent a critical period that can significantly impact clinical outcomes of older adults, yet there is a lack of standardized tools to measure patient-reported experiences and outcomes during this transition. Our objective was to develop and validate the Patient-Reported Outcome Measure-Older adult care Transitions in the ED (PROM-OTED) tool to measure care transition outcomes within 4-10 days after ED discharge. METHODS:Older adults (65+ years) discharged from four EDs were enrolled between November 2021 and April 2024 in a multiphase process: qualitative interviews, item generation, member checking, cognitive debriefing, technical expert panel review, and psychometric evaluation and validation. We employed descriptive statistics, item analysis, interitem correlation, and factor analyses to assess the tool's validity and reliability. RESULTS:Across all phases, we enrolled 290 older adults. The final 18-item PROM-OTED tool included items that addressed understanding of discharge instructions, medication management, follow-up care, and quality of life. The tool demonstrated feasibility with a mean (±SD) completion time of 4.97 (±3.04) min and was able to be administered electronically or via telephone. The tool additionally demonstrated excellent internal consistency (Cronbach's alpha 0.9376, McDonald's omega 0.9988) and good test-retest reliability (r = 0.8437). Exploratory factor analysis supported a robust factor structure and significant correlations between the PROM-OTED tool with the Care Transitions Measure-3, a general measure of hospital discharge quality of care, support its concurrent validity. CONCLUSIONS:The PROM-OTED tool is a reliable and preliminarily valid instrument for use during the immediate post-ED period, with potential clinical applications in enhancing discharge practices and assessing care transition outcomes of older adults during observational or interventional studies.

INTRODUCTION/UNASSIGNED:The rapidly ageing population and multimorbidity are associated with increased emergency department (ED) visits by older adults. In the ED, older adults have higher risk of hospitalization, functional and cognitive decline, and mortality. Boarding, holding admitted patients in the ED awaiting a hospital bed, exacerbates these negative outcomes, which disproportionately affect older adults. METHODS/UNASSIGNED:We conducted a cross-sectional analysis to investigate US boarding trends by age using clinical administrative data from 5 health systems and publicly available NHAMCS data from 2018 to 2024. RESULTS/UNASSIGNED:Boarding ≥3 h in the ED has increased across diverse hospital types, with oldest adults (85+) facing the greatest risk (System 4: IRR [95% CI] = 1.18 [1.15-1.20], System 5: IRR [95% CI] = 1.20 [1.17-1.23], System 3 [Community Hospital]: IRR [95% CI] = 1.25 [1.19-1.33]). These results were recapitulated at the national level in NHAMCS (IRR [95% CI] = 1.30 [1.05-1.61]). DISCUSSION/UNASSIGNED:The trend of increased boarding has serious implications for patients, caregivers, and health systems. The 2025 CMS Age-Friendly Hospital Measure offers opportunities to improve processes and procedures to mitigate the negative effects of hospital boarding on older patients. We highlight opportunities to address this challenge, including ongoing quality improvement initiatives, bed prioritization algorithms, and alternate admission pathways.

INTRODUCTION/BACKGROUND:The study aimed to develop and validate the Emergency Department Dementia Algorithm (EDDA) to detect dementia among older adults (65+) and support clinical decision-making in the emergency department (ED). METHODS:In a multisite retrospective study of 759,665 ED visits, electronic health record data from Yale New Haven Health (2014-2022) were used to train three supervised and semi-unsupervised positive-unlabeled machine learning models (XGBoost, Random Forest, LASSO). A separate test set of 400 ED encounters underwent adjudicated chart review for validation. RESULTS:EDDA achieved an area under the receiver-operating characteristic curve (AUROC) of 0.85 in the test set and 0.93 in the validation set. Positive-unlabeled learning improved performance. Agreement between EDDA and clinician-adjudicated dementia diagnoses was moderate (kappa = 0.50), with 17% of EDDA-positive patients having undiagnosed probable dementia. DISCUSSION/CONCLUSIONS:EDDA enhances dementia detection in the ED, with potential for real-time implementation to improve patient outcomes and care transitions. HIGHLIGHTS/CONCLUSIONS:Developed a machine learning algorithm using electronic health record data to detect dementia in the emergency department (ED). Algorithm designed to balance detection accuracy with ease of ED implementation. Parsimonious model with limited but predictive variables selected for rapid ED use. Focused on real-time application, optimizing ED workflows, and clinician support. Aims to enhance ED dementia detection, patient safety, and care coordination.

Persons Living with Dementia (PLWD), diagnosed or undiagnosed, have high Emergency Department (ED) use. Identification of such patients poses significant challenges for emergency clinicians with considerable downstream implications on patients, care partners, and healthcare systems. With the advent of Geriatric Emergency Departments (GEDs) there is an opportunity to understand and improve care of PLWDs in EDs with effective allocation of resources and the development of novel techniques to better support detecting those at risk, communicating findings, and coordinating care for such patients. Advances have been made leveraging Electronic Health Record (EHR) data to risk stratify patients for dementia in the hope that those at high-risk may benefit from further evaluation. The promise of multiple blood-base biomarkers (BBM) as a future modality to improve detection of those at risk of dementias, will also have the potential to advance the delivery of care of PLWD and their care partners in EDs. HIGHLIGHTS: EDs have an integral role in delivering care for Person Living with Dementia and their care partners. High acuity and fast paced ED environment and other barriers makes it difficult to identify Person Living with Dementia. EHR-based risk stratification algorithms can identify patients at risk for Dementia in ED and outpatient settings. Use of Blood-Based Biomarkers in the ED setting is novel and considerations of its use and implications need to be studied. EHR based risk stratification algorithm and Blood Based Biomarkers when used judiciously have the potential to overcome some of the known barriers to identify and improve care for Person Living with Dementia as they transition through EDs.

A core tenant of the Geriatric Emergency care Applied Research Network 2.0-Advancing Dementia Care (GEAR 2.0-ADC) is the inclusion of community members during all stages of clinical research. As such, we deliberately integrated and supported patient and public involvement in the evaluation and selection of GEAR 2.0-ADC Pilot Research Grants by developing and adapting traditional grant application review structures, with input from community members, to create the GEAR 2.0-ADC Community Review Committee approach. Community members, including persons living with dementia, effectively participated in all three rounds of research grant application review and selection, complementing the traditional scientific review process. The structure and flexibility of the GEAR 2.0-ADC Community Review Committee approach serve as a model for patient and public grant application review involvement with strong potential for applications across grant reviews in other medical specialties.

INTRODUCTION/BACKGROUND:Cognitive impairment (CI) is under-recognized by emergency department (ED) clinicians, and processes for cognitive screening and outpatient referrals are limited. METHODS:This pilot study tested the feasibility of ED clinicians referring older adult patients identified through CI screening and direct clinician referral for outpatient cognitive evaluation. Telephone interviews and chart reviews were conducted on 100 patients about their emergency care, cognitive function, and referral status. RESULTS:A total of 9359 ED patients were screened for memory and thinking problems, with 650 (6.9%) reporting such issues. A total of 100 patients were discharged and referred for outpatient cognitive evaluation, consisting of 37 referred from screening and 67 through direct clinician referral. Of these, 26 (26.0%) scheduled and 19 (19.0%) completed outpatient evaluations within 100 days. Fifteen (78.9%) were formally diagnosed with dementia, CI, or memory loss. DISCUSSION/CONCLUSIONS:ED clinicians are able to identify and appropriately refer older patients with CI for outpatient evaluation. Future studies can improve referral rates with solutions addressing detection and follow-up challenges. HIGHLIGHTS/CONCLUSIONS:Screening for cognitive impairment and outpatient referral for cognitive evaluation is feasible in the emergency department. Nearly 80% of patients who completed follow-up were diagnosed with cognitive impairment, including probable dementia and Alzheimer's disease. Significant gaps and barriers remain in maintaining outpatient follow-up from initial referral from the emergency department, with less than one in five patients completing outpatient evaluations.

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/METHODS: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/CONCLUSIONS: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.