Faculty Bibliography

Background: Emergency department (ED) visits at end-of-life may cause financial strain and serve as a marker of inadequate access to community services and health care. We sought to examine end-of-life ED use, total healthcare spending, and out-of-pocket spending in a nationally representative sample. Methods: Using Medicare Current Beneficiary Survey data, we conducted a pooled cross-sectional analysis of Medicare beneficiaries aged 65+ years with a date of death between July 1, 2015 and December 31, 2021. Our primary outcomes were ED visits, total healthcare spending, and out-of-pocket spending in the 7, 30, 90, and 180 days preceding death. We estimated a series of zero-inflated negative binomial models identifying patient characteristics associated with the primary outcomes. Results: Among 3812 older adult decedents, 610 (16%), 1207 (31.7%), 1582 (41.5%), and 1787 (46.9%) Medicare beneficiaries had ED visits in the final 7, 30, 90, and 180 days, respectively, of life. For Medicare beneficiaries with at least one ED visit in the final 30 days of life, the median total and out-of-pocket costs were, respectively, $12,500 and $308, compared, respectively, with $278 and $94 for those without any ED visits (p < 0.001 for both comparisons). Having a diagnosis of dementia (odds ratio [OR] 0.71; 95% confidence interval [CI] 0.51"“0.99; p = 0.04) and being on hospice status during the year of death (OR 0.56; 95% CI 0.48"“0.66; p = <0.001) were associated with a decreased likelihood of having an ED visit. Having dementia was associated with a decreased likelihood of having any healthcare spending (OR 0.50; 95% CI 0.36"“0.71; p = 0.001) and any out-of-pocket spending (OR 0.51; 95% CI 0.36"“0.72; p = <0.001). Conclusions: One in three older adults visit the ED in the last month of life, and approximately one in two utilize ED services in the last half-year of life, with evidence of associated considerable total and out-of-pocket spending.

BACKGROUND:Geriatric emergency department (GED) guidelines endorse screening older patients for geriatric syndromes in the ED, but there have been significant barriers to widespread implementation. The majority of screening programs require engagement of a clinician, nurse, or social worker, adding to already significant workloads at a time of record-breaking ED patient volumes, staff shortages, and hospital boarding crises. Automated, electronic health record (EHR)-embedded risk stratification approaches may be an alternate solution for extending the reach of the GED mission by directing human actions to a smaller subset of higher risk patients. METHODS:We define the concept of automated risk stratification and screening using existing EHR data. We discuss progress made in three potential use cases in the ED: falls, cognitive impairment, and end-of-life and palliative care, emphasizing the importance of linking automated screening with systems of healthcare delivery. RESULTS:Research progress and operational deployment vary by use case, ranging from deployed solutions in falls screening to algorithmic validation in cognitive impairment and end-of-life care. CONCLUSIONS:Automated risk stratification offers a potential solution to one of the most pressing problems in geriatric emergency care: identifying high-risk populations of older adults most appropriate for specific GED care. Future work is needed to realize the promise of improved care with less provider burden by creating tools suitable for widespread deployment as well as best practices for their implementation and governance.

As the population ages, the prevalence of cognitive impairment due to neurodegenerative diseases such as Alzheimer disease (AD) is expected to double in the United States to nearly 14 million over the next 40 years. AD and related dementias (ADRD) are a leading cause of morbidity and mortality and among the costliest to society. Although emerging biomedical interventions for ADRD focus on early stages and are currently limited to AD, care management can benefit patients with ADRD across the disease course. Moreover, some causes of cognitive impairment are modifiable, and optimal overall management may slow or prevent additional decline. Nevertheless, a sizable proportion of cases of cognitive impairment among older adults remain undiagnosed. Primary care practitioners are often the first health care professionals to encounter cognitive concerns or to be able to observe changes in function resulting from cognitive impairment; hence, they have much to contribute to population health solutions for detecting cognitive impairment among older adults. In this report, we present key points and gaps in knowledge about methods for detecting cognitive impairment in primary care clinics. These were developed via an interdisciplinary Geriatrics Summit hosted by the National Academy of Neuropsychology in 2022, attended by representatives of national organizations engaged in work to improve care of older adults. We propose a novel workflow to facilitate detecting cognitive impairment during routine primary care, focusing on opportunities provided by the annual wellness visit, a preventive visit available to Medicare beneficiaries, along with additional recommendations and opportunities for clinical practice and research.

BACKGROUND/UNASSIGNED:Older adults treated in emergency departments (EDs) are at higher risk for adverse outcomes. Using multiple facilities can worsen this issue through service duplication and poor care transitions. Veterans with dual insurance coverage can access both Veterans Health Administration (VHA) and non-VHA EDs. This study aimed to identify factors associated with non-VHA ED use among veterans. METHODS/UNASSIGNED:We conducted a retrospective observational study of patients aged ≥ 65 who had primary care at the James J Peters VA Medical Center and at least one VHA or non-VHA ED visit between October 2017 and February 2020. Data were collected from the Veterans Affairs Corporate Data Warehouse and the Bronx Regional Health Information Exchange Organization. Generalized linear mixed models were used to examine factors influencing non-VHA ED use. RESULTS/UNASSIGNED:The study sample consisted of 3,897 veterans and a total of 13,312 ED visits. Compared to VHA-exclusive ED users, non-VHA ED users were more likely to live farther away (OR 1.04, CI 1.02 - 1.06) and seek care outside regular hours, including mornings (OR 1.61, CI 1.39 - 1.87), nights (OR 1.49, CI 1.33 - 1.66), weekends (OR 1.28, CI 1.16 - 1.42), and holidays (OR 1.32, CI 1.04 - 1.68). They were also more likely to present with emergency care sensitive conditions (OR 2.13, CI 1.90 - 2.37) and recent inpatient hospitalizations (OR 1.22, CI 1.05 - 1.41). CONCLUSION/UNASSIGNED:These findings suggested that distance and acuity are important predictors of non-VHA ED use in urban areas such as the Bronx, NY. Identifying veterans with key risk factors could improve care coordination and potentially reduce non-VHA ED use.

The objective of the study is to identify healthcare events leading to a diagnosis of dementia from a large real-world dataset. This study uses a data-driven approach to identify temporally ordered pairs and trajectories of healthcare codes in the electronic health record (EHR). This allows for discovery of novel temporal risk factors leading to an outcome of interest that may otherwise be unobvious. We identified several known (Down syndrome RR = 116.1, thiamine deficiency RR = 76.1, and Parkinson's disease RR = 41.1) and unknown (Brief psychotic disorder RR = 68.6, Toxic effect of metals RR = 40.4, and Schizoaffective disorders RR = 40.0) factors for a specific dementia diagnosis. The associations with the greatest risk for any dementia diagnosis were found to be primarily related to mental health (Brief psychotic disorder RR = 266.5, Dissociative and conversion disorders RR = 169.8), or neurologic conditions or procedures (Dystonia RR = 121.9, Lumbar Puncture RR = 119.0). Trajectory and clustering analysis identified factors related to cerebrovascular disorders, as well as diagnoses which increase the risk of toxic imbalances. The results of this study have the ability to provide valuable insights into potential patient progression towards dementia and improve recognition of patients at risk for developing dementia.

STUDY OBJECTIVE:We sought to describe diagnosis rates and compare common process outcomes between geriatric emergency departments (EDs) and nongeriatric EDs participating in the American College of Emergency Physicians Clinical Emergency Data Registry (CEDR). METHODS:We conducted an observational study of ED visits in calendar year 2021 within the CEDR by older adults. The analytic sample included 6,444,110 visits at 38 geriatric EDs and 152 matched nongeriatric EDs, with the geriatric ED status determined based on linkage to the American College of Emergency Physicians' Geriatric ED Accreditation program. Stratified by age, we assessed diagnosis rates (X/1000) for 4 common geriatric syndrome conditions and a set of common process outcomes including the ED length of stay, discharge rates, and 72-hour revisit rates. RESULTS:Across all age categories, geriatric EDs had higher diagnosis rates than nongeriatric EDs for 3 of the 4 following geriatric syndrome conditions of interest: urinary tract infection, dementia, and delirium/altered mental status. The median ED site-level length of stay for older adults was lower at geriatric EDs compared with that at nongeriatric EDs, whereas 72-hour revisit rates were similar across all age categories. Geriatric EDs exhibited a median discharge rate of 67.5% for adults aged 65 to 74 years, 60.8% for adults aged 75 to 84 years, and 55.6% for adults aged >85 years. Comparatively, the median discharge rate at nongeriatric ED sites was 69.0% for adults aged 65 to 74 years, 64.2% for adults aged 75 to 84 years, and 61.3% for adults aged >85 years. CONCLUSION:Geriatric EDs had higher geriatric syndrome diagnosis rates, lower ED lengths of stay, and similar discharge and 72-hour revisit rates when compared with nongeriatric EDs in the CEDR. These findings provide the first benchmarks for emergency care process outcomes in geriatric EDs compared with nongeriatric EDs.

BACKGROUND:Emergency department (ED) visits are common at the end-of-life, but the identification of patients with life-limiting illness remains a key challenge in providing timely and resource-sensitive advance care planning (ACP) and palliative care services. To date, there are no validated, automatable instruments for ED end-of-life screening. Here, we developed a novel electronic health record (EHR) prognostic model to screen older ED patients at high risk for 6-month mortality and compare its performance to validated comorbidity indices. METHODS:This was a retrospective, observational cohort study of ED visits from adults aged ≥65 years who visited any of 9 EDs across a large regional health system between 2014 and 2019. Multivariable logistic regression that included clinical and demographic variables, vital signs, and laboratory data was used to develop a 6-month mortality predictive model-the Geriatric End-of-life Screening Tool (GEST) using five-fold cross-validation on data from 8 EDs. Performance was compared to the Charlson and Elixhauser comorbidity indices using area under the receiver-operating characteristic curve (AUROC), calibration, and decision curve analyses. Reproducibility was tested against data from the remaining independent ED within the health system. We then used GEST to investigate rates of ACP documentation availability and code status orders in the EHR across risk strata. RESULTS:A total of 431,179 encounters by 123,128 adults were included in this study with a 6-month mortality rate of 12.2%. Charlson (AUROC (95% CI): 0.65 (0.64-0.69)) and Elixhauser indices (0.69 (0.68-0.70)) were outperformed by GEST (0.82 (0.82-0.83)). GEST displayed robust performance across demographic subgroups and in our independent validation site. Among patients with a greater than 30% mortality risk using GEST, only 5.0% had ACP documentation; 79.0% had a code status previously ordered, of which 70.7% were full code. In decision curve analysis, GEST provided greater net benefit than the Charlson and Elixhauser scores. CONCLUSIONS:Prognostic models using EHR data robustly identify high mortality risk older adults in the ED for whom code status, ACP, or palliative care interventions may be of benefit. Although all tested methods identified patients approaching the end-of-life, GEST was most performant. These tools may enable resource-sensitive end-of-life screening in the ED.