James Francis Burke

Objectives: Interhospital transfer is essential for accessing specialized critical care services, yet it poses clinical risk and substantial burden for patients and the healthcare system. Tele-critical care (TCC) programs extend expertise to resource-limited hospitals and may influence transfer decisions by identifying patients requiring escalation or supporting local management. We examined the association between TCC capability at index ICU hospitalizations, interhospital transfer, and post-transfer outcomes. Design: Nationwide retrospective cohort study using 2021–2023 Medicare claims linked to the American Hospital Association Annual Survey Database (AHAASD). Setting: U.S. acute care hospitals. Patients: Medicare fee-for-service beneficiaries with ICU hospitalizations between 2022 and 2023. Interventions: None. Measurements and Main Results: TCC capability was identified by AHAASD reporting and/or the presence of five or more TCC claims annually. The primary outcome was interhospital ICU transfer. Exploratory post-transfer outcomes included receipt of specialty procedures, death or hospice discharge within 1 day of transfer, in-hospital and 30-day mortality, and discharge disposition. Hierarchical logistic regression adjusted for patient demographics, comorbidities, acute organ failures, and transferring/accepting hospital characteristics, with transferring hospitals as random intercepts. Among 2,140,919 ICU hospitalizations, 33.4% occurred at 1,066 TCC-capable hospitals. Absolute transfer rates were similar (2.5% vs. 3.0%), but TCC capability was associated with higher adjusted odds of transfer (adjusted odds ratio [aOR], 1.08; 95% CI, 1.01–1.14). In exploratory post-transfer analyses, transferred patients from TCC hospitals had greater illness severity yet were less likely to die or be discharged to hospice within 1 day of transfer (4.6% vs. 6.6%; aOR, 0.86; 95% CI, 0.76–0.97) and more likely to be discharged home within 2 days (4.7% vs. 3.7%; aOR, 1.17; 95% CI, 1.03–1.33). Conclusions: TCC capability was associated with modestly increased transfer rates, fewer potentially low-value transfers, and improved post-transfer outcomes, suggesting improved transfer selection.

Objective: With the expected demographic shift toward those ≥65 years of age in the United States, late onset epilepsy (LOE) poses a significant public health issue, yet it has been historically understudied. We are undertaking an effort in the Epilepsy‐Cog study to pool individual participant data from six United States‐based prospective cohort studies. In this paper, we outline the process for ascertaining epilepsy, harmonizing, and pooling individual participant data across the six cohorts. Methods: The Epilepsy‐Cog study includes individual participant data from six United States‐based longitudinal cohort studies: Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Multi‐Ethnic Study of Atherosclerosis, Northern Manhattan Study (NOMAS), Reasons for Geographic and Racial Differences in Stroke, and Washington Heights/Inwood Columbia Aging Project. In all cohorts except NOMAS, prevalent and incident epilepsy were ascertained using Medicare claims‐based algorithms. In NOMAS, epilepsy cases were identified through cohort‐based reporting and medical record review. To perform cross‐cohort harmonization of variables, we used the lowest common denominator approach, assigning response categories or value levels in common across all cohorts. Results: From a total of 68 544 participants across six cohorts, 43 753 participants met eligibility criteria for Epilepsy‐Cog. Among them, we identified 551 (1.3%) participants with prevalent epilepsy and 1500 (3.4%) participants with incident epilepsy. We have harmonized demographic characteristics, health behaviors, vascular risk factors (VRFs), one genetic variable, medication use, subjective health status measures, incident events, and cause‐of‐death variables. Significance: The Epilepsy‐Cog pooled cohort of 43 753 participants with and without epilepsy, combined with harmonized demographic, VRF, and event data, offers a unique resource to yield new insights into LOE.

Background: Stroke hospitalization represents underlying stroke incidence and hospital utilization. We sought to identify factors associated with county‐level hospitalization rates (HRs) and counties with HRs above or below expectation using publicly available data. Methods: This cross‐sectional study is based on the analysis of county‐level 3‐year average stroke HRs (principal International Classification of Diseases, Tenth Revision [ICD‐10] , codes I60.X–I69.X) among Medicare fee‐for‐service beneficiaries from 2018 to 2020. Linear mixed models were fitted to investigate 6 sets of factors associated with HRs in a serial additive stepwise fashion (ie, demographics, overall population vascular risk factors, risk factor treatment, health delivery and access, environmental features, and socioeconomic status). We reported on marginal R ² , the most impactful factors, and characterized proportional difference between crude and predicted HRs. Results: The cohort of 3198 (98.6%) counties and county‐equivalents had a mean stroke HR of 11.2 per 100 000 (SD=2.6). The mean characteristics of the included counties were as follows: 19.4% age ≥65 years, 73% White race, 7.6% coronary heart disease prevalence, 38% hyperlipidemia prevalence, and 5.7 primary care physicians per 10 000. In the fully adjusted model, between‐county unexplained variation remained moderately high ( R ² =0.57). The most impactful factors associated with stroke HRs were prevalence of coronary heart disease, hypertension, smoking, nonadherence to antihypertensive medication, and elevation above sea level. Counties in the northwest United States generally had lower‐than‐expected HRs. Conclusions: Considerable unexplained county‐level variance in stroke HRs exists after accounting for a wide variety of known and potential predictors. Future work to clarify the mechanism of known predictors and explain variance may inform interventions to improve systems of care.

There are significant differences in compensation between medical specialties. In this study, we analyzed neurologist compensation in the United States compared with other medical specialties and in relation to productivity metrics. We evaluated data from the 2013-2023 editions of the SullivanCotter Physician Compensation and Productivity Survey, which collects compensation and productivity metrics directly from hospitals, hospital systems, and medical groups. We compared neurologists with 8 other specialties (internal medicine, pediatrics, family medicine, radiology, emergency medicine, neurosurgery, orthopaedic surgery, and interventional cardiology). The primary outcome was median compensation, defined as base salary and incentive pay, after being inflation-adjusted to 2023 dollars. The secondary outcome was median work relative value units (wRVUs), adjusted for modifiers and excluding technical components. The tertiary outcome was compensation per wRVU. Outcomes were standardized to a full-time effort equivalent. From 2013 to 2023, the average yearly number of physicians and neurologists in our cohort was 37,443 and 2,280, respectively. Inflation-adjusted median neurologist compensation started at $313,315 in 2013 and increased by 1.6% to $318,284 by 2023. In comparison, pediatrics remained the lowest compensated specialty, increasing by 4.9% from $258,073 to $270,666 and neurosurgery was the highest compensated, increasing by 5.0% from $790,336 to $829,527. Median neurologist wRVUs started at 4,475 in 2013 and increased by 12.3% to 5,024 by 2023. In 2023, neurologists received less compensation per wRVU ($65/wRVU) than neurosurgery ($90), orthopaedic surgery ($76), or interventional cardiology ($68), but more than pediatrics ($48), family medicine ($50), internal medicine ($54), radiology ($55), or emergency medicine ($56). Over time, neurologist compensation became less varied by geography of practice location or hospital vs medical group employment. Among neurologists, compensation increased for neurohospitalists and vascular neurologists, whereas it declined for those in epilepsy, neuromuscular, multiple sclerosis, and neurocritical care. Despite a 12% increase in wRVUs, inflation-adjusted neurologist compensation has remained stable since 2013. Compensation differences between neurologists and other medical specialties are not solely due to variance in wRVU generation. Future studies should explore factors contributing to these findings, including reimbursement models and governmental policies.

Background: More young women than men experience first‐time strokes. This may be from improved detection of milder severity strokes in young women, as they are more likely to present with nondebilitating neurologic symptoms than men. Methods: The objective was to examine sex differences in stroke severity among young adults. Young adults (18–55) with index stroke (January 1, 2012–April 3, 2019) were identified, using Colorado All Payer's Claims Database and linked to the GWTG (Get With The Guidelines)‐Stroke Registry. Records were reviewed based on 5/5 linked identifiers (±1 day for admission/discharge dates, date of birth, sex, and hospital), then on 4/5 linked identifiers. Stroke severity based on National Institutes of Health Stroke Scale score was extracted from GWTG‐stroke. Logistic regression models were used to calculate odds ratios (OR) of having a mild severity stroke (National Institutes of Health Stroke Scale score ≤5) by sex in ages 18 to 45 and 46 to 55 years. Results: Colorado All Payer's Claims Database captured 3029 stroke cases; 2732 from hospitals that reported to GWTG‐Stroke; 1597 (58.7%) linked at least 4/5 identifiers; 1311 with National Institutes of Health Stroke Scale score (50.2% women, 80% ischemic). Women were younger (mean age 45.4 years, men 46.9 years, P =0.001), had lower blood pressure (median 143/85, men 150/91, P P P =0.02) but not in 46–55 (OR, 1.02 [95% CI, 0.5–2.08]). There was no difference in ischemic stroke severity by sex in either age group. Conclusions: Young women with index strokes did not present with more milder severity strokes compared with men.

An older adult affordable housing community and a Federally Qualified Health Center partnered to improve the health of low-income older adults. The Unite Care Model included establishing onsite primary care, wellness support, and social needs assistance. The RE-AIM framework guided our mixed-methods evaluation. We sought to determine whether the model was associated with change in blood pressure, social or physical environment and understand model reach and implementation. Of the 251 residents, 13.1% had a clinic visit, and of respondents 70% attended at least one wellness event, and 35% received social needs assistance (reach). Clinic utilization was not associated with improved blood pressure or environment change (effectiveness). Residents reported barriers to clinic utilization including an established provider, uncertainty in transferring care, lack of urgent visits, and insurance barriers. Administrators echoed policy, staffing, and patient barriers to utilization (implementation). Expanding appointment options, increasing staffing, and overcoming insurance barriers may increase effectiveness.