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Delays in seeking emergency care stemming from patient reluctance may explain the rise in cases of out-of-hospital cardiac arrest and associated poor health outcomes during the COVID-19 pandemic. In this study we used emergency medical services (EMS) call data from the Boston, Massachusetts, area to describe the association between patients' reluctance to call EMS for cardiac-related care and both excess out-of-hospital cardiac arrest incidence and related outcomes during the pandemic. During the initial COVID-19 wave, cardiac-related EMS calls decreased (-27.2 percent), calls with hospital transportation refusal increased (+32.5 percent), and out-of-hospital cardiac arrest incidence increased (+35.5 percent) compared with historical baselines. After the initial wave, although cardiac-related calls remained lower (-17.2 percent), out-of-hospital cardiac arrest incidence remained elevated (+24.8 percent) despite fewer COVID-19 infections and relaxed public health advisories. Throughout Boston's fourteen neighborhoods, out-of-hospital cardiac arrest incidence was significantly associated with decreased cardiac-related calls, but not with COVID-19 infection rates. These findings suggest that patients were reluctant to obtain emergency care. Efforts are needed to ensure that patients seek timely care both during and after the pandemic to reduce potentially avoidable excess cardiovascular disease deaths.

Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of this study was to improve upon the established Revised Framingham Stroke Risk Score and design an interactive Non-Linear Stroke Risk Score. Leveraging machine learning algorithms, our work aimed at increasing the accuracy of event prediction and uncovering new relationships in an interpretable fashion. A two-phase approach was used to create our stroke risk prediction score. First, clinical examinations of the Framingham offspring cohort were utilized as the training dataset for the predictive model. Optimal Classification Trees were used to develop a tree-based model to predict 10-year risk of stroke. Unlike classical methods, this algorithm adaptively changes the splits on the independent variables, introducing non-linear interactions among them. Second, the model was validated with a multi-ethnicity cohort from the Boston Medical Center. Our stroke risk score suggests a key dichotomy between patients with history of cardiovascular disease and the rest of the population. While it agrees with known findings, it also identified 23 unique stroke risk profiles and highlighted new non-linear relationships; such as the role of T-wave abnormality on electrocardiography and hematocrit levels in a patient's risk profile. Our results suggested that the non-linear approach significantly improves upon the baseline in the c-statistic (training 87.43% (CI 0.85-0.90) vs. 73.74% (CI 0.70-0.76); validation 75.29% (CI 0.74-0.76) vs 65.93% (CI 0.64-0.67), even in multi-ethnicity populations. The clinical implications of the new risk score include prioritization of risk factor modification and personalized care at the patient level with improved targeting of interventions for stroke prevention., Competing Interests: The authors report no competing interests.

Rationale and Objectives: Physician staff of academic hospitals today practice in several geographic locations including their main hospital. This is referred to as the extended campus. With extended campuses expanding, the growing complexity of a single division's schedule means that a naive approach to scheduling compromises revenue. Moreover, it may provide an unfair allocation of individual revenue, desirable or burdensome assignments, and the extent to which the preferences of each individual are met. This has adverse consequences on incentivization and employee satisfaction and is simply against business policy., Materials and Methods: We identify the daily scheduling of physicians in this context as an operational problem that incorporates scheduling, revenue management, and fairness. Noting previous success of operations research and optimization in each of these disciplines, we propose a simple unified optimization formulation of this scheduling problem using mixed-integer optimization., Results: Through a study of implementing the approach at the Division of Angiography and Interventional Radiology at the Brigham and Women's Hospital, which is directed by one of the authors, we exemplify the flexibility of the model to adapt to specific applications, the tractability of solving the model in practical settings, and the significant impact of the approach, most notably in increasing revenue by 8.2% over previous operating revenue while adhering strictly to a codified fairness and objectivity., Conclusions: We found that the investment in implementing such a system is far outweighed by the large potential revenue increase and the other benefits outlined., (Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.)

Background: Although the practical challenges to work hour restrictions have been the focus of much discussion, cultural resistance to such change has received less attention. Surgical residency has its own unique social structure, and we hypothesized that challenges to this would provide impediments to successful implementation of duty hours reform., Study Design: We used ethnographic research methods to study the efforts at work hour restriction over a 15-month period before the introduction of the Accreditation Council for Graduate Medical Education regulations. These methods, validated for studying institutional change, build on intense periods of observation. Records of observations are then analyzed and coded to uncover cultural and political challenges. The frequency of successful hand-offs in sign-out situations between day and night float residents was measured as an objective index of success., Results: Practical issues were addressed initially by scheduling adjustments including creating a night float system. The hand-offs that this system required, however, were successful only 14% of the time. Subsequent steps to address the challenge to resident identity by top-down support of a new definition of professionalism increased the number of successful hand-offs to 39%. Finally, a reduction in a noted hierarchy violation led to successful hand-offs 79% of the time., Conclusions: These results demonstrate that practical solutions alone may not be a sufficient basis for change in surgical residency. While we face other challenges to the traditional surgical culture, attention to social and political issues may enhance the success of our efforts.