Patient-Centered Appointment Scheduling Using Agent-Based Simulation

Enhanced access and continuity are key components of patient-centered care. Existing studies show that several interventions such as providing same day appointments, walk-in services, after-hours care, and group appointments, have been used to redesign the healthcare systems for improved access to primary care. However, an intervention focusing on a single component of care delivery (i.e. improving access to acute care) might have a negative impact other components of the system (i.e. reduced continuity of care for chronic patients). Therefore, primary care clinics should consider implementing multiple interventions tailored for their patient population needs. We collected rapid ethnography and observations to better understand clinic workflow and key constraints. We then developed an agent-based simulation model that includes all access modalities (appointments, walk-ins, and after-hours access), incorporate resources and key constraints and determine the best appointment scheduling method that improves access and continuity of care. This paper demonstrates the value of simulation models to test a variety of alternative strategies to improve access to care through scheduling

Rapid Response of an Academic Surgical Department to the COVID-19 Pandemic: Implications for Patients, Surgeons, and the Community.

BackgroundAs the coronavirus disease 2019 (COVID-19) pandemic continues to spread, swift actions and preparation are critical for ensuring the best outcomes for patients and providers. We aim to describe our hospital and Department of Surgery's experience in preparing for the COVID-19 pandemic and caring for surgical patients during this unprecedented time.Study designThis is a descriptive study outlining the strategy of a single academic health system for addressing the following 4 critical issues facing surgical departments during the COVID-19 pandemic: developing a cohesive leadership team and system for frequent communication throughout the department; ensuring adequate hospital capacity to care for an anticipated influx of COVID-19 patients; safeguarding supplies of blood products and personal protective equipment to protect patients and providers; and preparing for an unstable workforce due to illness and competing personal priorities, such as childcare.ResultsThrough collaborative efforts within the Department of Surgery and hospital, we provided concise and regular communication, reduced operating room volume by 80%, secured a 4-week supply of personal protective equipment, and created reduced staffing protocols with back-up staffing plans.ConclusionsBy developing an enabling infrastructure, a department can nimbly respond to crises like COVID-19 by promoting trust among colleagues and emphasizing an unwavering commitment to excellent patient care. Sharing principles and practical applications of these changes is important to optimize responses across the country and the world

A tug-of-war between driver and passenger mutations in cancer and other adaptive processes

Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few 'driver' mutations occur alongside thousands of random 'passenger' mutations-a natural consequence of cancer's elevated mutation rate. Some passengers can be deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression that is described by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers meltdown. We find support for the model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to rationalize successes and failures of different treatment strategies. We find that a tumor's load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. Collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by both current and future therapies

Complex Care Management Program Overview

This report includes brief updates on various forms of complex care management including: Aetna - Medicare Advantage Embedded Case Management ProgramBrigham and Women's Hospital - Care Management ProgramIndependent Health - Care PartnersIntermountain Healthcare and Oregon Health and Science University - Care Management PlusJohns Hopkins University - Hospital at HomeMount Sinai Medical Center -- New York - Mount Sinai Visiting Doctors Program/ Chelsea-Village House Calls ProgramsPartners in Care Foundation - HomeMeds ProgramPrinceton HealthCare System - Partnerships for PIECEQuality Improvement for Complex Chronic Conditions - CarePartner ProgramSenior Services - Project Enhance/EnhanceWellnessSenior Whole Health - Complex Care Management ProgramSumma Health/Ohio Department of Aging - PASSPORT Medicaid Waiver ProgramSutter Health - Sutter Care Coordination ProgramUniversity of Washington School of Medicine - TEAMcar

Stress on the Ward – An Empirical Study of the Nonlinear Relationship between Organizational Workload and Service Quality

We discuss the impact of organizational workload on professional service outcomes, such as survival rates in hospitals. The prevailing view in the literature is that service quality deteriorates when organizational workload increases. In contrast, we argue that the relationship between workload and service outcomes is nonlinear and that there is a quality-optimal workload level. Whilst outcomes deteriorate with increasing workload when workload levels are already high, they will improve if workload increases from a low level. We reach this hypothesis by combining three perspectives: (i) the queuing theory perspective, with its focus on congestion, (ii) a discretionary choice perspective, with a focus on decisions made by professionals in response to changes in workload, and (iii) an endocrinological perspective, with a focus on the subconscious eff ects of workload on worker performance through the cognitive impact of stress hormones. Using a patient census of 1.4 million patients in 624 departments across 101 hospitals, we provide empirical support for the nonlinearity hypothesis in the context of hospital survival rates. We further discuss the implications for hospital capacity planning and the wider implications for service operations management.Service quality; service outcomes; organizational workload; hospital capacity planning; behavioral operations; stress

CareOregon: Transforming the Role of a Medicaid Health Plan From Payer to Partner

Details Triple Aim pilot programs designed to offer patient-centered medical homes and multidisciplinary case management in an effort to improve population health, enhance patients' experience, and slow cost growth

Absolute electrical impedance tomography (aEIT) guided ventilation therapy in critical care patients: simulations and future trends

Thoracic electrical impedance tomography (EIT) is a noninvasive, radiation-free monitoring technique whose aim is to reconstruct a cross-sectional image of the internal spatial distribution of conductivity from electrical measurements made by injecting small alternating currents via an electrode array placed on the surface of the thorax. The purpose of this paper is to discuss the fundamentals of EIT and demonstrate the principles of mechanical ventilation, lung recruitment, and EIT imaging on a comprehensive physiological model, which combines a model of respiratory mechanics, a model of the human lung absolute resistivity as a function of air content, and a 2-D finite-element mesh of the thorax to simulate EIT image reconstruction during mechanical ventilation. The overall model gives a good understanding of respiratory physiology and EIT monitoring techniques in mechanically ventilated patients. The model proposed here was able to reproduce consistent images of ventilation distribution in simulated acutely injured and collapsed lung conditions. A new advisory system architecture integrating a previously developed data-driven physiological model for continuous and noninvasive predictions of blood gas parameters with the regional lung function data/information generated from absolute EIT (aEIT) is proposed for monitoring and ventilator therapy management of critical care patients

Prediction and prevention of the next pandemic zoonosis.

Most pandemics--eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza--originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption