Background:The purpose of the study was to investigate the relationship between community-level variables and emergency department (ED) visit rates before and during COVID-19. The focus was on opioid-related ED visits. Despite large declines in overall ED visits during COVID-19, opioid-related visits increased. While visits for avoidable conditions decreased, the opposite was true for opioid-related visits. Methods:We combined data from Florida EDs with community-level variables from the 2020 American Community Survey. The outcome measures of the study were quarterly ZIP code tabulation-area-level ED visit rates for opioid-related ED visits as well as visit rates for all other causes. Associations with opioid-related visit rates were estimated before and during COVID-19. Results:The associations between community-level variables and opioid-related visit rates did not match those found when analyzing overall ED visit rates. The increase in opioid-related visits during COVID-19 was not unique to or more prevalent in areas with a larger percentage of racial/ethnic minority populations. However, socioeconomic status was important, as areas with higher unemployment, lower income, lower home ownership, and higher uninsured had higher overall ED visit rates and opioid visit rates during the pandemic. In addition, the negative association with income increased during the pandemic. Conclusion:These results suggest socioeconomic status should be the focus of prevention and treatment efforts to reduce opioid-related visits in future pandemics. Healthcare organizations can use these results to target their prevention and treatment efforts during future pandemics.

Population Health ManagementVol. 26, No. 4 CommentariesAchieving Health EquityJulie A. Jacko and François SainfortJulie A. JackoAddress correspondence to: Julie A. Jacko, PhD, Dr. Kiran C. Patel College of Allopathic Medicine, Department of Population Health Sciences, 3200 South University Drive, Nova Southeastern University, Fort Lauderdale, FL 33328-2018, USA E-mail Address: [email protected]Dr. Kiran C. Patel College of Allopathic Medicine, Department of Population Health Sciences, Nova Southeastern University, Fort Lauderdale, Florida, USA.H. Wayne Huizenga College of Business and Entrepreneurship, Department of Decision Sciences and Department of Management, Nova Southeastern University, Fort Lauderdale, Florida, USA.Search for more papers by this author and François SainfortH. Wayne Huizenga College of Business and Entrepreneurship, Department of Decision Sciences and Department of Management, Nova Southeastern University, Fort Lauderdale, Florida, USA.Dr. Kiran C. Patel College of Allopathic Medicine, Department of Population Health Sciences, Nova Southeastern University, Fort Lauderdale, Florida, USA.Search for more papers by this authorPublished Online:14 Aug 2023https://doi.org/10.1089/pop.2023.0097AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Achieving Health Equity." Population Health Management, 26(4), pp. 199–200FiguresReferencesRelatedDetails Volume 26Issue 4Aug 2023 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:Julie A. Jacko and François Sainfort.Achieving Health Equity.Population Health Management.Aug 2023.199-200.http://doi.org/10.1089/pop.2023.0097Published in Volume: 26 Issue 4: August 14, 2023PDF download

Purpose As one of the five major dimensions of service quality, empathy has been and continues to be regarded as a requirement for a successful service encounter. This paper focuses on the highly customer-centric service industry of health care. The purpose of this paper is to shed light on the potential negative effects of empathy on both the physician and the patient. Design/methodology/approach Building on an in-depth review of literature and well-established service quality models, the authors propose a new model for understanding the complex role of physician empathy in the physician–patient encounter. The trait, emotional intelligence (EI), is presented as a moderator for physician empathy levels. Findings The Health Care Optimal Physician Empathy (HOPE) model enables further characterization and analysis of the tradeoffs between patient satisfaction and physician burnout and determining when empathy optimally works to the benefit of both the physician and the patient to maximize service quality. The HOPE model provides a systematic way to understand and determine the appropriate level of physician empathy that results in optimal outcomes for both physicians and their patients by demonstrating the tradeoffs between physician burnout and patient satisfaction. Originality/value The authors highlight the potential detrimental effects on physicians themselves, and, in turn, on service quality. The theoretical and practical implications in this paper provide insights into the development and implementation of empathy-focused interventions and best practices to optimize service quality in the physician–patient interaction. The HOPE model is the first of its kind in shedding light on the manifestation of physician empathy.

Premedical students typically pursue undergraduate specialization in basic biological and other sciences, learning to understand living systems at a microscopic, genetic, or molecular level. However, curricula in the basic sciences do not traditionally include courses that enable students to learn about living systems at the macro level-understanding individuals within their environment, as well as understanding and managing the health of populations, especially those with underlying conditions or the underserved. This disconnect can be bridged by creating novel curricular programs intersecting medicine and business. Population health management is a multidisciplinary field that aims to improve the patient experience, reduce health care costs, and improve treatment outcomes. Though related to public health, the 2 fields differ in significant ways. Population health management emphasizes health outcomes and their measurements and seeks to improve health outcomes based on a full understanding of risk, behaviors, lifestyle, environment, and all social determinants of health. A shift in premedical education that connects the medical sciences with business requires curricular reform with the emerging field of population health management at their intersection, allowing students to be better prepared for future medical practices and to understand expectations, benchmarks, business, and economics in a new value-based health care system.

Emergency department (ED) visits for drug overdoses increased nationally during COVID-19 despite declines in all-cause ED visits. The study purpose was to compare characteristics of ED visits for opioid and stimulant overdoses before and during COVID-19 in Florida. This study tested for disparities in ED visits for opioid and stimulant overdoses by race/ethnicity, age, and insurance status. The study identified ED visits for opioid and stimulant overdose in Florida during quarters two and three of 2019 and compared them with quarters two and three of 2020. Overall, there was an increase in the number of opioid and stimulant overdoses during COVID-19. Combined with the decline in the number of all-cause ED visits, drug overdoses represented a larger share of ED visits during COVID-19 compared with before COVID-19. The study did not find evidence of disparities by race/ethnicity, as each group experienced similar increases in the likelihood of ED visits involving drug overdoses during COVID-19. Differences emerged according to age and insurance status. ED visits involving those under age 18 were more likely to involve opioid or stimulant overdose, and ED visits among those over age 65 were less likely to involve opioid overdose during COVID-19. ED visits among those with vulnerable insurance status were more likely to involve opioid overdose during COVID-19. Patterns of behavior change during periods of restricted activity due to a pandemic. These changes in behavior change the mix of risks that people face, suggesting the need for a reallocation of population health management resources during pandemics.

The integration of medical schools and clinical partners is effectively established through the formation of academic medical centers (AMCs). The tripartite mission of AMCs emphasizes the importance of providing critical clinical services, medical innovation through research, and the education of future health care leaders. Although AMCs represent only 5% of all hospitals, they contribute substantially to serving disadvantaged populations of patients, including an estimated 37% of all charity care and 26% of all Medicaid hospitalizations. Currently, most AMCs use a business model centered upon revenue generated from hospital services and/or practice plans. In the last decade, mounting financial demands have placed significant pressure on AMC finances because of the rising costs associated with complex clinical care and operating diverse graduate medical education programs. A shift toward population health-centric health care management strategies will profoundly influence the predominant forms of health care delivery in the United States in the foreseeable future. Health systems are increasingly pursuing new strategies to manage financial risk, such as forming Accountable Care Organizations and provider-sponsored plans to provide value-based care. Refocusing research and operational capacity toward population health management fosters collaboration and enables reintegration with hospital and clinical partners across care networks, and can potentially create new revenue streams for AMCs. Despite the benefits of population health integration, current literature lacks a blueprint to guide AMCs in the transformation toward sustainable population health management models. The purpose of this paper is to propose a modern conceptual framework that can be operationalized by AMCs in order to achieve a sustainable future.

Description The opioid crisis poses a substantial threat to youth throughout the nation. This crisis has been exacerbated by the COVID-19 pandemic, reversing some of the positive national trends in the fight against the opioid epidemic. Some risk factors for youth opioid use have been identified nationally. The South Florida tri-county region of Miami-Dade, Broward and Palm Beach is a culturally distinct region which may not follow national trends and likely has unique risk and protective factors. To address the concerning spike in youth opioid use in South Florida, a community coalition was formed to identify factors unique to South Florida and create a plan for early awareness and prevention.

Background:In Florida, 2.4 million people have diabetes and 5.8 million are pre-diabetic. Not only has the prevalence of diabetes doubled over the past 20 years from 5.2 in 1992 to 11.2 in 2014, but the Centers for Disease Control and Prevention expects 1 out of every 3 adults will have diabetes by the year 2050. In addition, in every year since 1996, Florida well exceeds the national levels in terms of prevalence of diabetes, and the gap is getting wider. A study was conducted to gather information from key physician stakeholders as to how to address unmet needs of patients at risk for, or whom already have, diabetes in a tri-county region of South Florida where the prevalence of diabetes is very high. Objective:The goal was to catalyze innovation and generate solutions for high quality and affordable diabetes care by convening community physicians in South Florida and querying them about solutions for delivering value-based care. Methods:A physician-led task force of community physicians was convened to uncover unmet needs in the diabetes care continuum, identify areas of improvement for coordinating care across the continuum and effectively accessing specialty care. Focus groups were convened with 30 participants to capture qualitative data relative to unmet needs, utilizing the Rapid Ideation Technique. A survey instrument was designed and administered to the twenty-one community clinicians on the task force to augment the qualitative data with quantitative data. The first part of the survey captured characteristics of the participating clinicians, their practices, their diabetes services and management approaches. The second part of the survey captured individual ratings of the importance and merit of needs and/or potential solutions generated. Results:The focus groups generated a wealth of information regarding challenges, issues, areas of opportunities, and potential solutions that could be organized within eight main themes: care coordination and integration; patient engagement, education and behavioral change; physician and practice support; EMR and data issues; telehealth solutions; health informatics and data analytics; and access to care. The surveys culminated in the formation of a Call-For-Action Agenda for immediate work. Conclusions:The ultimate goal of the taskforce was to catalyze innovation and generate solutions for high quality and affordable care. This article reports the findings and provides a roadmap for the future.

Introduction There are currently no data, blueprints, best practices, or financial models available to guide the creation of a new medical school. Yet, the United States is experiencing unprecedented growth of new allopathic medical schools. Findings This article brings logic to the process. It converts the complexity of what is often regarded as an administrative exercise into the first published framework of management principles. Those principles were then translated into a process map and a financial optimization model. All three elements can be successfully implemented for establishing an accredited, value-driven medical education program that minimizes time from inception to implementation, and ensures sustainability over time. Outcomes This case report provides a blueprint for planning and implementation of a new medical school. Outcomes include both process and optimization models, as well as valuable insights that have utility when considering a new medical school to mitigate the projected nationwide shortage of physicians.

Despite a shift from institutional services toward more home and community-based services (HCBS) for older adults who need long-term services and supports (LTSS), the effects of HCBS have yet to be adequately synthesized in the literature. This review of literature from 1995 to 2012 compares the outcome trajectories of older adults served through HCBS (including assisted living [AL]) and in nursing homes (NHs) for physical function, cognition, mental health, mortality, use of acute care, and associated harms (e.g., accidents, abuse, and neglect) and costs. NH and AL residents did not differ in physical function, cognition, mental health, and mortality outcomes. The differences in harms between HCBS recipients and NH residents were mixed. Evidence was insufficient for cost comparisons. More and better research is needed to draw robust conclusions about how the service setting influences the outcomes and costs of LTSS for older adults. Future research should address the numerous methodological challenges present in this field of research and should emphasize studies evaluating the effectiveness of HCBS.

OBJECTIVESReducing preventable deaths because of uncontrolled hemorrhage, tension pneumothorax, and airway loss is a priority. As part of a research initiative comparing different training models, this study evaluated the reliability and validity of a test that assesses combat medic performance during a polytrauma scenario using live animal models.METHODSNine procedural checklists and seven global rating scales were piloted with four cohorts of soldiers (n = 94) at two U.S. training sites. Cohorts represented "novice" to "proficient" trainees. Procedure scores and a mean global score were calculated per subject. The intraclass correlation was calculated per procedure, with 0.70 as the threshold for acceptability. An overall difference among cohorts was hypothesized: Cohort 4 (proficient) > Cohort 3 (competent) > Cohort 2 (beginners) > Cohort 1 (novice) trainees. Data were analyzed using Kruskal-Wallis and analysis of variance.RESULTSAt Site A, intraclass correlation coefficients ranged from 74% to 93% for 6 of 9 procedures. Cohorts differed significantly on hemorrhage control, needle decompression, cricothyrotomy, amputation management, chest tube insertion, and mean global scores. Cohort 4 outperformed the others, and Cohorts 2 and 3 outperformed Cohort 1.CONCLUSIONThe test differentiates novices from beginners, competent, and proficient trainees on difficult procedures and overall performance.

Objectives Bayesian statistical methods are increasingly popular as a tool for meta-analysis of clinical trial data involving both direct and indirect treatment comparisons. However, appropriate selection of prior distributions for unknown model parameters and checking of consistency assumptions required for feasible modeling remain particularly challenging. We compared Bayesian and traditional frequentist statistical methods for multiple treatment comparisons in the context of pharmacological treatments for female urinary incontinence (UI). Data sources We searched major electronic bibliographic databases, U.S. Food and Drug Administration reviews, trial registries, and research grant databases up to November 2011 to find randomized studies published in English that examined drugs for urgency UI on continence, improvements in UI, and treatment discontinuation due to harms. Review methods We fitted fixed and random effects models in frequentist and Bayesian frameworks. In a hierarchical model of eight treatments, we separately analyzed one safety and two efficacy outcomes. We produced Bayesian and frequentist treatment ranks and odds ratios (and associated measures of uncertainty) across all bivariate treatment comparisons. We also calculated the number needed to treat (NNT) to achieve continence or avoid harms from pooled absolute risk differences. Results While frequentist and Bayesian analyses produced broadly comparable odds ratios of safety and efficacy, the Bayesian method's ability to deliver the probability that any treatment is best, or among the top two such treatments, offered a more meaningful clinical interpretation. In our study, two drugs emerged as attractive because while neither had any significant chance of being among the least safe drugs, both had greater than 50 percent chances of being among the top three drugs in terms of Best12 probability for one of the efficacy endpoints. Conclusions Bayesian methods are more flexible and their results more clinically interpretable but require more careful development and specialized software. Key Messages Both Bayesian and frequentist hierarchical models can be effective in multiple treatment comparisons. Bayesian models sensibly shrink estimates towards each other, encouraging more borrowing of statistical strength from the entire collection of studies. Bayesian methods also lead to more clinically interpretable results (through their ability to assign probabilities to events), as well as more sensible rankings of the pharmacological treatments as compared to traditional NNT-based methods. Further development of hierarchical Bayesian multiple treatment comparison methods is warranted, especially for nonbinary data models, simultaneous decisionmaking across multiple endpoints, assessing consistency, and incorporating data sources of varying quality (e.g., clinical vs. observational data).