With 42% of all emergency department visits in the United States related to pain, physicians who work in this setting are tasked with providing adequate pain management to patients with varying primary complaints and medical histories. Complicating this, the United States is in the midst of an opioid overdose epidemic. State governments and national organizations have developed guidelines and legislation to curtail opioid prescriptions in acute care settings, while also incentivizing providers for patient satisfaction and completeness of pain control. In order to inform future policies that focus on provider pain medication prescribing, we sought to characterize the factors physicians weigh when considering treating pain with opioids in the emergency department. We conducted and transcribed open-ended, semistructured qualitative interviews with 52 physicians at a national emergency medicine conference. Participants reported a wide range of factors contributing to their opioid prescribing patterns related to three domains: 1) provider assessment of pain characteristics, 2) patient-based considerations, and 3) practice environment. Pain characteristics include the characteristics of various acute and chronic pain syndromes, including physicians' empathy due to their own experiences with pain. Patient characteristics include "trustworthiness," race and ethnicity, and the concern for risk of misuse. Factors related to the practice environment include hospital policy, legislation/regulation, and guidelines. The decision to prescribe opioids to patients in the emergency department is complex and nuanced. Physicians are interested in guidance and are concerned about the competing pressures placed on their opioid prescribing due to incentives related to patient satisfaction scores on one hand and inflexible policies that do not allow for individualized, patient-centered decisions on the other.
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http://dx.doi.org/10.1177/2381468316681006 | DOI Listing |
Am J Emerg Med
January 2025
Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale University, New Haven, CT, USA.
Background: This study aimed to examine how physician performance metrics are affected by the speed of other attendings (co-attendings) concurrently staffing the ED.
Methods: A retrospective study was conducted using patient data from two EDs between January-2018 and February-2020. Machine learning was used to predict patient length of stay (LOS) conditional on being assigned a physician of average speed, using patient- and departmental-level variables.
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
JMIR AI
January 2025
Department of Radiology, Children's National Hospital, Washington, DC, United States.
Clin Infect Dis
January 2025
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases, Respiratory Medicine and Critical Care, Berlin, Germany.
Background: Existing risk evaluation tools underperform in predicting intensive care unit (ICU) admission for patients with the Coronavirus Disease 2019 (COVID-19). This study aimed to develop and evaluate an accurate and calculator-free clinical tool for predicting ICU admission at emergency room (ER) presentation.
Methods: Data from patients with COVID-19 in a nationwide German cohort (March 2020-January 2023) were analyzed.
PLoS One
January 2025
Animal and Human Health Department, International Livestock Research Institute, Nairobi, Kenya.
Non-conformance with antibiotic withdrawal period guidelines represents a food safety concern, with potential for antibiotic toxicities and allergic reactions as well as selecting for antibiotic resistance. In the Kenyan domestic pig market, conformance with antibiotic withdrawal periods is not a requirement of government legislation and evidence suggests that antibiotic residues may frequently be above recommended limits. In this study, we sought to explore enablers of and barriers to conformance with antibiotic withdrawal periods for pig farms supplying a local independent abattoir in peri-urban Nairobi.
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