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BACKGROUND. The federal No Surprises Act (NSA), designed to eliminate surprise medical billing for out-of-network (OON) care for circumstances beyond patients' control, established the independent dispute resolution (IDR) process to settle clinician-payer payment disputes for OON care. OBJECTIVE. The purpose of our study was to assess the fraction of OON claims for which radiologists and other hospital-based specialists can expect to at least break even when challenging payer-determined payments through the NSA IDR process, as a measure of the process's financial viability. METHODS. This retrospective study extracted claims from a national commercial database (Optum's deidentified Clinformatics Data Mart) for hospital-based specialties occurring on the same day as in-network emergency department (ED) visits or inpatient stays from January 2017 to December 2021. OON claims were identified. OON claims batching was simulated using IDR rules. Maximum potential recovered payments from the IDR process were estimated as the difference between the charges and the allowed amount. The percentages of claims for which the maximum potential payment and one-quarter of this amount (a more realistic payment recovery estimate) would exceed IDR fees were determined, using US$150 and US$450 fee thresholds to approximate the range of final 2024 IDR fees. These values represented the percentage of OON claims that would be financially viable candidates for IDR submission. RESULTS. Among 76,221,264 claims for hospital-based specialties associated with in-network ED visits or inpatient stays, 1,482,973 (1.9%) were OON. The maximum potential payment exceeded fee thresholds of US$150 and US$450 for 55.0% and 32.1%, respectively, of batched OON claims for radiologists and 76.8% and 61.3% of batched OON claims for all other hospital-based specialties combined. At payment of one-quarter of that amount, these values were 26.9% and 10.6%, respectively, for radiologists and 56.6% and 38.4% for all other hospital-based specialties combined. CONCLUSION. The IDR process would be financially unviable for a substantial fraction of OON claims for hospital-based specialists (more so for radiology than for other such specialties). CLINICAL IMPACT. Although the NSA enacted important patient protections, IDR fees limit clinicians' opportunities to dispute payer-determined payments and potentially undermine their bargaining power in contract negotiations. Therefore, IDR rulemaking may negatively impact patient access to in-network care.
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Dissidências e Disputas , Humanos , Estudos Retrospectivos , Estados Unidos , Radiologia/economia , Serviço Hospitalar de Emergência/economia , NegociaçãoRESUMO
BACKGROUND AND OBJECTIVES: Patient monitoring systems provide critical information but often produce loud, frequent alarms that worsen patient agitation and stress. This may increase the use of physical and chemical restraints with implications for patient morbidity and autonomy. This study analyzes how augmenting alarm thresholds affects the proportion of alarm-free time and the frequency of medications administered to treat acute agitation. METHODS: Our emergency department's patient monitoring system was modified on June 28, 2022 to increase the tachycardia alarm threshold from 130 to 150 and to remove alarm sounds for several arrhythmias, including bigeminy and premature ventricular beats. A pre-post study was performed lasting 55 days before and 55 days after this intervention. The primary outcome was change in number of daily patient alarms. The secondary outcomes were alarm-free time per day and median number of antipsychotic and benzodiazepine medications administered per day. The safety outcome was the median number of patients transferred daily to the resuscitation area. We used quantile regression to compare outcomes between the pre- and post-intervention period and linear regression to correlate alarm-free time with the number of sedating medications administered. RESULTS: Between the pre- and post-intervention period, the median number of alarms per day decreased from 1332 to 845 (-37%). This was primarily driven by reduced low-priority arrhythmia alarms from 262 to 21 (-92%), while the median daily census was unchanged (33 vs 32). Median hours per day free from alarms increased from 1.0 to 2.4 (difference 1.4, 95% CI 0.8-2.1). The median number of sedating medications administered per day decreased from 14 to 10 (difference - 4, 95% CI -1 to -7) while the number of escalations in level of care to our resuscitation care area did not change significantly. Multivariable linear regression showed a 60-min increase of alarm-free time per day was associated with 0.8 (95% CI 0.1-1.4) fewer administrations of sedating medication while an additional patient on the behavioral health census was associated with 0.5 (95% CI 0.0-1.1) more administrations of sedating medication. CONCLUSION: A reasonable change in alarm parameter settings may increase the time patients and healthcare workers spend in the emergency department without alarm noise, which in this study was associated with fewer doses of sedating medications administered.
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Alarmes Clínicos , Serviço Hospitalar de Emergência , Agitação Psicomotora , Humanos , Masculino , Agitação Psicomotora/tratamento farmacológico , Feminino , Pessoa de Meia-Idade , Antipsicóticos/uso terapêutico , Antipsicóticos/administração & dosagem , Adulto , Idoso , Benzodiazepinas/uso terapêutico , Benzodiazepinas/administração & dosagem , Monitorização Fisiológica/métodos , Hipnóticos e Sedativos/uso terapêutico , Hipnóticos e Sedativos/administração & dosagemRESUMO
BACKGROUND: Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload. OBJECTIVE: The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR). METHODS: This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression. RESULTS: We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations. CONCLUSIONS: In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.
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Registros Eletrônicos de Saúde , Carga de Trabalho , Humanos , Serviço Hospitalar de Emergência , Pacientes Internados , PercepçãoRESUMO
Importance: While most patients with acute pancreatitis (AP) fulfill diagnostic criteria with characteristic abdominal pain and serum lipase levels of at least 3 times the upper limit of normal (reference range) at presentation, early imaging is often used for confirmation. A prior prediction model and corresponding point-based score were developed using nonimaging parameters to diagnose AP in patients presenting to the emergency department (ED). Objective: To evaluate the performance of the prediction model to diagnose AP in a prospective patient cohort. Design, Setting, and Participants: This prospective diagnostic study included consecutive adult patients presenting to the ED between January 1, 2020, and March 9, 2021, at 2 large academic medical centers in the northeastern US with serum lipase levels at least 3 times the upper limit of normal. Patients transferred from outside institutions or with malignant disease and established intra-abdominal metastases, acute trauma, or altered mentation were excluded. Data were analyzed from October 15 to October 23, 2023. Exposures: Participants were assigned scores for initial serum lipase level, number of prior AP episodes, prior cholelithiasis, abdominal surgery within 2 months, presence of epigastric pain, pain of worsening severity, duration from pain onset to presentation, and pain level at ED presentation. Main Outcome and Measures: A final diagnosis of AP, established by expert review of hospitalization records. Results: Prospective scores in 349 participants (mean [SD] age, 53.0 [18.8] years; 184 women [52.7%]; 66 Black [18.9%]; 199 White [57.0%]) demonstrated an area under the receiver operating characteristics curve of 0.91. A score of at least 6 points achieved highest accuracy (F score, 82.0), corresponding to a sensitivity of 81.5%, specificity of 85.9%, positive predictive value of 82.6%, and negative predictive value of 85.1% for AP diagnosis. Early computed tomography or magnetic resonance imaging was performed more often in participants predicted to have AP (116 of 155 [74.8%] with a score ≥6 vs 111 of 194 [57.2%] with a score <6; P < .001). Early imaging revealed an alternative diagnosis in 8 of 116 participants (6.9%) with scores of at least 6 points, 1 of 93 (1.1%) with scores of at least 7 points, and 1 of 73 (1.4%) with scores of at least 8 points. Conclusions and Relevance: In this multicenter diagnostic study, the prediction model demonstrated excellent AP diagnostic accuracy. Its application may be used to avoid unnecessary confirmatory imaging.
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Lipase , Pancreatite , Humanos , Pancreatite/diagnóstico , Pancreatite/sangue , Feminino , Masculino , Estudos Prospectivos , Pessoa de Meia-Idade , Adulto , Lipase/sangue , Serviço Hospitalar de Emergência , Idoso , Valor Preditivo dos Testes , Doença Aguda , Dor Abdominal/etiologiaRESUMO
BACKGROUND: Academic emergency medicine (EM) is foundational to the EM specialty through the development of new knowledge and clinical training of resident physicians. Despite recent increased attention to the future of the EM workforce, no evaluations have specifically characterized the U.S. academic EM workforce. We sought to estimate the national proportion of emergency physicians (EPs) identified as academic and the proportion of emergency department (ED) visits that take place at academic sites. METHODS: We performed a cross-sectional analysis of EPs and EDs using data from the American Hospital Association, the Centers for Medicare & Medicaid Services, and Doximity's Residency Navigator. EPs were identified as "academic" if they were affiliated with at least one facility determined to be academic, defined as EDs officially designated by the Accreditation Council for Graduate Medical Education (ACGME) as clinical training sites at accredited EM residency programs. Our primary outcomes were to estimate the national proportion of EPs identified as academic and the proportion of ED visits performed at academic sites. RESULTS: Our analytic sample included 26,937 EPs practicing clinically across 4920 EDs and providing care during 130,471,386 ED visits. Among EPs, 11,720 (43.5%) were identified as academic, and among EDs, 635 (12.9%) were identified as academic sites, including 585 adult/general sites, 45 pediatric-specific sites, and 10 sites affiliated with the Department of Veterans Affairs. In 2021, academic EDs provided care for 42,794,106 ED visits or 32.8% of all ED visits nationally. CONCLUSIONS: Approximately four in 10 EPs practice in at least one clinical training site affiliated with an ACGME-accredited EM residency program, and approximately one in three ED visits nationally occur in these academic EDs. We encourage further work using alternative definitions of an academic EPs and EDs, along with longitudinal research to identify trends in the workforce's composition.
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Medicina de Emergência , Serviço Hospitalar de Emergência , Médicos , Humanos , Estudos Transversais , Estados Unidos , Medicina de Emergência/educação , Serviço Hospitalar de Emergência/estatística & dados numéricos , Médicos/provisão & distribuição , Médicos/estatística & dados numéricos , Centros Médicos Acadêmicos/estatística & dados numéricos , Recursos Humanos/estatística & dados numéricos , Internato e Residência/estatística & dados numéricosRESUMO
Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy of clinical situations using diagnostic variables (true and false positives and negatives, respectively). Decision tree representations of medical decision-making tools can be generated using diagnostic variables found in literature and entropy removal can be calculated for these tools. This concept of clinical entropy removal has significant potential for further use to bring forth healthcare innovation, such as quantifying the impact of clinical guidelines and value of care and applications to Emergency Medicine scenarios where diagnostic accuracy in a limited time window is paramount. This analysis was done for 623 diagnostic tools and provided unique insights into their utility. For studies that provided detailed data on medical decision-making algorithms, bootstrapped datasets were generated from source data to perform comprehensive machine learning analysis on these algorithms and their constituent steps, which revealed a novel and thorough evaluation of medical diagnostic algorithms.
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Algoritmos , Tomada de Decisão Clínica , Entropia , Aprendizado de Máquina , Teoria da InformaçãoRESUMO
OBJECTIVE: Currently, computed tomographic pulmonary angiogram (CTPA) for evaluating acute pulmonary embolism (PE) in Emergency Departments (EDs) is overused and with low yields. The goal of this study is to assess the impact of an evidence-based clinical decision support (CDS) tool, aimed at optimizing appropriate use of CTPA for evaluating PE. METHODS: The study was performed at EDs in a large healthcare system and included 9 academic and community hospitals. The primary outcome was the percent difference in utilization (number of CTPA performed/number of ED visits) and secondary outcome was yield (percentage of CTPA positive for acute PE), comparing 12 months before (6/1/2021-5/31/2022) vs. 12 months after (6/1/2022-5/31/2023) a system-wide implementation of the CDS. Univariate and multivariable analyses using logistic regression were performed to assess factors associated with diagnosis of acute PE. Statistical process control (SPC) charts were used to assess monthly trends in utilization and yield. RESULTS: Among 931,677 visits to Emergency Departments, 28,101 CTPAs were performed on 24,675 patients. 14,825 CTPAs were performed among 455,038 visits (3.26%) pre-intervention; 13,276 among 476,639 visits (2.79%) post-intervention, a 14.51% relative decrease in CTPA utilization (chi-square, p<0.001). CTPA yield remained unchanged (1371/14825=9.25% pre- vs. 1184/13276=8.92% post-intervention; chi-square, p=0.34). Patients with COVID diagnosis prior to CTPA had higher probability of acute PE. SPC charts demonstrated seasonal variation in utilization (Friedman test, p=0.047). DISCUSSION: Implementing a CDS based on validated decision rules was associated with a significant reduction in CTPA utilization. The change was immediate and sustained for 12 months post-intervention.