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Objectives Assess the impact of an electronic health record (EHR)‐embedded clinical pathway (ePATH) as compared to a paper‐based clinical decision support tool on outcomes for patients presenting to the emergency department (ED) with suspected acute coronary syndrome (ACS). Methods A retrospective, quasi‐experimental study using difference‐in‐differences and interrupted time series specifications to evaluate the impact of an EHR‐embedded clinical pathway between April 2013 and July 2017. The intervention was implemented in February 2016 at a large academic tertiary hospital and compared to a local community hospital without the intervention. Eligible patients included adults (>18 years) presenting to the ED with chest pain who had a troponin ordered within 2 hours of arrival and a chest pain‐related diagnosis. Patients with initial evidence of acute myocardial infarction were excluded. Primary outcomes included rates of admission and stress testing, hospital length of stay, and occurrence of major adverse cardiac events. Results On average, there were 170 chest pain visits per month at the intervention site. The frequency of hospital admission (unadjusted 28.2% to 20.9%, P

Background Hospital-affiliated freestanding emergency departments (FREDs) are rapidly proliferating in some states and have been the subject of recent policy debate. As FREDs' role in acute care delivery is expanding in certain regions, little is known about the quality of care that they provide for their sickest patients. Our aim was to compare timeliness of emergent care at FREDs and hospital-based EDs (HEDs) for patient visits with selected high-acuity and time-sensitive conditions. Methods We performed a retrospective observational analysis of adult patient visit data from 19 FREDs and five HEDs from one health system over a 1-year period. Median times to events and hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated via Cox regression. Results The median time to electrocardiogram for visits with chest pain was 10 minutes at FREDs and 9 minutes at HEDs (HR = 0.91 [CI = 0.87 to 0.96]). Time to cardiac catheterization lab for visits with ST-segment elevation myocardial infarction (STEMI) was 78 minutes at FREDs, inclusive of transfer time, and 31 minutes at HEDs (HR = 0.41 [CI = 0.24 to 0.71]). Time to computed tomography for visits with stroke was 37 minutes at FREDs and 29 minutes at HEDs (HR = 0.42 [CI = 0.31 to 0.58]). Among visits with sepsis, FREDs had longer times to lactate collection (HR = 0.41 [CI = 0.30 to 0.56]), blood culture collection (HR = 0.24 [CI = 0.11 to 0.51]), and antibiotic administration (HR = 0.61 [CI = 0.26 to 1.42]). Beta agonists were administered for visits with asthma exacerbations in 24 minutes at FREDs and 44 minutes at HEDs (HR = 2.50 [CI = 2.34 to 2.68]), with similar times for anticholinergic and corticosteroid administration. Conclusions Freestanding EDs provided more timely care than HEDs for visits with asthma exacerbation and less timely care for acute chest pain, stroke, and sepsis, although absolute differences were small. Even though STEMI patients at FREDs required transfer for catheterization, they tended to receive care in line with national guidelines.

Background Evaluate an indication‐based clinical decision support tool to improve antibiotic prescribing in the emergency department. Methods Encounters where an antibiotic was prescribed between January 2015 and October 2017 were analyzed before and after the introduction of a clinical decision support tool to improve clinicians’ selection of a guideline‐approved antibiotic based on clinical indication. Evaluation was conducted on a pre‐defined subset of conditions that included skin and soft tissue infections, respiratory infections, and urinary infections. The primary outcome was ordering of a guideline‐approved antibiotic prescription at the drug and duration of therapy level. A mixed model following a binomial distribution with a logit link was used to model the difference in proportions of guideline‐approved prescriptions before and after the intervention. Results For conditions evaluated, selection rate of a guideline‐approved antibiotic for a given indication improved from 67.1% to 72.2% (P < 0.001). When duration of therapy is included as a criterion, selection of a guideline‐approved antibiotic was lower and improved from 24.7% to 31.4% (P < 0.001), highlighting that duration of therapy is often missing at the time of prescribing. The most substantial improvements were seen for pneumonia and pyelonephritis with an increase from 87.9% to 97.5% and 62.8% to 82.6%, respectively. Other significant improvements were seen for abscess, cellulitis, and urinary tract infections. Conclusion Antibiotic prescribing can be improved both at the drug and duration of therapy level using a non‐interruptive and indication based‐clinical decision support approach. Future research and quality improvement efforts are needed to incorporate duration of therapy guidelines into the antibiotic prescribing process.

Background As there has been increasing pressure on acute care services to redefine how their care is delivered, hospital-affiliated freestanding emergency departments (FREDs) have rapidly expanded in some markets. Little is known about the populations served or the quality of care provided by these facilities. Objective The objective of this study was to compare patient visit characteristics, geographic catchment areas, and operational performance between hospital-affiliated FREDs and hospital-based emergency departments (HEDs). Research design This was a population-based retrospective observational analysis of 19 FREDs and 5 HEDs in a single health system over a 1-year period. We abstracted patient visit data from the electronic health record and supplemented catchment area data with the 2016 American Community Survey. We analyzed lengths of stay using generalized linear models adjusted for age, severity, and insurance status. Results FREDs had lower proportions of visits from nonwhite patients and more visits from privately insured patients than HEDs, with similar proportions of uninsured patient visits. These trends were mirrored in catchment area analyses. FRED visits were lower acuity, with fewer imaging and laboratory tests performed. The adjusted mean length of stay for discharged patients was 109 minutes for FREDs compared with 169 minutes for HEDs. For admitted or transferred patients, adjusted lengths of stay were 213 minutes at FREDs and 287 minutes at HEDs. Conclusions Hospital-affiliated FREDs serve more affluent and less diverse patient populations and geographic communities. Relative to HEDs, they have lower acuity patient visits with fewer tests, and they have shorter lengths of stay, even after adjustment for patient visit characteristics.

Objective There are significantly fewer women than men in leadership roles in healthcare. Previous studies have shown that, overall, male physicians earn nearly $20,000 more annually than their female physician colleagues after adjusting for confounding factors. However, there has not been a description of physician leadership compensation in relation to gender. Methods This was a successive cross-sectional observation study design of 154 Emergency Departments (EDs) in the U.S. from five years (2013, 2015-2018) using Association of Academic Chairs in Emergency Medicine & Academy of Administrators in Academic EM survey data. The primary variable of interest, leadership role, was attained by re-coding the survey responses to assign primary job duty into four main categories: no leadership role, operations leadership, education leadership, and executive leadership. Results Overall, 8,820 responses were included. Across all survey years, the average percentage of women in any leadership role was significantly less than men (44.5% [95% CI: ± 1.7%]) vs. 55.3% [95% CI: ± 1.2%]). Women in leadership roles worked more clinical hours than men in the same position (female median = 1,008; male median = 960). Women also had significantly lower salaries than men at each of the five-year time points that data are reported, with unadjusted average salary differences of $-54,409 per year for executives, $-27,803 for operational leaders, and $-17,803 for education leaders. Conclusions Female physicians hold fewer leadership roles in academic EM, and when they do, they work more clinical hours and are paid less than male physicians. As a specialty, emergency medicine should continue to investigate and report out gender achievement disparities as work is done to rectify the system inequalities.

Investors, entrepreneurs, health care pundits, and venture capital firms all agree that the health care sector is awaiting a digital revolution. Steven Case, in 2016, predicted a “third wave” of innovation that would leverage big data, artificial intelligence, and machine learning to transform medicine and finally achieve reduced costs, improved efficiency, and better patient outcomes. Academic medical centers (AMCs) have the infrastructure and resources needed by digital health intrapreneurs and entrepreneurs to innovate, iterate, and optimize technology solutions for the major pain points of modern medicine. With large unique patient data sets, strong research programs, and subject matter experts, AMCs have the ability to assess, optimize, and integrate new digital health tools with feedback at the point of care and research-based clinical validation. As AMCs begin to explore digital health solutions, they must decide between forming internal teams to develop these innovations or collaborating with external companies. Although each has its drawbacks and benefits, AMCs can both benefit from and drive forward the digital health innovations that will result from this journey. This viewpoint will provide an explanation as to why AMCs are ideal incubators for digital health solutions and describe what these organizations will need to be successful in leading this “third wave” of innovation.

UNSTRUCTURED Investors, entrepreneurs, healthcare pundits, and venture capital firms all agree that the healthcare sector is an antiquated beast awaiting a digital disruption. Technology adoption in healthcare occurs at a glacial pace but this has not prevented bullish investments in digital health solutions in the past 10 years. Steven Case predicted a “third wave” of innovation in 2016 that would leverage big data, artificial intelligence, and machine learning to transform medicine and finally achieve the reduced costs and improved outcomes demanded by the public. Academic health systems already have the infrastructure needed by digital health entrepreneurs to innovate, iterate and optimize technology solutions for the major pain points of modern medicine. With implementation scientists, large patient panels, strong research programs, and multidisciplinary providers, academic health institutions have the ability to assess new digital solutions with mentored testing, feedback at the point of care and clinical validation. The largest hurdle for academic health systems is the intolerance for financial risk when investing time and money into start-up ideas which have a high likelihood of failing fast. The bottom line of academic health systems does not support these endeavors but the need for change is evident and now is the opportunity to change how medicine will be practiced for the next 50 years. This is a call upon academic institutions and the nation’s clinical leaders to lead the “third wave” of innovation and truly optimize care delivery, improve patient outcomes, and bend the cost curve.

Despite decades of effort to drive quality improvement, many health care organizations still struggle to optimize their performance on quality metrics. The advent of publicly reported quality rankings and ratings allows for greater visibility of overall organizational performance, but has not provided a roadmap for sustained improvement in these assessments. Most quality training programs have focused on developing knowledge and skills in pursuit of individual and project-level improvements. To date, no training program has been associated with improvements in overall organization-level, publicly reported measures. In 2012, the Institute for Health care Quality, Safety, and Efficiency was launched, which is an integrated set of quality and safety training programs, with a focus on leadership development and support of performance improvement through data analytics and intensive coaching. This effort has trained nearly 2000 individuals and has been associated with significant improvement in organization-level quality rankings and ratings, offering a framework for organizations seeking systematic, long-term improvement.

Study Objective: To determine whether deployment of an integrated virtual sepsis surveillance program could improve time to antibiotics and mortality in a longitudinal cohort of non-present on admi...

Introduction Post-procedural debrief is recommended to improve patient safety. We examined operating room (OR) clinicians’ perceptions of the impact of a multi-disciplinary debrief on OR culture. Methods A survey was administered to 182 OR clinicians at a major academic medical center. Attitudes toward the surgical debrief and its effect on patient safety and OR culture were evaluated. Results Majority of clinicians (58.2%) believed creating a culture of safety in the OR was a shared care team responsibility, however, surgical attendings and trainees were more likely to assign this responsibility to the surgical attending. Few circulating nurses and trainees felt comfortable initiating a surgical debrief. Overall clinicians agreed that a debrief would impact both patient safety outcomes and OR culture. Conclusions Clinicians felt implementation of a surgical debrief would positively affect the OR culture of safety by improving interdisciplinary communication and influencing the power hierarchy that exists in many ORs.

Many high utilizers of the emergency department (ED) have public insurance, especially through Medicaid. We evaluated how participation in Bridges to Care (B2C)-an ED-initiated, multidisciplinary, community-based program-affected subsequent ED use, hospital admissions, and primary care use among publicly insured or Medicaid-eligible high ED utilizers. During the six months after the B2C intervention was completed, participants had significantly fewer ED visits (a reduction of 27.9 percent) and significantly more primary care visits (an increase of 114.0 percent), compared to patients in the control group. In a subanalysis of patients with mental health comorbidities, we found that recipients of B2C services had significantly fewer ED visits (a reduction of 29.7 percent) and hospitalizations (30.0 percent), and significantly more primary care visits (an increase of 123.2 percent), again compared to patients in the control group. The B2C program reduced acute care use and increased the number of primary care visits among high ED utilizers, including those with mental health comorbidities.

While there has been considerable effort devoted to developing alternative payment models (APMs) for primary care physicians and for episodes of care beginning with inpatient admissions, there has been relatively little attention by payers to developing APMs for specialty ambulatory care, and no efforts to develop APMs that explicitly focus on emergency care. In order to ensure that emergency care is appropriately integrated and valued in future payment models, emergency physicians (EPs) must engage with the stakeholders within the broader health care system. In this article, we describe a framework for the development of APMs for emergency medicine and present four examples of APMs that may be applicable in emergency medicine. A better understanding of how APMs can work in emergency medicine will help EPs develop new APMs that improve the cost and quality of care, and leverage the value that emergency care brings to the system.

OBJECTIVE The objective was to evaluate the impact of evidence-based clinical decision support tools integrated directly into provider workflow in the electronic health record on utilization of computed tomography (CT) brain, C-spine, and pulmonary embolism (PE). METHODS Validated, well-accepted scoring tools for head injury, C-spine injury, and PE were embedded into the electronic health record in a manner minimally disruptive to provider workflow. This was a longitudinal, before/after study in five emergency departments (EDs) in a healthcare system with a common electronic health record. Attending ED physicians practicing during the entire study period were included. The main outcome measure was proportion of CTs ordered by provider (total number of CT scans of a given type divided by total patients seen by that provider) in aggregate in the pre- and post intervention period. RESULTS There were 235,858 total patient visits analyzed in this study with an absolute decrease of 6,106 CT scan ordering for the three studies. Across all sites, there was greater than 6% decrease in utilization of CT brain and CT C-spine (-10%, 95% CI = -13% to -7%, p

Purpose We describe an interdisciplinary community-academic program that teaches students how to assess and address social determinants of health (SDH) and population health for patients using the emergency department (ED). Method Twelve students from multiple disciplines participated in the Hot Spotters Student Program (HSSP). The students conducted SDH assessments on 456 patients and visited 11 different local community organizations. Results Student focus group analysis identified three main themes: 1) previous lack of awareness or educational training about social determinants of health and health inequities, 2) self-noted post-program professional and educational growth, and 3) increased community awareness and engagement.

The high prevalence of compassion fatigue contributes to burnout among oncology nurses. Interventions are needed to support individuals across diverse roles and practice settings in oncology. Virtual reality (VR) is an emerging technology that has been applied in healthcare education and training and is being explored as an intervention to reduce stress and support wellness for healthcare providers. This article reviews recommendations from an implementation project about a VR intervention for oncology nurses.

BackgroundEmergency department (ED) crowding is a critical problem in the delivery of acute unscheduled care. Many causes are external to the ED, but antiquated operational traditions like triage also contribute. A physician intake model has been shown to be beneficial in a single-centre study, but whether this solution is generalisable is not clear. We aimed to characterise the current state of front-end intake models in a national sample of EDs and quantify their effects on throughput measures.MethodsWe performed a descriptive mixed-method analysis of ED process changes implemented by a cross section of self-selecting institutions who reported 2 years of demographic/operational data and structured process descriptions of any ‘new front-end processes to replace traditional nurse-based triage’.ResultsAmong 25 participating institutions, 19 (76%) provided data. While geographically diverse, most were urban, academic adult level 1 trauma centres. Thirteen (68%) reported implementing a new intake process. All were run by attending emergency physicians, and six (46%) also included advanced practice providers. Daily operating hours ranged from 8 to 16 (median 12, IQR 10.25–15.85), and the majority performed labs, imaging and medication administration and directly discharged patients. Considering each site’s before-and-after data as matched pairs, physician-driven intake was associated with mean decreases in arrival-to-provider time of 25 min (95% CI 13 to 37), ED length of stay 36 min (95% CI 12 to 59), and left before being seen rate 1.2% (95% CI 0.6% to 1.8%).ConclusionsIn this cross section of primarily academic EDs, implementing a physician-driven front-end intake process was feasible and associated with improvement in operational metrics.

Study objective Accountable care organizations are provider networks aiming to improve quality while reducing costs for populations. It is unknown how value-based care within accountable care organizations affects emergency medicine care delivery and payment. Our objective was to describe how accountable care has impacted emergency care redesign and payment. Methods We performed a qualitative study of accountable care organizations, consisting of semistructured interviews with emergency department (ED) and accountable care organization leaders responsible for strategy, care redesign, and payment. We analyzed transcripts for key themes, using thematic analysis techniques. Results We performed 22 interviews across 7 accountable care organizations. All sites were enrolled in the Medicare Shared Savings Program; however, sites varied in region and maturity with respect to population health initiatives. Nearly all sites were focused on reducing low-value ED visits, expanding alternate venues for acute unscheduled care, and redesigning care to reduce ED admission rates through expanded care coordination, including programs targeting high-risk populations such as older adults and frequent ED users, telehealth, and expanded use of direct transfer to skilled nursing facilities from the ED. However, there has been no significant reform of payment for emergency medical care within these accountable care organizations. Nearly all informants expressed concern in regard to reduced ED reimbursement, given accountable care organization efforts to reduce ED utilization and increase clinician participation in alternative payment contracts. No participants expressed a clear vision for reforming payment for ED services. Conclusion Care redesign within accountable care organizations has focused on outpatient access and alternatives to hospitalization. However, there has been little influence on emergency medicine payment, which remains fee for service. Evidence-based policy solutions are urgently needed to inform the adoption of value-based payment for acute unscheduled care.

Background: Direct-to-consumer (DTC) virtual urgent care (VUC) visits are increasingly popular across both for-profit and nonprofit healthcare systems; however, few peer-reviewed studies have described the ecology of a VUC program. Design/Setting: In this retrospective cohort study, patients (N = 2,216) received care through a VUC platform offered by a regional health system over an approximately 2-year period. Results: Seventy-one percent of patients were identified as females. The age of the patients ranged from 18 to 85 years (median 39 years, interquartile range [IQR] 32–49 years). Eighty-four percent (n = 1,906) of patients had a registered primary care provider (PCP), while 177 (8%) chose to self-pay for the VUC service. Seventy-six percent of visits occurred between Monday and Friday, and 71% (n = 1,573) visits occurred between 8 am and 6 pm. The median provider response time was 24 minutes. Visits were conducted by videoconference 84% of the time; providers and patients spent a median of 7.4 minutes (IQR 4.3, 9.9 min) together in the video room. Seventy-seven percent of visits generated a prescription, of which 70% were on antibiotics. Conclusions: Most virtual visits were initiated by existing health system patients with a primary care physician, and the majority of patients sought care during usual business hours. Most visits led to a prescription, most commonly an antibiotic. These data can help inform operational leaders who are considering how best to structure, staff, and develop key performance indicators for their own VUC programs. Additionally, these data challenge the notion that acute, episodic DTC encounters occur after-hours and are utilized by uninsured patients who lack a relationship with a primary care physician.

Evaluate nine different models, the interaction of three flow models (ESI, intake attending physician, and no split flow) and three physical design typologies (zero, one, and two internal-waiting areas), on Emergency Department (ED) flow and patient-centered metrics.Discrete Event Simulation (DES) was used to systematically manipulate flow and physical design. Three base models were developed and validated using ED and patient specific data. Subsequently, systematic manipulations of flow and internal-waiting areas were performed on other models. Five outcomes of interest were tracked - length of stay (LOS), bed utilization rate, door to provider time, left without being seen rate, and number of movements per patient. Models were compared for statistical significance and effect size using ANOVA, and linear and non-linear regression.The shortest LOS (mean 175.2 min) and highest bed utilization rate (5.02 patients/bed/day) were obtained with flow split by an intake attending physician with two internal-waiting areas. These represented improvements of 54 min and 1.48 patients/bed/day over the control model. Two-way ANOVA demonstrated that both physical design and flow type were statistically significant predictors of all outcomes of interest (p .0001). Depending on flow type, adding one additional internal-waiting area resulted in decreased LOS (range 10.6-21.8 min), increased bed utilization (range 0.23-0.40 patients/bed/day), decreased D2P (range 1.3-4.8 min), and decreased LWBS (0.66%-2.0%).Based on a DES model with empirical data from a single institution, combining flow split by an intake attending physician and multiple internal-waiting areas resulted in improved ED operational and patient-centered metrics.

Health care systems have utilized various process redesign methodologies to improve care delivery. This article describes the creation of a novel process improvement methodology, Rapid Process Optimization (RPO). This system was used to redesign emergency care delivery within a large academic health care system, which resulted in a decrease: (1) door-to-physician time (Department A: 54 minutes pre vs 12 minutes 1 year post; Department B: 20 minutes pre vs 8 minutes 3 months post), (2) overall length of stay (Department A: 228 vs 184; Department B: 202 vs 192), (3) discharge length of stay (Department A: 216 vs 140; Department B: 179 vs 169), and (4) left without being seen rates (Department A: 5.5% vs 0.0%; Department B: 4.1% vs 0.5%) despite a 47% increased census at Department A (34 391 vs 50 691) and a 4% increase at Department B (8404 vs 8753). The novel RPO process improvement methodology can inform and guide successful care redesign.

OBJECTIVE This study aimed to develop an emergency department (ED) trigger tool to improve the identification of adverse events in the ED and that can be used to direct patient safety and quality improvement. This work describes the first step toward the development of an ED all-cause harm measurement tool by experts in the field. METHODS We identified a multidisciplinary group of emergency medicine safety experts from whom we solicited candidate triggers. We then conducted a modified Delphi process consisting of 4 stages as follows: (1) a systematic literature search and review, including an independent oversampling of review for inclusion, (2) solicitation of empiric triggers from participants, (3) a Web-based survey ranking triggers on specific performance constructs, and (4) a final in-person meeting to arrive at consensus triggers for testing. Results of each step were shared with participants between each stage. RESULTS Among an initial 804 unique articles found using our search criteria, we identified 94 that were suitable for further review. Interrater reliability was high (κ = 0.80). Review of these articles yielded 56 candidate triggers. These were supplemented by 58 participant-submitted triggers yielding a total of 114 candidate triggers that were shared with team members electronically along with their definitions. Team members then voted on each measure via a Web-based survey, ranking triggers on their face validity, utility for quality improvement, and fidelity (sensitivity/specificity). Participants were also provided the ability to flag any trigger about which they had questions or they felt merited further discussion at the in-person meeting. Triggers were ranked by combining the first 2 categories (face validity and utility), and information on fidelity was reviewed for decision making at the in-person meeting. Seven redundant triggers were eliminated. At an in-person meeting including representatives from all facilities, we presented the 50 top-ranked triggers as well as those that were flagged on the survey by 2 or more participants. We reviewed each trigger individually, identifying 41 triggers about which there was a clear agreement for inclusion. Of the seven additional triggers that required subsequent voting via e-mail, 5 were adopted, arriving at a total of 46 consensus-derived triggers. CONCLUSIONS Our modified Delphi process resulted in the identification of 46 final triggers for the detection of adverse events among ED patients. These triggers should be pilot field tested to quantify their individual and collective performance in detecting all-cause harm to ED patients.

Background The Affordable Care Act has added millions of new Medicaid enrollees to the health care system. These patients account for a large proportion of emergency department (ED) utilization. Objective Our aim was to characterize this population and their ED use at a national level. Methods We used the 2010 National Hospital Ambulatory Medical Care Survey (NHAMCS) to describe demographics and clinical characteristics of nonelderly adults (≥18 years old and ≤64 years old) with Medicaid-covered ED visits. We defined frequent ED users as individuals who make ≥4 ED visits/year and business hours as 8 am to 5 pm . We used descriptive statistics to describe the epidemiology of Medicaid-covered ED visits. Results NHAMCS included 21,800 ED visits by nonelderly adults in 2010, of which 5,659 (24.09%) were covered by Medicaid insurance. Most ED visits covered by Medicaid were made by patients who are young (25 and 44 years old) and female (67.95%; 95% confidence interval [CI] 66.00–69.89). A large proportion of the ED visits covered by Medicaid were revisits within 72 h (14.66%; 95% CI 9.13–20.19) and from frequent ED users (32.32%; 95% CI 24.29–40.35). Almost half of all ED visits covered by Medicaid occurred during business hours (45.44%; 95% CI 43.45–47.43). Conclusions The vast majority of Medicaid enrollees who used the ED were young females, with a large proportion of visits occurring during business hours. Almost one-third of all visits were from frequent ED users.

OBJECTIVES The objective was to identify the effects of gender and other predictors of change in the salary of academic emergency physicians over a four sequential time period of survey administration, across a sample of physicians within different emergency departments (EDs) and within states representing the four main geographical regions of the United States. METHODS This was a successive cross-sectional observational study of EDs in the United States using an annual salary survey distributed to all Association of Academic Chairs in Emergency Medicine (AACEM) and Academy of Administrators in Academic Emergency Medicine (AAAEM) members in 2013, 2015, 2016, and 2017 with a sample size of 7,102 respondents over all time periods. The primary variable of interest was the adjusted base salary, calculated to be the full-time effort of the physician without any enhancements (e.g., without stipend, release time, extra hours). Institutional predictive variables included U.S. region that ED was in and if the site was an academic or community academic hybrid ("community") ED. Individual level variables included gender, academic rank, years at academic rank, years at rank within the ED, and primary duty (clinical or other). A series of Wilcoxon tests were conducted to determine if the unadjusted difference in salaries by gender for each year of the survey were significantly different. The effects of relative change in adjusted base salary over time were assessed using a mixed-effects regression model, with institutional- and individual-level predictors included in the model. RESULTS Data were provided by 81 departments across the four geographic regions of the United States (Northeast, South, West, and Midwest). Most of the survey respondents across the four time periods of administration were male (65%) and reported primary clinical appointments at an academic ED (94%). Overall salaries increased across the four time points of the data with an overall relative 10.8% (95% confidence interval [CI] = 9.6%-12%) change in median salary between 2013 and 2017; the relative percentage change for female respondents was 10.6% (95% CI = 9.4%-11.85%) and 11.1% (95% CI = 10.2%-12%) for males. Within survey years, not adjusting for academic rank, the median salary increase for males was higher ($226,746 in 2013 to $252,000 in 2017) than females ($217,000 in 2013 to $240,000 in 2017), with significance at all four time points (Z = 6.33, p

Accountable Care Organizations (ACOs) are integrated provider groups aiming to improve health care value for a population. Hospitalizations account for ~ 32% of US health care expenditures, and ED visits account for up to 6%; therefore, one strategy to improve value is to manage the acute care needs of the population in lower cost settings.1 To date, most cost-reduction efforts have focused on improving chronic disease management, for example, through medication management and decreasing readmissions.2 We aim to describe how ACOs are prioritizing cost-reduction strategies related to acute unscheduled care using responses from a national survey of ACOs.

OBJECTIVES Quality and safety review for performance improvement is important for systems of care and is required for US academic emergency departments (EDs). Assessment of the impact of patient safety initiatives in the context of increasing burdens of quality measurement compels standardized, meaningful, high-yield approaches for performance review. Limited data describe how quality and safety reviews are currently conducted and how well they perform in detecting patient harm and areas for improvement. We hypothesized that decades-old approaches used in many academic EDs are inefficient and low yield for identifying patient harm. METHODS We conducted a prospective observational study to evaluate the efficiency and yield of current quality review processes at five academic EDs for a 12-month period. Sites provided descriptions of their current practice and collected summary data on the number and severity of events identified in their reviews and the referral sources that led to their capture. Categories of common referral sources were established at the beginning of the study. Sites used the Institute for Healthcare Improvement's definition in defining an adverse event and a modified National Coordinating Council for Medication Error Reporting and Prevention (MERP) Index for grading severity of events. RESULTS Participating sites had similar processes for quality review, including a two-level review process, monthly reviews and conferences, similar screening criteria, and a grading system for evaluating cases. In 60 months of data collection, we reviewed a total of 4735 cases and identified 381 events. This included 287 near-misses, errors/events (MERP A-I) and 94 adverse events (AEs) (MERP E-I). The overall AE rate (event rate with harm) was 1.99 (95% confidence interval = 1.62%-2.43%), ranging from 1.24% to 3.47% across sites. The overall rate of quality concerns (events without harm) was 6.06% (5.42%-6.78%), ranging from 2.96% to 10.95% across sites. Seventy-two-hour returns were the most frequent referral source used, accounting for 47% of the cases reviewed but with a yield of only 0.81% in identifying harm. Other referral sources similarly had very low yields. External referrals were the highest yield referral source, with 14.34% (10.64%-19.03%) identifying AEs. As a percentage of the 94 AEs identified, external referrals also accounted for 41.49% of cases. CONCLUSIONS With an overall adverse event rate of 1.99%, commonly used referral sources seem to be low yield and inefficient for detecting patient harm. Approximately 6% of the cases identified by these criteria yielded a near miss or quality concern. New approaches to quality and safety review in the ED are needed to optimize their yield and efficiency for identifying harm and areas for improvement.

Access to acute and emergency care is essential when we are ill or injured, but the costs are significant. How can we make services more efficient and effective? This thought-provoking text provides twenty case studies detailing successful innovations to enhance value, including telehealth, observation medicine, high utilizer programs, and the use of informatics to improve clinical decision support. A detailed history of system developments over the last fifty years in the US and internationally is provided, and subjects including measurement and quality improvement, volume versus value based care, and emergency department crowding are discussed. This book is an ideal way for emergency physicians and healthcare managers to explore new ideas and enhance the quality of care in their area.

Objectives Policymakers have increasingly focused on emergency department (ED) utilization for primary care–treatable conditions as a potentially avoidable source of rising health care costs. The objective was to determine the association of health insurance type and arrival time, as indicators of limited availability of primary care, with primary care–treatable classification of ED visits. Methods This was a retrospective analysis of a nationally representative sample of 241,167 ED visits from the 1997 to 2009 National Hospital Ambulatory Medical Care Surveys (NHAMCS). Probabilities of ED visits being primary care–treatable were categorized based on the primary International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code. The association of health insurance type and arrival time was determined with the average probability of the primary diagnosis being primary care–treatable using multivariable linear regression. Results Compared to privately insured visits, Medicaid visits had a 1.7% (95% confidence interval [CI] = 1.2% to 2.2%) and uninsured visits a 2.4% (95% CI = 1.9% to 3.0%) higher probability of primary care–treatable classification, while Medicare visits had a 1.4% (95% CI = 0.7% to 2.0%) lower probability during the overall study period. Compared to business hours, weekend visits had a 1.5% (95% CI = 1.0% to 2.0%) higher probability of being primary care–treatable during the overall study period. From 1997 to 2009, the overall adjusted probability of ED visits being primary care–treatable increased by 0.19% (95% CI = 0.10 to 0.28) per year. This probability increased at a rate of 0.52% per year for Medicare visits (95% CI = 0.38% to 0.65%), more than double that of Medicaid visits (0.25% per year, 95% CI = 0.13% to 0.37%). By contrast, there was no significant change from 1997 to 2009 in the average probability of ED visits being primary care–treatable by privately insured (0.05% per year, 95% CI = –0.07 to 0.16) or uninsured (0.00% per year, 95% CI = –0.12 to 0.13) individuals. Conclusions These findings add to prior work that implicates insurance type and arrival time in the variation of primary care–treatable ED visits. Although primary care–treatable classification of ED visits was most associated with uninsured or Medicaid visits, this classification increased most rapidly among Medicare visits during the study period. Resumen Objetivos Los politicos se han centrado cada vez mas en la utilizacion del servicio de urgencias (SU) en patologias tratables en atencion primaria (TAP) como una fuente potencialmente evitable de incrementar los costes del sistema sanitario. El objetivo fue determinar la asociacion del tipo de seguro sanitario y el tiempo de llegada, como indicadores de disponibilidad limitada, con la clasificacion de patologias TAP de las visitas al SU. Metodologia Analisis retrospectivo de una muestra representative nacional de 241.167 visitas al SU desde 1997 a 2009 de las National Hospital Ambulatory Medical Care Surveys. Las probabilidades de visita al SU por procesos TAP se categorizaron basandose en la codificacion CIE-9-MC. La asociacion del tipo de seguro sanitario y el tiempo de llegada se determino con la probabilidad promedio de diagnostico principal de ser TAP usando un analisis multivariable de regresion lineal. Resultados En comparacion a las visitas de los asegurados de forma privada, las visitas Medicaid tuvieron un 1,7% (IC 95% = 1,2% a 2,2%) y las visitas de los no asegurados un 2,4% (IC 95%= 1,9% a 3,0%) de mayor probabilidad de clasificacion como TAP, mientras que las visitas Medicare tuvieron un 1,4% (IC 95% = 0,7% a 2,0%) de menor probabilidad durante todo el periodo del estudio. En comparacion con la horas de trabajo, las visitas los fines de semana tuvieron un 1,5% (IC 95% = 1,0% a 2,0%) de mayor probabilidad de ser TAP durante todo el periodo del estudio. Desde 1997 a 2009, la probabilidad ajustada global de visitas al SU por procesos TAP se incremento un 0,19% (IC 95% =0,10 a 0,28) por ano. Este probabilidad incremento un porcentaje de un 0,52% por ano para las visitas Medicare (IC 95% =0,38% a 0,65%), mas del doble que las visitas Medicaid (0,25% por ano, IC 95% = 0,13% a 0,37%). En contraste, no hubo un cambio significativo de 1997 a 2009 en la probabilidad media de visitas al SU por procesos TAP en los individuos asegurados de forma privada (0,05% por ano, IC 95% = –0,07 a 0,16) o no asegurados (0,00% por ano, IC 95% = –0,12 a 0,13). Conclusiones Estos resultados anaden a los trabajos previos la implicacion del tipo de seguro y el tiempo de llegada en la variacion de las visitas al SU por procesos TAP. Aunque la calificacion de TAP de las visitas al SU se asocio con visitas de los no asegurados o Medicaid, esta clasificacion incremento mas rapidamente entre las visitas Medicare durante el periodo del estudio.

The proliferation of technology enthuses clinicians, researchers, and entrepreneurs to revolutionize health care and care delivery. Intersecting in the field of digital health, academic-industry collaboration (AIC) play a critical role in advancing evidence-based innovations into real world application. AIC models vary, but historically have not included the strong emphasis on rapid research and discovery that the digital health field demands. Due to the voluminous availability of real time patient and client data, academic health centers offer a rich interdisciplinary environment to develop, pilot and evaluate innovations in pragmatic settings. Despite the opportunity between academic health centers and industry to advance digital health innovation through rapid research, limited evidence exists of such collaboration. The purpose of this case report is to examine an AIC facilitating research of new health technologies within an academic health center. This paper presents a case report involving collaboration between diverse technology industry partners and an academic health center that encompasses a university health system (UCHealth), a university technology transfer office (CU Innovations), an innovation center (CARE Innovation Center), and research collaborators (mHealth Impact Laboratory). Case assertions discuss the lessons learned and recommendations when implementing such collaboration in practice. The principal finding is that academic health centers offer an innovative environment for AIC in digital health. Collaborations between academia and industry provide much promise in ensuring health innovations are scientifically sound while meeting the needs of a rapidly evolving technical climate.

Introduction: Reducing non-urgent emergency department (ED) visits has been targeted as a method to produce cost savings. To better describe these visits, we sought to compare resource utilization of ED visits characterized as non-urgent at triage to immediate, emergent, or urgent (IEU) visits.Methods: We performed a retrospective, cross-sectional analysis of the 2006-2009 National Hospital Ambulatory Medical Care Survey. Urgency of visits was categorized using the assigned 5-level triage acuity score. We analyzed resource utilization, including diagnostic testing, treatment, and hospitalization within each acuity categorization.Results: From 2006-2009, 10.1% (95% confidence interval [CI], 9.2-11.2) of United States ED visits were categorized as non-urgent. Most (87.8% [95%CI, 86.3-89.2]) non-urgent visits had some diagnostic testing or treatment in the ED. Imaging was common in non-urgent visits (29.8% [95%CI, 27.8-31.8]), although not as frequent as for IEU visits (52.9% [95%CI, 51.6-54.2]). Similarly, procedures were performed less frequently for non-urgent (34.1% [95%CI, 31.8-36.4]) compared to IEU visits (56.3% [95%CI, 53.5-59.0]). Medication administration was similar between the 2 groups (80.6% [95%CI, 79.5-81.7] vs. 76.3% [95% CI, 74.7-77.8], respectively). The rate of hospital admission was 4.0% (95%CI, 3.3-4.8) vs. 19.8% (95%CI, 18.4-21.3) for IEU visits, with admission to a critical care setting for 0.5% of non-urgent visits (95%CI, 0.3-0.6) vs. 3.4% (95%CI, 3.1-3.8) of IEU visits.Conclusions: For most non-urgent ED visits, some diagnostic or therapeutic intervention was performed. Relatively low, but notable proportions of non-urgent ED visits were admitted to the hospital, sometimes to a critical care setting. These data call into question non-urgent ED visits being categorized as “unnecessary,” particularly in the setting of limited access to timely primary care for acute illness or injury. [West J Emerg Med.609-616.]

Objectives The objective was to derive and validate a novel queuing theory–based model that predicts the effect of various patient crowding scenarios on patient left without being seen (LWBS) rates. Methods Retrospective data were collected from all patient presentations to triage at an urban, academic, adult-only emergency department (ED) with 87,705 visits in calendar year 2008. Data from specific time windows during the day were divided into derivation and validation sets based on odd or even days. Patient records with incomplete time data were excluded. With an established call center queueing model, input variables were modified to adapt this model to the ED setting, while satisfying the underlying assumptions of queueing theory. The primary aim was the derivation and validation of an ED flow model. Chi-square and Student's t-tests were used for model derivation and validation. The secondary aim was estimating the effect of varying ED patient arrival and boarding scenarios on LWBS rates using this model. Results The assumption of stationarity of the model was validated for three time periods (peak arrival rate = 10:00 a.m. to 12:00 p.m.; a moderate arrival rate = 8:00 a.m. to 10:00 a.m.; and lowest arrival rate = 4:00 a.m. to 6:00 a.m.) and for different days of the week and month. Between 10:00 a.m. and 12:00 p.m., defined as the primary study period representing peak arrivals, 3.9% (n = 4,038) of patients LWBS. Using the derived model, the predicted LWBS rate was 4%. LWBS rates increased as the rate of ED patient arrivals, treatment times, and ED boarding times increased. A 10% increase in hourly ED patient arrivals from the observed average arrival rate increased the predicted LWBS rate to 10.8%; a 10% decrease in hourly ED patient arrivals from the observed average arrival rate predicted a 1.6% LWBS rate. A 30-minute decrease in treatment time from the observed average treatment time predicted a 1.4% LWBS. A 1% increase in patient arrivals has the same effect on LWBS rates as a 1% increase in treatment time. Reducing boarding times by 10% is expected to reduce LWBS rates by approximately 0.8%. Conclusions This novel queuing theory–based model predicts the effect of patient arrivals, treatment time, and ED boarding on the rate of patients who LWBS at one institution. More studies are needed to validate this model across other institutions. Resumen Un Modelo de Flujo de Pacientes a traves del Servicio de Urgencias Basado en los Principios de la Teoria de Colas Objetivos Derivar y validar un modelo novedoso basado en la teoria de colas que predice el impacto de varios escenarios de saturacion de pacientes en el porcentaje de pacientes dados de alta sin ser atendidos (PDASSA). Metodologia Se recogieron retrospectivamente los datos de todas las visitas de pacientes al triaje de un servicio de urgencias (SU) solo para adultos, urbano y universitario, que recibio 87.705 visitas el ano 2008. Los datos de las franjas horarias diarias predefinidas se dividieron en grupos de derivacion y validacion basados en dias pares e impares. Se excluyeron las historias de pacientes con datos incompletos de tiempo. Usando un modelo de colas establecido de centralita de llamadas, se modificaron las variables de entrada para adaptar este modelo al escenario del SU, mientras se satisfacian los supuestos subyacentes de la teoria de colas. El objetivo principal fue la derivacion y la validacion de un modelo de flujo del SU. Se utilizaron los test de la t de Student y de ji-cuadrado para la derivacion y la validacion del modelo. El objetivo secundario fue estimar el impacto de la variacion en la llegada de pacientes al SU y los escenarios de tiempo de espera en el porcentaje de PDASSA usando este modelo. Resultados El supuesto estacionario del modelo fue validado para tres periodos de tiempo, el porcentaje de pico de llegada (10:00am a 12:00 p.m.), el porcentaje de llegada moderada (8:00 a.m. a 10:00 a.m.) y el porcentaje de menos llegada (4:00 a.m. a 6:00 a.m.) para diferentes dias de la semana y mes. Entre las 10:00 a.m. y 12:00 p.m., definido como el principal periodo del estudio que representa el pico de llegadas, el 3,9% (n = 4.038) de casos fueron PDASSA. Mediante el modelo derivado, el porcentaje de PDASSA declarado fue de un 4%. Los porcentajes se incrementaron a la vez que se incrementaba el porcentaje de llegadas de pacientes al SU, los tiempos de tratamiento y los tiempos de espera de cama del SU. Un incremento de un 10% en las llegadas horarias de pacientes al SU por encima del porcentaje de llegadas medio observado incremento el porcentaje de PDASSA predicho al 10,8%; un 10% de descenso en las llegadas horarias de pacientes al SU por debajo del porcentaje medio de llegadas observadas predijo un porcentaje de PDASSA de un 1,6%. Un descenso de 30 minutos en el tiempo de tratamiento por debajo del tiempo de tratamiento medio observado predijo un 1,4% de PDASSA. Un 1% de incremento en la llegada de pacientes tiene el mismo efecto en los porcentajes de PDASSA que un incremento del 1% en el tiempo de tratamiento. La reduccion de los tiempos de espera de cama en un 10% reduciria los porcentajes de PDASSA aproximadamente en un 0,8%. Conclusiones Este novedoso modelo basado en la teoria de colas predice el impacto de las llegadas de los pacientes, el tiempo de tratamiento y el tiempo de espera de cama del SU sobre el porcentaje de PDASSA en una institucion. Son necesarios mas estudios para validar este modelo en otras instituciones.