Understanding Emergency Care Delivery Through Computer Simulation Modeling.

In 2017, Academic Emergency Medicine convened a consensus conference entitled, "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes." This article, a product of the breakout session on "understanding complex interactions through systems modeling," explores the role that computer simulation modeling can and should play in research and development of emergency care delivery systems. This article discusses areas central to the use of computer simulation modeling in emergency care research. The four central approaches to computer simulation modeling are described (Monte Carlo simulation, system dynamics modeling, discrete-event simulation, and agent-based simulation), along with problems amenable to their use and relevant examples to emergency care. Also discussed is an introduction to available software modeling platforms and how to explore their use for research, along with a research agenda for computer simulation modeling. Through this article, our goal is to enhance adoption of computer simulation, a set of methods that hold great promise in addressing emergency care organization and design challenges.

Performance of the Hack's Impairment Index Score: A Novel Tool to Assess Impairment from Alcohol in Emergency Department Patients.

BACKGROUND: Over 35 million alcohol-impaired (AI) patients are cared for in emergency departments (EDs) annually. Emergency physicians are charged with ensuring AI patients' safety by identifying resolution of alcohol-induced impairment. The most common standard evaluation is an extemporized clinical examination, as ethanol levels are not reliable or predictive of clinical symptoms. There is no standard assessment of ED AI patients. OBJECTIVE: The objective was to evaluate a novel standardized ED assessment of alcohol impairment, Hack's Impairment Index (HII score), in a busy urban ED. METHODS: A retrospective chart review was performed for all AI patients seen in our busy urban ED over 24 months. Trained nurses evaluated AI patients with both "usual" and HII score every 2 hours. Patients were stratified by frequency of visits for AI during this time: high (≥ 6), medium (2-5), and low (1). Within each category, comparisons were made between HII scores, measured ethanol levels, and usual nursing assessment of AI. Changes in HII scores over time were also evaluated. RESULTS: A total of 8,074 visits from 3,219 unique patients were eligible for study, including 7,973 (98.7%) with ethanol levels, 5,061 (62.7%) with complete HII scores, and 3,646 (45.2%) with health care provider assessments. Correlations between HII scores and ethanol levels were poor (Pearson's R2  = 0.09, 0.09, and 0.17 for high-, medium-, and low-frequency strata). HII scores were excellent at discriminating nursing assessment of AI, while ethanol levels were less effective. Omitting extrema, HII scores fell consistently an average 0.062 points per hour, throughout patients' visits. CONCLUSIONS: The HII score applied a quantitative, objective assessment of alcohol impairment. HII scores were superior to ethanol levels as an objective clinical measure of impairment. The HII declines in a reasonably predictable manner over time, with serial evaluations corresponding well with health care provider evaluations.

Incorporating discrete event simulation into quality improvement efforts in health care systems.

Quality improvement (QI) efforts are an indispensable aspect of health care delivery, particularly in an environment of increasing financial and regulatory pressures. The ability to test predictions of proposed changes to flow, policy, staffing, and other process-level changes using discrete event simulation (DES) has shown significant promise and is well reported in the literature. This article describes how to incorporate DES into QI departments and programs in order to support QI efforts, develop high-fidelity simulation models, conduct experiments, make recommendations, and support adoption of results. The authors describe how DES-enabled QI teams can partner with clinical services and administration to plan, conduct, and sustain QI investigations.

The H-Impairment Index (HII): a standardized assessment of alcohol-induced impairment in the Emergency Department.

BACKGROUND: Emergency Departments (EDs) care for thousands of alcohol-intoxicated patients annually. No clinically relevant bedside measures currently exist to describe degree of impairment. OBJECTIVES: To assess a group of bedside tests ("Hack's Impairment Index [HII] score") that applies a numerical value to the degree of alcohol-induced impairment in ED patients. METHODS: A six-month retrospective review of HII score data was performed in a convenience sample of 293 intoxicated ED patients. Patients were scored 0-4 on five tasks, divided by the maximum score (20 if all tasks completed), every 2 hours; and classified by the number of visits: Low-frequency (1 visit); Medium-frequency (2 visits); High-frequency (≥3 visits). Correlations were assessed between HII score, healthcare provider judgment of intoxication, and measured alcohol levels. RESULTS: Study patients had 513 visits; 236 were low-frequency, 26 middle-frequency and 31 high-frequency. Clinical assessment and HII score were strongly correlated (Spearman's rho = 0.82, p << 0.001); clinical assessment and alcohol level less strongly so (rho = 0.49, p << 0.001). Among low-frequency patients, HII score and alcohol level were weakly correlated (r = 0.324, p < 0.001), with no such correlation among high-frequency visitors (r = -0.04, p = 0.89). The mean decline between serial HII scores was 0.126 (95% CI: 0.098-0.154). CONCLUSION: This pilot study shows the HII score can be performed at the bedside of alcohol-intoxicated patients. The HII declines in a reasonably predictable manner over time; and applies a quantitative, objective assessment of alcohol impairment.

Decreased length of stay after addition of healthcare provider in emergency department triage: a comparison between computer-simulated and real-world interventions.

OBJECTIVE: (1) To determine the effects of adding a provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. (2) To assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics. METHODS: A group-level quasi-experimental trial comparing the St. Louis Veterans Affairs Medical Center emergency department (1) before intervention, (2) after institution of provider in triage, and discrete event simulation (DES) models of similar (3) 'before' and (4) 'after' conditions. The outcome measures were daily mean LOS and percentage of patients with LOS >6 h. RESULTS: The DES-modelled intervention predicted a decrease in the %6-hour LOS from 19.0% to 13.1%, and a drop in the daily mean LOS from 249 to 200 min (p<0.0001). Following (actual) intervention, the number of patients with LOS >6 h decreased from 19.9% to 14.3% (p<0.0001), with the daily mean LOS decreasing from 247 to 210 min (p<0.0001). CONCLUSION: Physician and mid-level provider coverage at triage significantly reduced emergency department LOS in this setting. DES accurately predicted the magnitude of this effect. These results suggest further work in the generalisability of triage providers and in the utility of DES for predicting quantitative effects of process changes.

Use of in situ simulation and human factors engineering to assess and improve emergency department clinical systems for timely telemetry-based detection of life-threatening arrhythmias.

BACKGROUND AND OBJECTIVES: Medical simulation and human factors engineering (HFE) may help investigate and improve clinical telemetry systems. Investigators sought to (1) determine the baseline performance characteristics of an Emergency Department (ED) telemetry system implementation at detecting simulated arrhythmias and (2) improve system performance through HFE-based intervention. METHODS: The prospective study was conducted in a regional referral ED over three 2-week periods from 2010 to 2012. Subjects were clinical providers working at the time of unannounced simulation sessions. Three-minute episodes of sinus bradycardia (SB) and of ventricular tachycardia (VT) were simulated. An experimental HFE-based multi-element intervention was developed to (1) improve system accessibility, (2) increase system relevance and utility for ED clinical practice and (3) establish organisational processes for system maintenance and user base cultivation. The primary outcome variable was overall simulated arrhythmia detection. Pre-intervention system characterisation, post-intervention end-user feedback and real-world correlates of system performance were secondary outcome measures. RESULTS: Baseline HFE assessment revealed limited accessibility, suboptimal usability, poor utility and general neglect of the telemetry system; one simulated VT episode (5%) was detected during 20 pre-intervention sessions. Systems testing during intervention implementation recorded detection of 4 out of 10 arrhythmia simulations (p=0.03). Twenty post-intervention sessions revealed more VT detections (8 of 10) than SB detections (3 of 10) for a 55% overall simulated arrhythmia detection rate (p=0.001). CONCLUSIONS: Experimental investigations helped reveal and mitigate weaknesses in an ED clinical telemetry system implementation. In situ simulation and HFE methodologies can facilitate the assessment and abatement of patient safety hazards in healthcare environments.

Color-coding and human factors engineering to improve patient safety characteristics of paper-based emergency department clinical documentation.

OBJECTIVE: Investigators studied an emergency department (ED) physical chart system and identified inconsistent, small font labeling; a single-color scheme; and an absence of human factors engineering (HFE) cues. A case study and description of the methodology with which surrogate measures of chart-related patient safety were studied and subsequently used to reduce latent hazards are presented. BACKGROUND: Medical records present a challenge to patient safety in EDs. Application of HFE can improve specific aspects of existing medical chart organization systems as they pertain to patient safety in acute care environments. METHODS: During 10 random audits over 5 consecutive days (573 data points), 56 (9.8%) chart binders (range 0.0-23%) were found to be either misplaced or improperly positioned relative to other chart binders; 12 (21%) were in the critical care area. HFE principles were applied to develop an experimental chart binder system with alternating color-based chart groupings, simple and prominent identifiers, and embedded visual cues. RESULTS: Post-intervention audits revealed significant reductions in chart binder location problems overall (p < 0.01), for Urgent Care A and B pods (6.4% to 1.2%; p < 0.05), Fast Track C pod (19.3% to 0.0%; p < 0.05) and Behavioral/Substance Abuse D pod (15.7% to 0.0%; p < 0.05) areas of the ED. The critical care room area did not display an improvement (11.4% to 13.2%; p = 0.40). CONCLUSIONS: Application of HFE methods may aid the development, assessment, and modification of acute care clinical environments through evidence-based design methodologies and contribute to safe patient care delivery.

Commentary: the role of mentored internships for systems engineering in improving health care delivery.

The authors advise the adoption of mentored internships in systems engineering, conducted at academic hospitals, directed by physicians, epidemiologists, and health administrators and overseen by faculty at attendant schools of engineering. Such internships are anticipated to directly address the immediate objectives of administrators and clinicians. Additionally, this affords future generations of health care engineers the opportunity to learn the language and methodology of the medical sciences to provide a common ground for the analysis and understanding of medical systems. In turn, this should foster collaboration between the principal stakeholders in health care delivery--practitioners, administrators, engineers, and researchers--in the collective efforts to improve the quality of services provided.

Reducing motor-vehicle collisions, costs, and fatalities by treating obstructive sleep apnea syndrome.

STUDY OBJECTIVES: Drivers suffering from obstructive sleep apnea syndrome (OSAS) have an increased risk for being involved in motor-vehicle collisions. This study estimates, for the first time, the annual OSAS-related collisions, costs, and fatalities in the United States and performs a cost-benefit analysis of treating drivers suffering from OSAS with continuous positive airway pressure (CPAP). DESIGN: The MEDLINE-PubMed database (1980 to 2003) was searched for information on OSAS. A meta-analysis was performed of studies investigating the relationship between collisions and OSAS. Data from the National Safety Council were used to estimate OSAS-related collisions, costs, and fatalities and their reduction with treatment. Next, the annual cost of treating OSAS with CPAP was calculated. Finally, multiple 1-way sensitivity analyses were performed. SETTING: N/A. PATIENTS OR PARTICIPANTS: N/A. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: More than 800,000 drivers were involved in OSAS-related motor-vehicle collisions in the year 2000. These collisions cost 15.9 billion dollars and 1,400 lives in the year 2000. In the United States, treating all drivers suffering from OSAS with CPAP would cost 3.18 billion dollars, save 11.1 billion dollars in collision costs, and save 980 lives annually. CONCLUSION: Annually, a small but significant portion of motor-vehicle collisions, costs, and deaths are related to OSAS. With CPAP treatment, most of these collisions, costs, and deaths can be prevented. Treatment of OSAS benefits both the patient and the public.