Stephen J. Traub

Diagnosis of reversible causes of coma

Because coma has many causes, physicians must develop a structured, algorithmic approach to diagnose and treat reversible causes rapidly. The three main mechanisms of coma are structural brain lesions, diffuse neuronal dysfunction, and, rarely, psychiatric causes. The first priority is to stabilise the patient by treatment of life-threatening conditions, then to use the history, physical examination, and laboratory findings to identify structural causes and diagnose treatable disorders. Some patients have a clear diagnosis. In those who do not, the first decision is whether brain imaging is needed. Imaging should be done in post-traumatic coma or when structural brain lesions are probable or possible causes. Patients who do not undergo imaging should be reassessed regularly. If CT is non-diagnostic, a checklist should be used use to indicate whether advanced imaging is needed or evidence is present of a treatable poisoning or infection, seizures including non-convulsive status epilepticus, endocrinopathy, or thiamine deficiency.

Risk Factors for Radiocontrast Nephropathy After Emergency Department Contrast- enhanced Computerized Tomography

OBJECTIVES Radiocontrast nephropathy (RCN) is a known complication of procedures in which intravascular iodinated contrast material is used. The authors sought to determine the risk factors for RCN after emergency department (ED) contrast-enhanced computerized tomography (CECT). METHODS This was a retrospective case-control study of patients presenting to a tertiary care ED between January 1, 2004, and December 31, 2006. Inclusion criteria were CECT performed in the ED, serum creatinine measured prior to CECT, and serum creatinine measured 48 to 96 hours after CECT. Exclusion criterion was dialysis-dependent renal failure prior to CECT. The outcome of RCN was defined as an absolute creatinine increase of greater than or equal to 0.5 mg/dL, or a 25% increase above baseline. The charts of all RCN patients and a random sample of non-RCN patients were reviewed to document the presence or absence of potential risk factors. Univariate analysis was performed using chi-square and multiple logistic regression applying a weighted technique to account for sampling of non-RCN patients. RESULTS Among the 5,006 patients meeting inclusion criteria, 349 (7%) developed RCN. Multiple regression analysis demonstrated that serum creatinine > 2 mg/dL, liver disease, heart failure, hematocrit < 30%, hypertension, and diabetes were risk factors for RCN, whereas age > 75 years, vascular disease, and serum creatinine > 1.5 mg/dL were not. The area under the curve (AUC) for the model was 0.65. Although the risk of RCN increased with the number of risk factors present, we could not develop a model with sufficient diagnostic accuracy to guide clinical decision-making. CONCLUSIONS The authors report risk factors for RCN in a large case-control study, but could not develop an accurate decision tool to identify patients at increased risk for RCN after ED CECT.

N-Acetylcysteine Plus Intravenous Fluids Versus Intravenous Fluids Alone to Prevent Contrast-Induced Nephropathy in Emergency Computed Tomography

STUDY OBJECTIVE We test the hypothesis that N-acetylcysteine plus normal saline solution is more effective than normal saline solution alone in the prevention of contrast-induced nephropathy. METHODS The design was a randomized, double blind, 2-center, placebo-controlled interventional trial. Inclusion criteria were patients undergoing chest, abdominal, or pelvic computed tomography (CT) scan with intravenous contrast, older than 18 years, and at least one contrast-induced nephropathy risk factor. Exclusion criteria were end-stage renal disease, pregnancy, N-acetylcysteine allergy, or clinical instability. Intervention for the treatment group was N-acetylcysteine 3 g in 500 mL normal saline solution as an intravenous bolus and then 200 mg/hour (67 mL/hour) for up to 24 hours; and for the placebo group was 500 mL normal saline solution and then 67 mL/hour for up to 24 hours. The primary outcome was contrast-induced nephropathy, defined as an increase in creatinine level of 25% or 0.5 mg/dL, measured 48 to 72 hours after CT. RESULTS The data safety and monitoring board terminated the study early for futility. Of 399 patients enrolled, 357 (89%) completed follow-up and were included. The N-acetylcysteine plus saline solution group contrast-induced nephropathy rate was 14 of 185 (7.6%) versus 12 of 172 (7.0%) in the normal saline solution only group (absolute risk difference 0.6%; 95% confidence interval -4.8% to 6.0%). The contrast-induced nephropathy rate in patients receiving less than 1 L intravenous fluids in the emergency department (ED) was 19 of 147 (12.9%) versus 7 of 210 (3.3%) for greater than 1 L intravenous fluids (difference 9.6%; 95% confidence interval 3.7% to 15.5%), a 69% risk reduction (odds ratio 0.41; 95% confidence interval 0.21 to 0.80) per liter of intravenous fluids. CONCLUSION We did not find evidence of a benefit for N-acetylcysteine administration to our ED patients undergoing contrast-enhanced CT. However, we did find a significant association between volume of intravenous fluids administered and reduction in contrast-induced nephropathy.

EMERGENCY DEPARTMENT RAPID MEDICAL ASSESSMENT: OVERALL EFFECT AND MECHANISTIC CONSIDERATIONS

BACKGROUND Although the use of a physician and nurse team at triage has been shown to improve emergency department (ED) throughput, the mechanism(s) by which these improvements occur is less clear. OBJECTIVES 1) To describe the effect of a Rapid Medical Assessment (RMA) team on ED length of stay (LOS) and rate of left without being seen (LWBS); 2) To estimate the effect of RMA on different groups of patients. METHODS For Objective 1, we compared LOS and LWBS on dates when we utilized RMA to comparable dates when we did not. For Objective 2, we utilized patient logs to divide patients into groups and estimated the effects of the RMA on each. RESULTS Objective 1. LOS fell from 297.8 min pre-RMA to 261.7 min during RMA, an improvement of 36.1 (95% confidence interval 21.8-50.4) min; LWBS did not change significantly. Objective 2. Patients seen and dispositioned by the RMA had an estimated decrease in LOS of 117.8 min (estimated decrease in LOS of 45%), but patients seen by the RMA whose care was transitioned to the main ED had an estimated increase in LOS of 25.0 min (estimated increase in LOS of 8%). CONCLUSIONS On a system level, the addition of an RMA shift at a single facility was associated with an improvement in LOS, but not LWBS. On a mechanistic level, it seems that improvements occurred as a result of the rapid disposition component of the RMA rather than placing advanced orders at triage.

Emergency Department Physician Telemedical Triage

BACKGROUND Telemedical physician triage (TPT) is a potential application of telemedicine in the emergency department (ED). We report the technical success, patient satisfaction, and effect on ED throughput metrics (length of stay [LOS] and time to physician evaluation [TPE]) of TPT performed on a mobile platform. MATERIALS AND METHODS Patients underwent standard nursing triage with or without TPT. Technical success is reported as raw data. Patient satisfaction is reported as raw data±standard deviation on a 5-point (low-to-high) scale. LOS and TPE are reported as mean±SD [95% CI] values. Statistical analyses of LOS and TPE are via two-sample t test. RESULTS One hundred six patients were registered during intervention periods, and TPT was completed in 36 (34%). One hundred ninety-six patients were registered during control periods. The technical success rate was 95%. Average patient satisfaction was 4.7 on a 5-point scale. The primary analysis (106 patients) showed no change in LOS (266±101 [244-288] min versus 258±172 [234-282] min) but a trend toward improved TPE with TPT (35±28 [29-41] min versus 42±31 [38-46] min) (p=0.052). A secondary analysis (36 patients) showed no change in LOS (273±125 [231-316] min versus 258±172 [234-282] min) but improved TPE with TPT (16±15 [11-21] min versus 42±31 [38-46] min) (p<0.0001). CONCLUSIONS TPT in the ED on a mobile platform was technically successful, well accepted by patients, and associated with a decrease in TPE but not LOS.

Emergency Department Rotational Patient Assignment

STUDY OBJECTIVE We compare emergency department (ED) operational metrics obtained in the first year of a rotational patient assignment system (in which patients are assigned to physicians automatically according to an algorithm) with those obtained in the last year of a traditional physician self-assignment system (in which physicians assigned themselves to patients at physician discretion). METHODS This was a pre-post retrospective study of patients at a single ED with no financial incentives for physician productivity. Metrics of interest were length of stay; arrival-to-provider time; rates of left before being seen, left subsequent to being seen, early returns (within 72 hours), and early returns with admission; and complaint ratio. RESULTS We analyzed 23,514 visits in the last year of physician self-assignment and 24,112 visits in the first year of rotational patient assignment. Rotational patient assignment was associated with the following improvements (percentage change): median length of stay 232 to 207 minutes (11%), median arrival to provider time 39 to 22 minutes (44%), left before being seen 0.73% to 0.36% (51%), and complaint ratio 9.0/1,000 to 5.4/1,000 (40%). There were no changes in left subsequent to being seen, early returns, or early returns with admission. CONCLUSION In a single facility, the transition from physician self-assignment to rotational patient assignment was associated with improvement in a broad array of ED operational metrics. Rotational patient assignment may be a useful strategy in ED front-end process redesign.

Initial Diagnosis and Management of Coma

Coma represents a true medical emergency. Drug intoxications are a leading cause of coma; however, other metabolic disturbances and traumatic brain injury are also common causes. The general emergency department approach begins with stabilization of airway, breathing, and circulation, followed by a thorough physical examination to generate a limited differential diagnosis that is then refined by focused testing. Definitive treatment is ultimately disease-specific. This article presents an overview of the pathophysiology, causes, examination, and treatment of coma.

A method for the analysis and visualization of clinical workflow in dynamic environments

The analysis of clinical workflow offers many challenges, especially in settings characterized by rapid dynamic change. Typically, some combination of approaches drawn from ethnography and grounded theory-based qualitative methods are used to develop relevant metrics. Medical institutions have recently attempted to introduce technological interventions to develop quantifiable quality metrics to supplement existing purely qualitative analyses. These interventions range from automated location tracking to repositories of clinical data (e.g., electronics health record (EHR) data, medical equipment logs). Our goal in this paper is to present a cohesive framework that combines a set of analytic techniques that can potentially complement traditional human observations to derive a deeper understanding of clinical workflow and thereby to enhance the quality, safety, and efficiency of care offered in that environment. We present a series of theoretically-guided techniques to perform analysis and visualization of data developed using location tracking, with illustrations using the Emergency Department (ED) as an example. Our framework is divided into three modules: (i) transformation, (ii) analysis, and (iii) visualization. We describe the methods used in each of these modules, and provide a series of visualizations developed using location-tracking data collected at the Mayo Clinic ED (Phoenix, AZ). Our innovative analytics go beyond qualitative study, and includes user data collected from a relatively modern but increasingly ubiquitous technique of location tracking, with the goal of creating quantitative workflow metrics. Although we believe that the methods we have developed will generalize well to other settings, additional work will be required to demonstrate their broad utility beyond our single study environment.

Modelling attending physician productivity in the emergency department: a multicentre study

Objectives Emergency physician productivity, often defined as new patients evaluated per hour, is essential to planning clinical operations. Prior research in this area considered this a static quantity; however, our group’s study of resident physicians demonstrated significant decreases in hourly productivity throughout shifts. We now examine attending physicians’ productivity to determine if it is also dynamic. Methods This is a retrospective cohort study, conducted from 2014 to 2016 across three community hospitals in the north-eastern USA, with different schedules and coverage. Timestamps of all patient encounters were automatically logged by the sites’ electronic health record. Generalised estimating equations were constructed to predict productivity in terms of new patients per shift hour. Results 207 169 patients were seen by 64 physicians over 2 years, comprising 9822 physician shifts. Physicians saw an average of 15.0 (SD 4.7), 20.9 (SD 6.4) and 13.2 (SD 3.8) patients per shift at the three sites, with 2.97 (SD 0.22), 2.95 (SD 0.24) and 2.17 (SD 0.09) in the first hour. Across all sites, physicians saw significantly fewer new patients after the first hour, with more gradual decreases subsequently. Additional patient arrivals were associated with greater productivity; however, this attenuates substantially late in the shift. The presence of other physicians was also associated with slightly decreased productivity. Conclusions Physician productivity over a single shift follows a predictable pattern that decreases significantly on an hourly basis, even if there are new patients to be seen. Estimating productivity as a simple average substantially underestimates physicians’ capacity early in a shift and overestimates it later. This pattern of productivity should be factored into hospitals’ staffing plans, with shifts aligned to start with the greatest volumes of patient arrivals.

Are testers also admitters? Comparing emergency physician resource utilization and admitting practices

Objective To describe the relationship between emergency department resource utilization and admission rate at the level of the individual physician. Methods Retrospective observational study of physician resource utilization and admitting data at two emergency departments. We calculated observed to expected (O/E) ratios for four measures of resource utilization (intravenous medications and fluids, laboratory testing, plain radiographs, and advanced imaging studies) as well as for admission rate. Expected values reflect adjustment for patient‐ and time‐based variables. We compared O/E ratios for each type of resource utilization to the O/E ratio for admission for each provider. We report degree of correlation (slope of the trendline) and strength of correlation (adjusted R2 value) for each association, as well as categorical results after clustering physicians based on the relationship of resource utilization to admission rate. Results There were statistically significant positive correlations between resource utilization and physician admission rate. Physicians with lower resource utilization rates were more likely to have lower admission rates, and those with higher resource utilization rates were more likely to have higher admission rates. Conclusions In a two‐facility study, emergency physician resource utilization and admission rate were positively correlated: those who used more ED resources also tended to admit more patients. These results add to a growing understanding of emergency physician variability.