Point of care (POC) laboratory testing is used to improve emergency department (ED) throughput but often overuses resources by duplicating formal laboratory testing. This study sought to evaluate the effect of a multimodal intervention on duplicate chemistry testing. This pre-post analysis included all visits to 2 urban EDs between June 2014 and June 2016. The multimodal intervention including provider education, signage, electronic health record redesign, and audit and feedback focused on reducing duplicate chemistry testing. The primary outcome was the number of duplicate chemistry tests per 100 visits. Autoregressive integrated moving-average models were used to account for secular changes. A total of 299 701 ED visits were included. The daily number of duplicate chemistry and POC chemistry tests significantly decreased following the intervention (3.3 fewer duplicates and 10.2 fewer POC per 100 ED visits, P < .0001). This implementation of a multimodal quality improvement intervention yielded substantial reductions in the overuse of blood chemistry testing in the ED.

Resident cost awareness and ability to accurately estimate laboratory order costs improved significantly after implementation of a comprehensive EHR cost display for all laboratory orders. The improvement in cost estimation accuracy for imaging orders, which did not have costs displayed, suggested a possible spillover effect generated by providing a cost context for residents.

IntroductionPoint-of-care (POC) testing allows for more time-sensitive diagnosis and treatment in the emergency department (ED) than sending blood samples to the hospital central laboratory (CL). However, many ED patients have blood sent to both, either out of clinical custom, or because clinicians do not trust the POC values. The objective of this study was to examine the level of agreement between POC and CL values in a large cohort of ED patients.MethodsIn an urban, Level I ED that sees approximately 120,000 patients/year, all patients seen between March 1, 2013, and October 1, 2014, who had blood sent to POC and CL labs had levels of agreement measured between serum sodium, potassium, blood urea nitrogen (BUN), creatinine, and hematocrit. We extracted data from the hospital’s clinical information system, and analyzed agreement with the use of Bland-Altman plots, defining both 95% confidence intervals (CIs) and more conservative CIs based on clinical judgment.ResultsOut of 163,661 patients seen during the study period, 14,567 had blood samples sent both for POC and CL analysis. Using clinical criteria, the levels of agreement for sodium were 98.6% (within 5mg/dL), for potassium 90.7% (0.5 mmol/L), for BUN 89.0% (within 5 mg/dL), for creatinine 94.5% (within 0.3 mg/dL), for hematocrit 96.5% (within 5 g/dL).ConclusionAgreement between POC and CL values is excellent. Restricting the analysis to clinically important levels of agreement continues to show a high level of agreement. The data suggest that sending a serum sample to the hospital CL for duplicate assays is unnecessary. This may result in substantial savings and shorter ED lengths of stay.

Background Cost awareness, to ensure physician stewardship of limited resources, is increasingly recognized as an important skill for physicians. The Accreditation Council for Graduate Medical Education has made cost awareness part of systems-based practice, a core competency of resident education. However, little is known about resident cost awareness. Objective We sought to assess senior resident self-perceived cost awareness and cost knowledge. Methods In March 2014, we conducted a cross-sectional survey of all emergency medicine, internal medicine, obstetrics and gynecology, orthopaedic surgery pediatrics, and medicine-pediatrics residents in their final year at Yale-New Haven Hospital. The survey examined attitudes toward health care costs and residents' estimates of order prices. We considered resident price estimates to be accurate if they were between 50% and 200% of the Connecticut-specific Medicare price. Results We sent the survey to 84 residents and received 47 completed surveys (56% response rate). Although more than 95% (45 of 47) felt that containing costs is the responsibility of every clinician, and 49% (23 of 47) agreed that cost influenced their decision when ordering, only 4% (2 of 47) agreed that they knew the cost of tests being ordered. No residents accurately estimated the price of a complete blood count with differential, and only 2.1% (1 of 47) were accurate for a basic metabolic panel. The overall accuracy of all resident responses was 25%. Conclusions In our study, many trainees exit residency with self-identified deficiencies in knowledge about costs. The findings show the need for educational approaches to improve cost awareness among trainees.

Objective: During pandemics, emergency departments (EDs) are challenged by the need to replace quarantined ED staff and avoid staffing EDs with nonemergency medicine (EM) trained physicians. We sought to design and examine three feasible ED staffing models intended to safely schedule EM physicians to staff three EDs within a health system during a prolonged infectious disease outbreak.Methods: We conducted simulation analyses examining the strengths and limitations of three ED clinician staffing models: two-team and three-team fixed cohort, and three-team unfixed cohort. Each model was assessed with and without immunity, and by varying infection rates. We assumed a 12-week pandemic disaster requiring a 2-week quarantine.Main outcome: The outcome, time to staffing shortage, was defined as depletion of available physicians in both 8- and 12-hour shift duration scenarios. Results: All staffing models initially showed linear physician attrition with higher infection rates resulting in faster staffing shortages. The three-team fixed cohort model without immunity was not viable beyond 11 weeks. The three-team unfixed cohort model without immunity avoided staffing shortage for the duration of the pandemic up to an infection rate of 50 percent. The two-team model without immunity also avoided staffing shortage up to 30 percent infection rate. When accounting for immunity, all models behaved similarly initially but returned to adequate staffing during week 5 of the pandemic. Conclusions: Simulation analyses reveal fundamental tradeoffs that are critical to designing feasible pandemic disaster staffing models. Emergency physicians should test similar models based on local assumptions and capacity to ensure adequate staffing preparedness for prolonged pandemics.