Each of the data sources described in this article has unique advantages and disadvantages when used to examine patterns of ED care, making the different data sources appropriate for different applications. Analysts should select a data source according to its construction and should bear in mind its strengths and weaknesses in drawing conclusions based on the estimates it yields.

Many patients who seek emergency department (ED) treatment are not well enough for immediate discharge but are not clearly sick enough to warrant full inpatient admission. These patients are increasingly treated as outpatients using observation services. Hospitals employ four basic approaches to observation services, which can be categorized by the presence or absence of a dedicated observation unit and of defined protocols. To understand which approach might have the greatest impact, we compared 2010 data from three sources: a case study of observation units in Atlanta, Georgia; statewide discharge data for Georgia; and national survey and discharge data. Compared to patients receiving observation services elsewhere in the hospital, patients cared for in "type 1" observation units-dedicated units with defined protocolshave a 23-38 percent shorter length-of-stay, a 17-44 percent lower probability of subsequent inpatient admission, and $950 million in potential national cost savings each year. Furthermore, we estimate that 11.7 percent of short-stay inpatients nationwide could be treated in a type 1 unit, with possible savings of $5.5-$8.5 billion annually. Policy makers should have hospitals report the setting in which observation services are provided and consider payment incentives for care in a type 1 unit.

The introduction of the RV5 vaccine was associated with a dramatic reduction in hospitalizations for acute gastroenteritis among US children during the 2008 rotavirus season.

Among patients in 8 states undergoing ambulatory surgery, rates of postsurgical visits for CS-SSIs were low relative to all causes; however, they may represent a substantial number of adverse outcomes in aggregate. Thus, these serious infections merit quality improvement efforts to minimize their occurrence.

The sharp increase in opioid-related stays overall during the transition to ICD-10-CM may indicate that the new classification system is capturing stays that were missed by ICD-9-CM data. Estimates of stays involving other diagnoses may also be affected, and analysts should assess potential discontinuities in trends across the ICD transition.

Background: An estimated 1.2 million people in the US have an acute myocardial infarction (AMI) each year. An estimated 7% of AMI hospitalizations result in death. Most patients experiencing acute coronary symptoms, such as unstable angina, visit an emergency department (ED). Some patients hospitalized with AMI after a treatand-release ED visit likely represent missed opportunities for correct diagnosis and treatment. The purpose of the present study is to estimate the frequency of missed AMI or its precursors in the ED by examining use of EDs prior to hospitalization for AMI. Methods: We estimated the rate of probable missed diagnoses in EDs in the week before hospitalization for AMI and examined associated factors. We used Healthcare Cost and Utilization Project State Inpatient Databases and State Emergency Department Databases for 2007 to evaluate missed diagnoses in 111,973 admitted patients aged 18 years and older. Results: We identified missed diagnoses in the ED for 993 of 112,000 patients (0.9% of all AMI admissions). These patients had visited an ED with chest pain or cardiac conditions, were released, and were subsequently admitted for AMI within 7 days. Higher odds of having missed diagnoses were associated with being younger and of Black

Objectives: The objective was to describe transfers out of hospital-based emergency departments (EDs) in the United States and to identify different characteristics of sending and receiving hospitals, travel distance during transfer, disposition on arrival to the second hospital, and median number of transfer partners among sending hospitals.Methods: Emergency department records were linked at transferring hospitals to ED and inpatient records at receiving hospitals in nine U.S. states using the 2010 Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases and State Inpatient Databases, the American Hospital Association Annual Survey, and the Trauma Information Exchange Program. Using the Clinical Classification Software (CCS) to categorize conditions, the 50 disease categories with the highest transfer rates were studied, and these were then placed into nine clinical groups. Records were included where both sending and receiving records were available; these data were tabulated to describe ED transfer patterns, hospital-to-hospital distances, final patient disposition, and number of transfer partners.Results: A total of 97,021 ED transfer encounters were included in the analysis from the 50 highest transfer rate disease categories. Among these, transfer rates ranged from 1% to 13%. Circulatory conditions made up about half of all transfers. Receiving hospitals were more likely to be nonprofit, teaching, trauma, and urban and have more beds with greater specialty coverage and more advanced diagnostic and therapeutic resources. The median transfer distance was 23 miles, with 25% traveling more than 40 to 50 miles. About 8% of transferred encounters were discharged from the second ED, but that varied from 0.6% to 53% across the 50 conditions. Sending hospitals had a median of seven transfer partners across all conditions and between one and four per clinical group.Conclusions: Among high-transfer conditions in U.S. EDs, patients are often transferred great distances, more commonly to large teaching hospitals with greater resources. The large number of transfer partners indicates a possible lack of stable transfer relationships between U.S. hospitals.ACADEMIC EMERGENCY MEDICINE 2015;22:157-165

Prognostic Level III. See instructions for Authors for a complete description of levels of evidence.