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.