Emergency department transfers and transfer relationships in United States hospitals.

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.

The transfer instability index: a novel metric of emergency department transfer relationships.

OBJECTIVES: In this study, the objective was to characterize emergency department (ED) transfer relationships and study the factors that predict the stability of those relationships. A metric is derived for ED transfer relationships that may be useful in assessing emergency care regionalization and as a resource for future emergency medicine research. METHODS: Emergency department records at transferring hospitals were linked to ED and inpatient records at receiving hospitals in nine U.S. states using the 2010 Healthcare Cost and Utilization Project 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 to categorize conditions, high transfer rate conditions were placed into nine clinical groups. The authors created a new measure, the "transfer instability index," which estimates the effective number of "transfer partners" for each sending ED: this is designed to measure the stability of outgoing transfer relationships, where higher values of the index indicate less stable relationships. The index provides a measure of how many hospitals a transferring hospital sends its patients to (weighted by how often each transfer partner is used). Regression was used to analyze factors associated with higher values of the index. RESULTS: Sending hospitals had a median of 3.5 effective transfer partners across all conditions. The calculated transfer instability indices varied from 1 to 2.4 across disease categories. In general, higher index values were associated with treating a higher proportion of publicly insured patients: 10 and 12% increases in the Medicare and Medicaid share of ED encounters, respectively, were associated with 10 and 14% increases in the effective number of transfer partners. This public insurance effect held while studying all conditions together as well as within individual disease categories, such as cardiac, neurologic, and traumatic conditions. CONCLUSIONS: United States EDs that transfer patients to other hospitals often have multiple transfer partners. The stability of the transfer relationship, assessed by the transfer instability index, differs by condition. Less stable transfer relationships (i.e., hospitals with greater numbers of transfer partners) were more common in EDs with higher proportions of publicly insured patients.

Emergency department variation in utilization and diagnostic yield of advanced radiography in diagnosis of pulmonary embolus.

BACKGROUND: There is growing pressure to measure and reduce unnecessary imaging in the emergency department. OBJECTIVE: We study provider and hospital variation in utilization and diagnostic yield for advanced radiography in diagnosis of pulmonary embolism (PE) and to assess patient- and provider-level factors associated with diagnostic yield. METHODS: Retrospective chart review of all adult patients presenting to four hospitals from January 2006 through December 2009 who had a computed tomography or ventilation/perfusion scan to evaluate for PE. Demographic data on the providers ordering the scans were collected. Diagnostic yield (positive scans/total scans ordered) was calculated at the hospital and provider level. The study was not designed to assess appropriateness of imaging. RESULTS: There was significant variation in utilization and diagnostic yield at the hospital level (chi-squared, p < 0.05). Diagnostic yield ranged from 4.2% to 8.2%; after adjusting for patient- and provider-level factors; the two hospitals with an emergency medicine residency training program had higher diagnostic yields (odds ratio [OR] 2.0, 95% confidence interval [CI] 1.6-2.5 and OR 1.9, 95% CI 1.5-2.4). There was no significant variation in diagnostic yield among the 90 providers after adjusting for patient, hospital, and provider characteristics. Providers with < 10 years of experience had lower odds of diagnosing a PE than more experienced graduates (OR 0.8, 95% CI 0.6-0.9). CONCLUSIONS: Although we found significant variation in utilization of advanced radiography for PE and diagnostic yield at the hospital level, there was no significant variation at the provider level after adjusting for patient-, hospital-, and provider-level factors.

Admit or transfer? The role of insurance in high-transfer-rate medical conditions in the emergency department.

STUDY OBJECTIVE: We study the association of payer status with odds of transfer compared with admission from the emergency department (ED) for multiple diagnoses with a high percentage of transfers. METHODS: This was a retrospective study of adult ED encounters using the Healthcare Cost and Utilization Project 2010 Nationwide Emergency Department Sample. We used the Clinical Classification Software to identify disease categories with 5% or more encounters resulting in transfer (27 categories; 3.7 million encounters based on survey weights). We sorted encounters by condition into 12 groups according to expected medical or surgical specialist needs. We used logistic regression to assess the role of payer status on odds of transfer compared with admission and report adjusted odds ratios (ORs). RESULTS: Among high-transfer conditions in 2010, uninsured patients had double the odds of transfer compared with privately insured patients (OR 2.12; 95% confidence interval [CI] 1.72 to 2.62). Medicaid patients were also more likely to be transferred (OR 1.2; 95% CI 1.04 to 1.38). Uninsured patients had higher odds of transfer in all specialist categories (significant in 9 of 12). The categories with the highest odds of transfer for the uninsured included nephrology (OR 2.44; 95% CI 1.07 to 5.55), psychiatry (OR 2.26; 95% CI 1.65 to 3.25), and hematology-oncology (OR 2.21; 95% CI 1.50 to 3.25); the highest for Medicaid were general surgery (OR 1.61; 95% CI 1.09 to 1.83), hematology-oncology (OR 1.55; 95% CI 1.05 to 2.30), and vascular surgery (OR 1.55; 95% CI 1.02 to 2.28). CONCLUSION: Insurance status appears to play a role in ED disposition (transfer versus admission) for many high-transfer conditions.