Presented at the American College of Emergency Physicians Scientific Assembly, San Francisco, CA, October 2011.
Original Research Contribution
Effect of Testing and Treatment on Emergency Department Length of Stay Using a National Database
Article first published online: 17 MAY 2012
© 2012 by the Society for Academic Emergency Medicine
Academic Emergency Medicine
Volume 19, Issue 5, pages 525–534, May 2012
How to Cite
Kocher, K. E., Meurer, W. J., Desmond, J. S. and Nallamothu, B. K. (2012), Effect of Testing and Treatment on Emergency Department Length of Stay Using a National Database. Academic Emergency Medicine, 19: 525–534. doi: 10.1111/j.1553-2712.2012.01353.x
The authors have no relevant financial information or potential conflicts of interest to disclose.
Supervising Editor: Roland C. Merchant, MD, MPH, ScD.
- Issue published online: 17 MAY 2012
- Article first published online: 17 MAY 2012
- Received July 22, 2011; revisions received October 3 and November 8, 2011; accepted November 12, 2011.
ACADEMIC EMERGENCY MEDICINE 2012; 19: 525–534 © 2012 by the Society for Academic Emergency Medicine
Objectives: Testing and treatment are essential aspects of the delivery of emergency care. Recognition of the effects of these activities on emergency department (ED) length of stay (LOS) has implications for administrators planning efficient operations, providers, and patients regarding expectations for length of visit; researchers in creating better models to predict LOS; and policy-makers concerned about ED crowding.
Methods: A secondary analysis was performed using years 2006 through 2008 of the National Hospital Ambulatory Medical Care Survey (NHAMCS), a nationwide study of ED services. In univariate and bivariate analyses, the authors assessed ED LOS and frequency of testing (blood test, urinalysis, electrocardiogram [ECG], radiograph, ultrasound, computed tomography [CT], or magnetic resonance imaging [MRI]) and treatment (providing a medication or performance of a procedure) according to disposition (discharged or admitted status). Two sets of multivariable models were developed to assess the contribution of testing and treatment to LOS, also stratified by disposition. The first was a series of logistic regression models to provide an overview of how testing and treatment activity affects three dichotomized LOS cutoffs at 2, 4, and 6 hours. The second was a generalized linear model (GLM) with a log-link function and gamma distribution to fit skewed LOS data, which provided time costs associated with tests and treatment.
Results: Among 360 million weighted ED visits included in this analysis, 227 million (63%) involved testing, 304 million (85%) involved treatment, and 201 million (56%) involved both. Overall, visits with any testing were associated with longer LOS (median = 196 minutes; interquartile range [IQR] = 125 to 305 minutes) than those with any treatment (median = 159 minutes; IQR = 91 to 262 minutes). This difference was more pronounced among discharged patients than admitted patients. Obtaining a test was associated with an adjusted odds ratio (OR) of 2.29 (95% confidence interval [CI] = 1.86 to 2.83) for experiencing a more than 4-hour LOS, while performing a treatment had no effect (adjusted OR = 0.84; 95% CI = 0.68 to 1.03). The most time-costly testing modalities included blood test (adjusted marginal effects on LOS = +72 minutes; 95% CI = 66 to 78 minutes), MRI (+64 minutes; 95% CI = 36 to 93 minutes), CT (+59 minutes; 95% CI = 54 to 65 minutes), and ultrasound (US; +56 minutes; 95% CI = 45 to 67 minutes). Treatment time costs were less substantial: performing a procedure (+24 minutes; 95% CI = 20 to 28 minutes) and providing a medication (+15 minutes; 95% CI = 8 to 21 minutes).
Conclusions: Testing and less substantially treatment were associated with prolonged LOS in the ED, particularly for blood testing and advanced imaging. This knowledge may better direct efforts at streamlining delivery of care for the most time-costly diagnostic modalities or suggest areas for future research into improving processes of care. Developing systems to improve efficient utilization of these services in the ED may improve patient and provider satisfaction. Such practice improvements could then be examined to determine their effects on ED crowding.