Association of emergency department and hospital characteristics with elopements and length of stay.
BACKGROUND
As the Centers for Medicare & Medicaid Services (CMS) core measures in 2013 compare Emergency Department (ED) treatment time intervals, it is important to identify ED and hospital characteristics associated with these metrics to facilitate accurate comparisons.


OBJECTIVE
The objective of this study is to assess differences in operational metrics by ED and hospital characteristics. ED-level characteristics included annual ED volume, percentage of patients admitted, percentage of patients presenting by ambulance, and percentage of pediatric patients. Hospital-level characteristics included teaching hospital status, trauma center status, hospital ownership (nonprofit or for-profit), inpatient bed capacity, critical access status, inpatient bed occupancy, and rural vs. urban location area.


METHODS
Data from the ED Benchmarking Alliance from 2004 to 2009 were merged with the American Hospital Association's Annual Survey Database to include hospital characteristics that may impact ED throughput. Overall median length of stay (LOS) and left before treatment is complete (LBTC) were the primary outcome variables, and a linear mixed model was used to assess the association between outcome variables and ED and hospital characteristics, while accounting for correlations among multiple observations within each hospital. All data were at the hospital level on a yearly basis.


RESULTS
There were 445 EDs included in the analysis, from 2004 to 2009, with 850 observations over 6 years. Higher-volume EDs were associated with higher rates of LBTC and LOS. For-profit hospitals had lower LBTC and LOS. Higher inpatient bed occupancies were associated with a higher LOS. Increasing admission percentages were positively associated with overall LOS for EDs, but not with rates of LBTC.


CONCLUSIONS
Higher-volume EDs are associated with higher LBTC and LOS, and for-profit hospitals appear more favorably in these metrics compared with their nonprofit counterparts. It is important to appreciate that hospitals have different baselines for performance that may be more tied to volume and capacity, and less to quality of care.
Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health and Science University, Portland, Oregon.
Daniel A
DA
Handel
Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health and Science University, Portland, Oregon; Department of Public Health and Preventive Medicine, Oregon Health and Science University, Portland, Oregon.
Rongwei
R
Fu
Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health and Science University, Portland, Oregon.
Eugene
E
Vu
Emergency Medicine Physicians, Canton, Ohio.
James J
JJ
Augustine
Department of Emergency Medicine, University of California, San Francisco, California.
Renee Y
RY
Hsia
Department of Emergency Medicine, Indiana University, Indianapolis, Indiana.
Charles M
CM
Shufflebarger
Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health and Science University, Portland, Oregon.
Benjamin
B
Sun
D000552:Ambulances / Q000706:statistics & numerical data; D001509:Bed Occupancy; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D006742:Hospital Bed Capacity; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D010067:Ownership; D010343:Patient Admission / Q000706:statistics & numerical data; D013997:Time Factors; D061665:Time-to-Treatment / Q000706:statistics & numerical data*; D014193:Trauma Centers / Q000706:statistics & numerical data; D016312:Treatment Refusal / Q000706:statistics & numerical data*
crowding; emergency department; health services; performance metrics; throughput