TY - GEN
T1 - Identifying emergency department efficiency frontiers and the factors associated with their efficiency performance
AU - Kang, Hyojung
AU - Nembhard, Harriet Black
AU - DeFlitch, Chris
PY - 2014
Y1 - 2014
N2 - Emergency department (ED) overcrowding has been recognized as a serious concern in hospitals nationwide. In response, many hospitals have implemented various improvement initiatives, but not all hospitals have found great success. This study aimed to develop a data-driven framework for benchmarking efficient EDs and adopting their best practices. First, a data envelopment analysis (DEA) was used to identify ED frontiers that have achieved operational efficiencies. Using the Emergency Department Benchmarking Alliance database for 2012, we divided 449 EDs into six groups and evaluated the efficiency of each ED in the groups. Inputs include number of ED beds, clinical staffing working hours, and non-clinical staffing working hours in the ED. Outputs include the number of patient visits per day, average length of stay, and the rate of leaving without being treated. Using the efficiency rankings, logistic regression was performed to identify which features of EDs contributed to their becoming efficient frontiers or inefficient units. The results indicated that the proportion of admitted patients through the ED, the intake model with a mid-level provider, a fast-track area, and a patient volume had a significant impact on efficiency of the EDs. The identification of successful EDs and their profiles may provide comparable ED benchmarking and the proliferation of best practices.
AB - Emergency department (ED) overcrowding has been recognized as a serious concern in hospitals nationwide. In response, many hospitals have implemented various improvement initiatives, but not all hospitals have found great success. This study aimed to develop a data-driven framework for benchmarking efficient EDs and adopting their best practices. First, a data envelopment analysis (DEA) was used to identify ED frontiers that have achieved operational efficiencies. Using the Emergency Department Benchmarking Alliance database for 2012, we divided 449 EDs into six groups and evaluated the efficiency of each ED in the groups. Inputs include number of ED beds, clinical staffing working hours, and non-clinical staffing working hours in the ED. Outputs include the number of patient visits per day, average length of stay, and the rate of leaving without being treated. Using the efficiency rankings, logistic regression was performed to identify which features of EDs contributed to their becoming efficient frontiers or inefficient units. The results indicated that the proportion of admitted patients through the ED, the intake model with a mid-level provider, a fast-track area, and a patient volume had a significant impact on efficiency of the EDs. The identification of successful EDs and their profiles may provide comparable ED benchmarking and the proliferation of best practices.
KW - Data envelopment analysis (DEA)
KW - Emergency department (ED)
KW - Logistic regression
KW - Operational efficiency
KW - Performance measures
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UR - http://www.scopus.com/inward/citedby.url?scp=84910051100&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84910051100
T3 - IIE Annual Conference and Expo 2014
SP - 3974
EP - 3983
BT - IIE Annual Conference and Expo 2014
PB - Institute of Industrial Engineers
T2 - IIE Annual Conference and Expo 2014
Y2 - 31 May 2014 through 3 June 2014
ER -