TY - JOUR
T1 - Not All Testers are Admitters
T2 - An Analysis of Emergency Physician Resource Utilization and Consultation Rates
AU - Antkowiak, Peter S.
AU - Lee, Terrance
AU - Chiu, David T.
AU - Stenson, Bryan A.
AU - Traub, Stephen J.
AU - Sanchez, Leon D.
AU - Joseph, Joshua W.
N1 - Funding Information:
P.S.A. L.D.S. and J.W.J. conceived the study and designed the analysis. P.S.A. T.L. and D.T.C. led data collection. P.S.A. and J.W.J. conducted data analysis and modeling. D.T.C. J.W.J. and L.D.S. advised all aspects of the study. All authors contributed to manuscript writing and revising. P.S.A. takes responsibility for the manuscript as a whole.
Publisher Copyright:
© 2021
PY - 2022/4
Y1 - 2022/4
N2 - Abstract Background: Variability exists in emergency physician (EP) resource utilization as measured by ordering practices, rate of consultation, and propensity to admit patients. Objective: To validate and expand upon previous data showing that resource utilization as measured by EP ordering patterns is positively correlated with admission rates. Methods: This is a retrospective study of routinely gathered operational data from the ED of an urban academic tertiary care hospital. We collected individual EP data on advanced imaging, consultation, and admission rates per patient encounter. To investigate whether there might be distinct groups of practice patterns relating these 3 resources, we used a Gaussian mixture model, a classification method used to determine the likelihood of distinct subgroups within a larger population. Results: Our Gaussian mixture model revealed 3 distinct groups of EPs based on their ordering practices. The largest group is characterized by a homogenous pattern of neither high or low resource utilization (n = 37, 27% female, median years’ experience: 6 [interquartile ratio {IQR} 3–18]; rates of advanced imaging, 38.9%; consultation, 45.1%; and admission 39.3%), with a modest group of low-resource users (n = 15, 60% female, median years’ experience: 6 [IQR 5–14]; rates of advanced imaging, 37%; consultation, 42.6%; and admission 37.3%), and far fewer members of a high-resource use group (n = 6, 0% female, median years’ experience: 6 [IQR 4–16]; rates of advanced imaging, 42.2%; consultation, 45.8%; and admission 40.6%). This variation suggests that not “all testers are admitters,” but that there exist wider practice variations among EPs. Conclusions: At our academic tertiary center, 3 distinct subgroups of EP ordering practices exist based on consultation rates, advanced imaging use, and propensity to admit a patient. These data validate previous work showing that resource utilization and admission rates are related, while demonstrating that more nuanced patterns of EP ordering practices exist. Further investigation is needed to understand the impact of EP characteristics and behavior on throughput and quality of care.
AB - Abstract Background: Variability exists in emergency physician (EP) resource utilization as measured by ordering practices, rate of consultation, and propensity to admit patients. Objective: To validate and expand upon previous data showing that resource utilization as measured by EP ordering patterns is positively correlated with admission rates. Methods: This is a retrospective study of routinely gathered operational data from the ED of an urban academic tertiary care hospital. We collected individual EP data on advanced imaging, consultation, and admission rates per patient encounter. To investigate whether there might be distinct groups of practice patterns relating these 3 resources, we used a Gaussian mixture model, a classification method used to determine the likelihood of distinct subgroups within a larger population. Results: Our Gaussian mixture model revealed 3 distinct groups of EPs based on their ordering practices. The largest group is characterized by a homogenous pattern of neither high or low resource utilization (n = 37, 27% female, median years’ experience: 6 [interquartile ratio {IQR} 3–18]; rates of advanced imaging, 38.9%; consultation, 45.1%; and admission 39.3%), with a modest group of low-resource users (n = 15, 60% female, median years’ experience: 6 [IQR 5–14]; rates of advanced imaging, 37%; consultation, 42.6%; and admission 37.3%), and far fewer members of a high-resource use group (n = 6, 0% female, median years’ experience: 6 [IQR 4–16]; rates of advanced imaging, 42.2%; consultation, 45.8%; and admission 40.6%). This variation suggests that not “all testers are admitters,” but that there exist wider practice variations among EPs. Conclusions: At our academic tertiary center, 3 distinct subgroups of EP ordering practices exist based on consultation rates, advanced imaging use, and propensity to admit a patient. These data validate previous work showing that resource utilization and admission rates are related, while demonstrating that more nuanced patterns of EP ordering practices exist. Further investigation is needed to understand the impact of EP characteristics and behavior on throughput and quality of care.
KW - consultation rates
KW - physician behavior
KW - resource utilization
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U2 - 10.1016/j.jemermed.2021.11.003
DO - 10.1016/j.jemermed.2021.11.003
M3 - Article
C2 - 35101310
AN - SCOPUS:85123681961
SN - 0736-4679
VL - 62
SP - 468
EP - 474
JO - Journal of Emergency Medicine
JF - Journal of Emergency Medicine
IS - 4
ER -