TY - JOUR
T1 - Anesthesia Residents Preferentially Request Operating Room Case Assignments with Complex Cases
AU - Kim, Peggy Y.
AU - Wanderer, Jonathan P.
AU - Allbritton, David W.
AU - Eikermann, Matthias
AU - Baker, Keith
N1 - Funding Information:
This work was supported by the Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA. Dr. Wanderer is funded by the Foundation for Anesthesia Education and Research (FAER) and the Anesthesia Quality Institute (AQI)'s Mentored Research Training Grant-Health Services Research (MTRG-HSR).
Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2017/4/1
Y1 - 2017/4/1
N2 - Self-directed learning is associated with knowledge and performance improvements, increased identification and amelioration of knowledge gaps, and heightened critical appraisal of available evidence. We developed and implemented a decision support system that could support self-directed learning for anesthesia residents by soliciting resident input in case selection. We hypothesized that residents would utilize this system to request complex cases, and that more advanced residents would request more complex cases. Prospective, observational study involving 101 anesthesiology residents. We used a web-based interface, RHINOS [Residents Helping in Navigating Operating Room (OR) Scheduling], which allowed residents to share their rank-ordered preferences for OR assignment. Number of cases per OR, anesthesia base units, time units, and proportion of inpatient cases were used as proxies for case complexity. Data were analyzed using a mixed linear model. Residents requested rooms with fewer cases [F(3,22,350) = 194.0; p < 0.001], more base units [F(3,19,158) = 291.4; p < 0.001], more time units [F(3,19,744) = 186.4; p < 0.001], and a greater proportion of cases requiring inpatient preoperative evaluation [F(3,51,929) = 11.3; p < 0.001]. In most cases, these differences were greater for more advanced residents. As hypothesized, residents requested ORs with higher case complexity, and these cases more often required inpatient preoperative evaluation. More advanced residents exhibited a stronger preference for more educational cases than junior residents.
AB - Self-directed learning is associated with knowledge and performance improvements, increased identification and amelioration of knowledge gaps, and heightened critical appraisal of available evidence. We developed and implemented a decision support system that could support self-directed learning for anesthesia residents by soliciting resident input in case selection. We hypothesized that residents would utilize this system to request complex cases, and that more advanced residents would request more complex cases. Prospective, observational study involving 101 anesthesiology residents. We used a web-based interface, RHINOS [Residents Helping in Navigating Operating Room (OR) Scheduling], which allowed residents to share their rank-ordered preferences for OR assignment. Number of cases per OR, anesthesia base units, time units, and proportion of inpatient cases were used as proxies for case complexity. Data were analyzed using a mixed linear model. Residents requested rooms with fewer cases [F(3,22,350) = 194.0; p < 0.001], more base units [F(3,19,158) = 291.4; p < 0.001], more time units [F(3,19,744) = 186.4; p < 0.001], and a greater proportion of cases requiring inpatient preoperative evaluation [F(3,51,929) = 11.3; p < 0.001]. In most cases, these differences were greater for more advanced residents. As hypothesized, residents requested ORs with higher case complexity, and these cases more often required inpatient preoperative evaluation. More advanced residents exhibited a stronger preference for more educational cases than junior residents.
KW - Case selection
KW - Education
KW - Self-directed learning
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U2 - 10.1007/s10916-017-0718-3
DO - 10.1007/s10916-017-0718-3
M3 - Article
C2 - 28283998
AN - SCOPUS:85014929276
SN - 0148-5598
VL - 41
JO - Journal of Medical Systems
JF - Journal of Medical Systems
IS - 4
M1 - 64
ER -