Surgeon and type of anesthesia predict variability in surgical procedure times.
BACKGROUND
Variability in surgical procedure times increases the cost of healthcare delivery by increasing both the underutilization and overutilization of expensive surgical resources. To reduce variability in surgical procedure times, we must identify and study its sources.


METHODS
Our data set consisted of all surgeries performed over a 7-yr period at a large teaching hospital, resulting in 46,322 surgical cases. To study factors associated with variability in surgical procedure times, data mining techniques were used to segment and focus the data so that the analyses would be both technically and intellectually feasible. The data were subdivided into 40 representative segments of manageable size and variability based on headers adopted from the common procedural terminology classification. Each data segment was then analyzed using a main-effects linear model to identify and quantify specific sources of variability in surgical procedure times.


RESULTS
The single most important source of variability in surgical procedure times was surgeon effect. Type of anesthesia, age, gender, and American Society of Anesthesiologists risk class were additional sources of variability. Intrinsic case-specific variability, unexplained by any of the preceding factors, was found to be highest for shorter surgeries relative to longer procedures. Variability in procedure times among surgeons was a multiplicative function (proportionate to time) of surgical time and total procedure time, such that as procedure times increased, variability in surgeons' surgical time increased proportionately.


CONCLUSIONS
Surgeon-specific variability should be considered when building scheduling heuristics for longer surgeries. Results concerning variability in surgical procedure times due to factors such as type of anesthesia, age, gender, and American Society of Anesthesiologists risk class may be extrapolated to scheduling in other institutions, although specifics on individual surgeons may not. This research identifies factors associated with variability in surgical procedure times, knowledge of which may ultimately be used to improve surgical scheduling and operating room utilization.
Strum
D P
DP
Department of Anesthesiology, Queen's University, Kingston, Ontario, Canada. strumd@post.queensu.ca
Sampson
A R
AR
May
J H
JH
Vargas
L G
LG
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000704:Analysis of Variance; D000776:Anesthesiology / Q000706:statistics & numerical data*; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D005260:Female; D013502:General Surgery / Q000458:organization & administration / Q000706:statistics & numerical data; D006784:Hospitals, Teaching / Q000458:organization & administration / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009873:Operating Rooms / Q000458:organization & administration* / Q000706:statistics & numerical data; D010561:Personnel Staffing and Scheduling; D012737:Sex Factors; D013514:Surgical Procedures, Operative / Q000191:economics / Q000706:statistics & numerical data*; D013997:Time Factors