CASEMIX study: Assessment of patient factors influencing the subprocedure duration of trauma/orthopaedic surgeries

The social and financial burdens of the operative environment remains to be a major problem in modern society. We analyse the impact of the introduction and application of a perioperative cloud system that cross-analyzes the pre-/intraoperative risks to minimize surgical time and maximize operation theater efficiency through improved planning.

TCC-CASEMIX© was introduced to our Department of Trauma Surgery of the University of Szeged to objectively measure intraoperative time durations according to each essential subprocedure. The study is largely divided into pre-operative assessments and intraoperative measurements. Patient data (age, sex, and ethnicity etc.) was registered preoperatively, and the expected time per each essential intraoperative step (skin incision, reduction, fixation etc.) was entered. The steps were then timed intraoperatively by surveyors, and postoperative cross analysis was performed. Our study was divided into two phases; phase 1, the surveying of general trauma / orthopedic cases, and phase two; the examination of high volume surgeries.

Acute cases of Open Reductions and Internal Fixation (ORIF) procedures depended heavily on the presentation of the fracture, and no clear correlations in the risk factors were found. Arthroscopies were a short, high-volume procedure, but there was a large difference between the surgeon's estimates and the operation duration. In high volume surgeries, although individual factors only slightly influenced surgical duration, patient cohort stratification led to a better understanding of factors that impact surgeries, namely the combination of BMI and surgeon years of experience. While the average (Intraoperative Duration) seemed to increase with BMI, younger surgeons were more influenced by the patients BMI.

A data filtering algorithm-assisted cloud system can be a reliable way to facilitate the planning of operating theater schedules. Patient stratification according to BMI and surgeon years of experience seems to affect intraoperative duration significantly, and the understanding of the risks and intraoperative steps has the potential to forecast surgeries with high precision.