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The Role Of Apella In Optimizing Operating Room Turnover Times
Sanjay V. Wunnava, MD, MS, Jay P. Natarajan, MD, Jean Bismuth, MD.
University of South Florida, Tampa, FL, USA.
BACKGROUNDSurgical turnover time (TOT) remains at the crux of efficiency and resource utilization for every hospital. Multiple themes have been identified as having a role in reducing TOT - these include parallel processing, team consistency/training, procedural standardization and finally, targeted workflow interventions. Missing in the literature is the optimal number of individuals involved in the turnover process and/or how this number may be affected by procedure type. We hope to better elucidate both using ApellaŽ - a healthcare technology company that uses computer vision and artificial intelligence to document the clinical and procedural workflows of the Operating Room (OR).METHODSA total of 802 turnovers in the Cardiovascular Transplant Operating Room were analyzed. Each was separated into a series of distinct phases across three different procedure types - minimally invasive, open, or hybrid. The number of people involved in each phase, the procedure type and the time to completion was recorded.RESULTSTOT ranged from 12 to 60 minutes (mean 43.75) with total staff ranging from 0.63 to 6.18 individuals. Linear regression analysis was performed to examine the relationship between TOT and staff allocation. This demonstrated statistically significant reductions in TOT of 3.947, 6.358 and 7.670 minutes per additional staff member in minimally invasive F(74,155) = 1.389, p<0.05, open F(171,143) = 1.966, p<0.01 and hybrid procedures F(93,164) = 2.311, p<0.01 respectively (Table 1). To examine whether the relationship between additional staff and TOT differed by case type, an ANCOVA was performed. The interaction was significant,
F(2,798) = 6.42,
p = .002, partial η˛ = .016, indicating that the slopes of turnover time on average occupancy varied by case type (Figure 1).
CONCLUSIONSStaff allocation is another aspect of hospital resource management that, when applied strategically, can significantly reduce turnover time (TOT), increase OR efficiency, and ultimately reduce hospital expenditure.
Table 1: Role of Average Occupancy on TOT | Minimally Invasive | Open | Hybrid |
| avg occupancy | -3.947*** | -6.358*** | -7.670*** |
| Std Error | (1.26) | (0.97) | (1.035) |
| | | |
| Observations | 230 | 315 | 258 |
| R2 | 0.399 | 0.702 | 0.567 |
| Adjusted R2 | 0.112 | 0.345 | 0.322 |
| Residual Std. Error | 8.668 (df=155) | 7.402 (df=143) | 6.695 (df=164) |
| F Statistic | 1.389** (df=74,155) | 1.966*** (df=171,143) | 2.311*** (df=93,164) |
| NOTE: **p<0.05; ***p<0.01 | | | |
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