Factors affecting total operating time for a standard surgical procedure Yu Chuan Chong

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1 Factors affecting total operating time for a standard surgical procedure Yu Chuan Chong Contributing authors: Colin Howie, David Ray, Deborah MacDonald, Hamish Simpson Introduction Surgeons and anaesthetists are being pressured to work faster to optimise the use of operating theatre capacity. The expected duration of both the Anaesthesia Preparation Time (APT: defined as the time the patient is attended by the anaesthetist in the Induction Room to the time the patient is moved into the Operating Room) and Surgical Time (ST: defined as the time from incision to wound closure) is important in planning the number of cases on a list. If the combined time of APT + ST is underestimated, patients will be cancelled at the end of the list and if it is overestimated the resources are underutilised. Although the surgical procedure itself consumes most of the operating time, an extended APT is also one of the factors responsible for a prolonged operating list and postponement of cases 1. The aim of this study was to determine the relationship between the common variables to all surgical procedures and the total operating, to see whether we could improve prediction of total time, and in turn optimise the use of operating time. Methods and materials The data was obtained from the computerised records of all surgical cases performed in the Orthopaedic Department at the Royal Infirmary of Edinburgh (RIE) over a 4-year period from November 2010 to December All these data were routinely recorded by the staff nurse in charge of the operating unit. Relevant variables extracted from the data were patient age, type of surgery, surgeon, anaesthetist, ASA grade, type of anaesthesia, APT and ST. In total, there were 30,119 records in the dataset. In order to reduce confounding factors, the analysis was restricted to patients undergoing primary elective total hip replacement (THR). Missing data were omitted from the analysis, leaving 2,391 eligible records. To ensure further consistency, the analysis focused on surgeons and anaesthetists who had done more than 50 cases over a 4-year period. Using the Statistical Package for the Social Sciences (SPSS) program, the correlation and significances between variables were analysed using Pearson s correlation analysis and One- way ANOVA analysis. Boxplots graphs were then used to study the distribution of the variables with significant differences. The mean total time (TT: defined as the sum of APT and ST, excluding time taken for moving and positioning the patient in the operating unit or time taken to transfer the patients to recovery area) was analysed and used to estimate the number of total hip replacements possible in a standard eight hour list. Results and discussion Table 1 depicts the Pearson s correlation analysis for patient age group and ASA grade against APT. The analysis showed that age did not affect the APT (P= 0.145). This was surprising as older age groups were considered to have poorer functional status and more comorbidities 2, which would affect the difficulty in administering anaesthesia consequently affecting the APT. The findings of Tessler et al 3 and Juvin et al 4 concurred with our results, stating that there was no significant association between age and difficulty in administering anaesthesia. Therefore, the postulate that elderly patients require more APT is not supported.

2 Variable n Anaesthesia Preparation Time (minutes) Mean SD Age group ASA Grade Table 1: Pearson s correlation analysis for patient age group and ASA grade against APT Significance R=0.030, P =0.145 R= 0.095, P =0.001 The analysis also revealed that there was a positive correlation between ASA grade and APT (P=0.001). It was expected that patients with poorer health would require longer APT as they are medically more complex and more likely to receive invasive monitoring 5. However, based on Figure 1 the median values for each ASA grade were similar, thus despite a statistically significant increase in the APT and increasing ASA grade, the increase in time is minimal. Figure 1: Boxplot of ASA grade against APT In Table 2, the one-way ANOVA analysis revealed there was a statistically significant difference between anaesthetic technique and APT (P=0.001) and also between the anaesthetist and APT (P=0.001). However, the time differences

3 were small (SD 1.6 and 3.9 minutes respectively) indicating minimal clinical significance. Our study showed that spinal anaesthesia was the quickest anaesthetic technique. Variable n Anaesthesia Preparation Time (minutes) Significance Anaesthetic technique GA GA+Blocks GA+SP SP SP+Epidural SP+Blocks Anaesthetist Locums Others Mean SD Table 2: One-Way ANOVA analysis for anaesthetic technique and anaesthetist on APT F(5,2385)= 4.785, P=0.001 F(16,2374)= , P=0.001 Figures 2 and 3 show that the maximum APT was 105 minutes (mean 26). Such variation in the APT will reduce the number of cases possible per list. This work was carried out in a teaching hospital and training is a possible cause for the prolongation of the APT. Whilst trainees require clinical experience, it may be that simulation in clinical training could be used help to ensure trainees receive the necessary training and reach a more advanced standard before they carry out procedures in an operating theatre.

4 Figure 2: Boxplot of anaesthetic technique against APT Figure 3: Boxplot of anaesthetist against APT Figure 4 shows that there are also outliers amongst the surgeons. If teaching is the reason for the surgical times outlying, surgical simulators could be used in training surgeons. Even though there is no robust evidence supporting the educational advantages of surgical simulation, we would anticipate that there would be a positive effect from the use of simulation by surgical trainees 6.

5 Figure 4: Boxplot of surgeon against ST Figures 3 and 4 shows that there is a 50% variation in the APT for different anaesthetists (mean: 20 to 35 minutes) and ST of different surgeons (mean: 60 to 90 minutes). Age, ASA grade and anaesthetic technique had minimal or no effect on the APT and ST. Other factors, including weight and anatomical abnormalities 7, which were not included in this study, might also affect the timings. Although maximising the utilisation of operating unit is important, patient safety is the top priority. There is a fine balance between speed and safety. Figure 5 represents the distribution of the total time. The mean TT for THR was 103 minutes (APT 26 + ST 77 minutes). If four cases were done per list, this would equate to a total of 412 minutes. However, the total time did not include the time taken for moving and positioning patient in the operating unit or the time taken to transfer the patient to recovery area. If 15 minutes was allowed for this, the total time per list would be 472 minutes. Even with the fastest anaesthetist (mean APT of 20 minutes) and fastest surgeon (mean ST of 63 minutes) a total of 490 minutes would be required for five THRs, making it ambitious to accommodate five THRs in an eight hour list.

6 Figure 5: Histogram of total time The British Orthopaedic Association advises surgeons to make maximum use of the available theatre time for elective surgery 8. Performing four cases in the allotted 480 minutes for a standard full day list would optimise the use of theatre resources. Conclusion This analysis showed that patient age was not a significant predictor of APT. Although the ASA grade, anaesthetic technique, and anaesthetist have statistically significant difference on APT, the difference in times is small. The average total operating time for a total hip replacement was 103 minutes suggesting that 4 cases in an 8-hour operating list is appropriate. References 1) Albouleish AE, Prough DS, Zornow MH, Hughes J, Whitten CW, Conlay LA, et al. The impact of longer-than-average times on billing of academic anesthesiology departments. Anesth and Analg 2001; 93: ) Wensing, Michel, Eric Vingerhoets, and Richard Grol. "Functional status, health problems, age and comorbidity in primary care patients." Quality of Life Research 10.2 (2001): ) Tessler, Michael J., et al. "The performance of spinal anesthesia is marginally more difficult in the elderly." Regional anesthesia and pain medicine 24.2 (1999): ) Juvin, Philippe, et al. "Difficult tracheal intubation is more common in obese than in lean patients." Anesthesia & Analgesia 97.2 (2003): ) Schuster, Martin, et al. "Reduction of anesthesia process times after the introduction of an internal transfer pricing system for anesthesia services." Anesthesia & Analgesia (2005): ) Atesok, Kivanc, et al. "Surgical simulation in orthopaedic skills training." Journal of the American Academy of Orthopaedic Surgeons 20.7 (2012): ) Rocke, D. A., et al. "Relative risk analysis of factors associated with difficult intubation in obstetric anesthesia." Anesthesiology 77.1 (1992): ) Advisory Book on Consultant Trauma and Orthopaedic Services: British Orthopaedic Association, First Published 1990; Revised 1998, 1999, 2007: (date last accessed 14 May 2014). Retrieved from