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Learning of A CAOS Enhanced Mechanical Instrument System for Total Knee Arthroplasty: A CUSUM Analysis

Yifei Dai, PhD

Exactech, Inc

James I. Huddleston III, MD

Stanford University School of Medicine

Matt Rueff

Exactech, Inc.

Laurent Angibaud, Dipl. Ing.

Exactech, Inc.

Derek F. Amanatullah, MD

Stanford University School of Medicine

INTRODUCTION

Computer-assisted orthopaedic surgery (CAOS) has been shown to offer improved accuracy to total knee arthroplasty (TKA) compared to conventional techniques.1 Despite promising results, one of the drawbacks for surgeons to adopt CAOS technology may be the requirement of switching from conventional to CAOS-specific instruments. Recent advances in CAOS, introduced a system designed to enhance the existing conventional mechanical instruments, removing the need for significant instrument change. While TKAs performed by this system can benefit from the improved accuracy offered by CAOS technology, it is important to assess the learning of the system to evaluate the efficiency of its adoption. Cumulative sum control chart (CUSUM) has been applied to assess the stabilization of industrial production processes and proven to be an objective and effective tool to evaluate the learning process. This method is currently under-recognized in TKA research. The purpose of this study was to use CUSUM to assess the learning curve on the critical surgical steps using the new CAOS enhanced mechanical instrument system.

MATERIALS

Four surgeons (2 seniors, and 2 fellows with no prior CAOS experience) were included in this sawbone study. Each surgeon performed proximal tibial and distal femoral resections on 6 knee models using conventional instrumentation and six knee models with the same conventional instrument system enhanced by CAOS. All resections were created targeting neutral coronal alignment, 3° tibial slope, and 10mm resection depth. For each surgeon, the cumulative sum of deviations was calculated2, specifically: the CUSUM score of the first case was the difference between the time of the first case and the mean surgical time. The CUSUM score of the second cases were the previous cases’ CUSUM score, plus the difference between the surgical time of the second case and the mean surgical time. This recursive process continued until the last case, which was calculated as 0. CUSUM score was plotted in chronological order for each surgeon. A horizontal trend in the plot signified the process was operating with stability. The case number (cases to proficiency) by which the CUSUM plot entered the horizontal trend was identified as the end of learning for each surgeon. The cases to proficiency was compared between the senior and the fellow surgeons. The surgical time in CAOS-enhanced cases during and after learning was compared to the conventional cases within each surgeon. Due to limited case numbers per surgeon, statistical assessment of the differences was not performed. The increase in surgical time after learning the CAOS system was compared to conventional cases on the pooled data (significance defined as p<0.05).

Table 1. Summary of learning characteristics in the senior surgeon and fellow surgeon groups.

Table 1. Summary of learning characteristics in the senior surgeon and fellow surgeon groups.

RESULTS

The CUSUM plot exhibited three unique phases in the first six cases of each surgeon with Phase II demonstrating stabilization of the process (Figure1). No substantial difference between the senior and novice surgeon groups was found in the speed of learning (2-3 cases). However, compared to the senior surgeons, the fellow surgeons demonstrated slightly steeper learning curve by adding 3-4 minutes to their learning cases (Figures 1 and 2). Compared to the conventional TKA, adding CAOS enhancement slightly increased time by 4-6 minutes during learning, and the difference reduced to 2-3 minutes after learning. No significant difference in surgical time was found between senior and fellow surgeons after their learning (Figure 2B).

Figure 1. Graphs on the CUSUM deviance charts for A) senior surgeon #1, B) senior surgeon #2, C) fellow surgeon #1, and D) fellow surgeon #2. The fellow surgeons exhibited a steeper learning curve compared to the senior surgeons. The graph was plotted according to the chronological case numbers.

Figure 1. Graphs on the CUSUM deviance charts for A) senior surgeon #1, B) senior surgeon #2, C) fellow surgeon #1, and D) fellow surgeon #2. The fellow surgeons exhibited a steeper learning curve compared to the senior surgeons. The graph was plotted according to the chronological case numbers.

DISCUSSION

This study applied CUSUM method to analyze learning curve of a CAOS-enhanced mechanical instrument system for TKA. As the CAOS guidance is based on existing conventional mechanical instruments, the adoption of the technology exhibited minimum learning effort (2-3 cases to learn), independent of the surgeon’s experience level.

Compared to conventional cases performed using the same mechanical instrument system, using the CAOS-enhanced system moderately increased the surgical time in critical bony resection steps by 4-6 minutes during learning. After quick mastering of the technology, the surgical time was only slightly extended by 2-3 minutes compared to conventional cases. The results demonstrated minimum impact on surgical efficiency by introducing CAOS to the existing conventional mechanical instruments, offering the proven benefit of CAOS technology without major disruption in the surgical tools the surgeons are already familiar with. Utilization of advanced methods in studying learning curves can provide an improved understanding of CAOS learning in general, but also allows differences in learning between individual surgeons to be explored. Further investigation of this study may include expanding the CUSUM assessment to the entire TKA surgical duration with more surgeon groups with different characteristics.

Figure 2. Comparison of surgical time between during learning CAOS enhancement, after learning CAOS enhancement, and mechanical instrumentation only case gruops in each individual surgeon. Due to limited cases number per surgeon, statistical assessment of the differences was not performed.

Figure 2. Comparison of surgical time between during learning CAOS enhancement, after learning CAOS enhancement, and mechanical instrumentation only case gruops in each individual surgeon. Due to limited cases number per surgeon, statistical assessment of the differences was not performed.

SIGNIFICANCE/CLINICAL RELEVANCE

An advanced method (CUSUM) was applied to assess the learning curve of a CAOS-enhanced mechanical instrument system. The data demonstrated a short learning duration for both senior and fellow surgeons and a mild impact on surgical time during learning.

REFERENCES

  1. Sparmann M, et al. Bone Joint Surg Br. 2003;85(6):830-5.
  2. Bokhari MB, et al. Surg Endosc. 2011;25(3):855-60.
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