Surgeon Performance as a Predictor for Patient-Reported Outcomes After Arthroscopic Partial Meniscectomy.

BACKGROUND

Surgeon performance has been investigated as a factor affecting patient outcomes after orthopaedic procedures to improve transparency between patients and providers.

PURPOSE/HYPOTHESIS: The purpose of this study was to identify whether surgeon performance influenced patient-reported outcomes (PROMs) 1 year after arthroscopic partial meniscectomy (APM). It was hypothesized that there would be no significant difference in PROMs between patients who underwent APM from various surgeons.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

A prospective cohort of 794 patients who underwent APM between 2018 and 2019 were included in the analysis. A total of 34 surgeons from a large multicenter health care center were included. Three multivariable models were built to determine whether the surgeon-among demographic and meniscal pathology factors-was a significant variable for predicting the Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain subscale, the Patient Acceptable Symptom State (PASS), and a 10-point improvement in the KOOS-Pain at 1 year after APM. Likelihood ratio (LR) tests were used to determine the significance of the surgeon variable in the models.

RESULTS

The 794 patients were identified from the multicenter hospital system. The baseline KOOS-Pain score was a significant predictor of outcome in the 1-year KOOS-Pain model (odds ratio [OR], 2.1 [95% CI, 1.77-2.48]; < .001), the KOOS-Pain 10-point improvement model (OR, 0.57 [95% CI, 0.44-0.73), and the 1-year PASS model (OR, 1.42 [95% CI, 1.15-1.76]; = .002) among articular cartilage pathology (bipolar medial cartilage) and patient-factor variables, including body mass index, Veterans RAND 12-Item Health Survey-Mental Component Score, and Area Deprivation Index. The individual surgeon significantly impacted outcomes in the 1-year KOOS-Pain mixed model in the LR test ( = .004).

CONCLUSION

Patient factors and characteristics are better predictors for patient outcomes 1 year after APM than surgeon characteristics, specifically baseline KOOS-Pain, although an individual surgeon influenced the 1-Year KOOS-Pain mixed model in the LR test. This finding has key clinical implications; surgeons who wish to improve patient outcomes after APM should focus on improving patient selection rather than improving the surgical technique. Future research is needed to determine whether surgeon variability has an impact on longer-term patient outcomes.