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

Area of Science:

• Orthopaedic surgery
• Patient outcomes research

Background:

• Investigating surgeon performance to enhance transparency in orthopaedic procedures.
• Assessing the impact of surgeon variability on patient outcomes.

Purpose of the Study:

• To determine if surgeon performance influences patient-reported outcomes (PROMs) one year after arthroscopic partial meniscectomy (APM).
• Hypothesizing no significant difference in PROMs based on the surgeon performing the APM.

Main Methods:

• Prospective cohort study of 794 patients undergoing APM (2018-2019) with 34 surgeons.
• Utilized multivariable models and Likelihood Ratio (LR) tests to assess surgeon impact on Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain, Patient Acceptable Symptom State (PASS), and KOOS-Pain improvement at 1 year.
• Controlled for demographic, meniscal pathology, and patient factors.

Main Results:

• Baseline KOOS-Pain score significantly predicted outcomes across all models (P < .001 to P = .002).
• Individual surgeon significantly impacted the 1-year KOOS-Pain mixed model (P = .004).
• Patient factors were stronger predictors of outcomes than surgeon characteristics.

Conclusions:

• Patient factors, particularly baseline KOOS-Pain, are more predictive of 1-year outcomes after APM than surgeon characteristics.
• Clinical focus should be on patient selection for improved APM outcomes, rather than solely on surgical technique.
• Further research is warranted to explore surgeon variability's long-term effects on patient outcomes.