Review assesses risk stratification tools for predicting complications in orthopaedic surgery, indicating promising utility of ECM and RSI 3.0.
Introduction: In orthopaedic surgery, accurate prediction of postoperative complications is critical to guide clinical decision-making, enable shared patient-surgeon discussions, and avoid adverse outcomes. Risk stratification tools aim to quantify this risk, but existing models vary widely in their performance and applicability. As health systems move toward value-based payment models and become increasingly litigious, refining these tools is increasingly important to avoid penalising surgeons treating high-risk patients and to ensure equitable access to care. Method: This review synthesised current evidence on risk-stratification tools in orthopaedics, focusing on their ability to predict complications and guide care. A practical analysis was also undertaken on 1,036 total knee arthroplasty patients at Massachusetts General Hospital, Harvard Medical School, to compare various risk stratification tools and to assess the variability of risk distributions based on the choice of tool. Results: Of existing risk stratification tools, the Elixhauser Comorbidity Measure (ECM) and Risk Stratification Index (RSI) 3.0 showed the strongest ability to predict common and major adverse events following orthopaedic surgery. Conversely, tools like the ACS NSQIP calculator demonstrated variable accuracy and poor performance for high-risk procedures. The total knee arthroplasty cohort analysis revealed disparate risk distributions for the same patient population depending on the tool chosen, representing high variability between tools and a high risk of introducing bias when selecting a particular tool for risk adjustment for public health or payment purposes. Discussion and conclusions: Despite the clinical importance of accurately assessing risk of complications and poor outcomes, no single risk-stratification tool is universally applicable across the orthopaedic population. ECM and RSI 3.0 are the most effective tools at present. Introducing risk adjustments can have unforeseen consequences as has been demonstrated in the United States.
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Boyle et al. (2025) studied this question.
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