Improving the referral pattern of patients with knee osteoarthritis to the orthopaedic surgeon: Development and evaluation of a new screening algorithm based on patient-reported data and radiographs.

INTRODUCTION:Many patients with knee osteoarthritis referred to orthopaedic surgeons are not eligible for surgery and might benefit from being examined by other healthcare professionals. The objective of this study was to develop and test a screening algorithm to define relevant referral to the OS. METHODS:Prior to clinical examination, 173 consecutive patients referred to the orthopaedic outpatient clinic completed questionnaires, and radiographic osteoarthritis severity was graded. The gold standard for relevant referral to an orthopaedic surgeon was based on actual treatment. The performance of the algorithm in predicting relevant referrals and total knee replacement (TKR) was assessed using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS:Referral to an orthopaedic surgeon was considered relevant in 65% (113/173) of patients. Sensitivity, specificity, PPV and NPV for predicting relevant referral to an orthopaedic surgeon were 0.70, 0.56, 0.76 and 0.48, respectively. The corresponding estimates for predicting TKR surgery were 0.92, 0.56, 0.55 and 0.92. CONCLUSIONS:The algorithm was able to identify most patients relevant for referral to an orthopaedic surgeon, but less suitable for identifying those not relevant. The algorithm demonstrated excellent performance in predicting TKR surgery. With further development, this screening algorithm might contribute to improvement of the referral pattern in the orthopaedic outpatient clinic.