Predicting the need for surgical intervention prior to first encounter for individuals with shoulder complaints: a unique approach

BACKGROUND: Increasing demand for musculoskeletal care necessitates efficient scheduling and matching of patients with the appropriate provider. However, up to 47% to 60% of orthopedic visits are made without formal triage. The purpose of this study was to develop a method to identify, prior to the initial office visit, the probability that a patient with shoulder symptoms will need surgery so that he or she can be appropriately matched with an operative or nonoperative provider. We hypothesized that patients who had an injury, previously saw an orthopedic provider, or previously underwent magnetic resonance imaging on the affected shoulder would be more likely to undergo surgery. METHODS: Drawing from expert opinion on potential risk factors (which could be identified prior to the initial office visit) for requiring operative intervention for a chief complaint of shoulder symptoms, we developed a branching-logic questionnaire that required a maximum of 7 responses from the patient during the scheduling process. We administered the questionnaire to patients calling with a chief complaint of shoulder symptoms at the time of initial appointment scheduling in a sports health network. A chart review was later completed to determine the ultimate treatment (operative vs. nonoperative) of each patient's complaint. A multivariate predictive model was then developed to determine the characteristics of patients with a higher surgical risk. RESULTS: We successfully developed a model capable of determining surgical risk from 7% to 90% based on patient sex, previous magnetic resonance imaging status, and injury status. CONCLUSIONS: Our predictive model can aid in patient clinical scheduling and ensure optimal matching of a patient with the best provider for the patient's care. Decreased wait times and appropriate matching may lead to increased patient satisfaction, superior outcomes, and more efficient use of health care resources.