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Taylor, Dean C.

https://orcid.org/0000-0001-7748-0469

Mayo Clinic

Duke University

Citations 2

Comparing Recurrence Rates and the Cost-Effectiveness of Arthroscopic Labral Repair and Nonoperative Management for Primary Anterior Shoulder Dislocations in Young Patients: A Decision-Analytic Markov Model-Based Analysis
Oeding, Jacob F. , Schulz, William R., Wang, Allen S. , Krych, Aaron J. , Taylor, Dean C. , Samuelsson, Kristian , Camp, Christopher L. , Krych, Aaron J , Wang, Allen , Samuelsson, Kristian , Oeding, Jacob F , Schulz, William R., Tagliero, Adam J.

The American Journal of Sports Medicine | October 12, 2024 | Volume: 52 | Issue: 13 | Pages: 3339-3348

10.1177/03635465241282342 Get It

Background: Value-based decision-making regarding nonoperative management versus early surgical stabilization for first-time anterior shoulder instability (ASI) events remains understudied. Purpose: To perform (1) a systematic review of the current literature and (2) a Markov model–based cost-effectiveness analysis comparing an initial trial of nonoperative management to arthroscopic Bankart repair (ABR) for first-time ASI. Study Design: Economic and decision analysis; Level of evidence, 3. Methods: A Markov chain Monte Carlo probabilistic model was developed to evaluate the outcomes and costs of 1000 simulated patients (mean age, 20 years; range, 12-26 years) with first-time ASI undergoing nonoperative management versus ABR. Utility values, recurrence rates, and transition probabilities were derived from the published literature. Costs were determined based on the typical patient undergoing each treatment strategy at the authors’ institution. Outcome measures included costs, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER). Results: The Markov model with Monte Carlo microsimulation demonstrated mean (± standard deviation) 10-year costs for nonoperative management and ABR of $38,649 ± $10,521 and $43,052 ± $9352, respectively. Total QALYs acquired over the 10-year time horizon were 7.67 ± 0.43 and 8.44 ± 0.46 for nonoperative management and ABR, respectively. The ICER comparing ABR with nonoperative management was found to be just $5725/QALY, which falls substantially below the $50,000 willingness-to-pay (WTP) threshold. The mean numbers of recurrences were 2.55 ± 0.31 and 1.17 ± 0.18 for patients initially assigned to the nonoperative and ABR treatment groups, respectively. Of 1000 samples run over 1000 trials, ABR was the optimal strategy in 98.7% of cases, with nonoperative management the optimal strategy in 1.3% of cases. Conclusion: ABR reduces the risk for recurrent dislocations and is more cost-effective despite higher upfront costs when compared with nonoperative management for first-time ASI in the young patient. While all these factors are important to consider in surgical decision-making, ultimate treatment decisions should be made on an individual basis and occur through a shared decision-making process.
Surgeon Applications of Patient Preferences in Treatment Decision Making for First-Time Anterior Shoulder Dislocation
Lau, Brian C. , Hutyra, Carolyn A. , Streufert, Benjamin D. , Reed, Shelby D. , Orlando, Lori A. , Taylor, Dean C. , Mather, Richard C. , Streufert, Benjamin, Huber, Joel C.

Orthopaedic Journal of Sports Medicine | December 4, 2020 | Volume: 8 | Issue: 12 | Pages: No page available

10.1177/2325967120966145 Get It

Background: Treatment of a first-time anterior shoulder dislocation (FTASD) is sensitive to patient preferences. The operative or nonoperative management debate provides an excellent opportunity to learn how surgeons apply patient preferences in treatment decisions. Purpose: To determine how patient preferences (repeat dislocation risk, recovery difficulties, fear of surgery, treatment costs) and surgeon factors influence a surgeon’s treatment plan for FTASD. Study Design: Cross-sectional study. Methods: Eight clinical vignettes of hypothetical patients with FTASD (including age, sex, and activity level) were presented to members of the Magellan Society. A second set of matched vignettes with patient preferences and clinical variables were also presented. The vignettes represented scenarios in which evidence does not favor one treatment over another. Respondents were asked how they would manage each hypothetical case. Respondents also estimated the risk of redislocation for the nonoperative cases for comparison with the published rates. Finally, respondents completed a Likert-scale questionnaire to determine their perceptions on factors influencing their decisions. Results: A total of 103 orthopaedic surgeons completed the survey; 48% practiced in an academic hospital; 79% were in practice for 10 years or longer; and 75% had completed a sports medicine fellowship. Patient preferences were the single most important factor influencing treatment recommendation, with activity type and age also important. Just 62% of the surgeon estimates of the risk of redislocation were consistent with the published rates. The inclusion of patient preferences to clinical variables changed treatment recommendations in 62.5% of our hypothetical cases. Respondents rated patient treatment preference as the leading factor in their treatment decision making. Conclusion: Patient preferences were important when deciding the appropriate treatment for FTASD. Respondents were inconsistent when applying evidence in their decision making and estimates of recurrent instability. Decision support tools that deliver patient preferences and personalized evidence-based outcome estimates improve the quality of decision making at the point of care.