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Orthopaedic Proceedings
Vol. 102-B, Issue SUPP_9 | Pages 31 - 31
1 Oct 2020
Jayakumar P Furlough K Uhler L Grogan-Moore M Gliklich R Rathouz P Bozic KJ
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Introduction

The application of artificial intelligence (A.I) using patient reported outcomes (PROs) to predict benefits, risks, benefits and likelihood of improvement following surgery presents a new frontier in shared decision-making. The purpose of this study was to assess the impact of an A.I-enabled decision aid versus patient education alone on decision quality in patients with knee OA considering total knee replacement (TKR). Secondarily we assess impact on shared decision-making, patient satisfaction, functional outcomes, consultation time, TKR rates and treatment concordance.

Methods

We performed a randomized controlled trial involving 130 new adult patients with OA-related knee pain. Patients were randomized to receive the decision aid (intervention group, n=65) or educational material only (control group, n=65) along with usual care. Both cohorts completed patient surveys including PROs at baseline and between 6–12 weeks following initial evaluation or TKR. Statistical analysis included linear mixed effect models, Mann-Whitney U tests to assess for differences between groups and Fisher's exact test to evaluate variations in surgical rates and treatment concordance.