This study evaluates a technology-enabled decision aid that provides evidence-based education (i.e. on understanding the condition, treatment options and comparisons, patient values and question & answer quiz) and personalized, quantifiable benefit-risk ratio alongside the level of potential benefit in relation to joint stiffness, joint pain and quality of life. The study will be performed in the setting of an integrated care system providing patient-centered care for hip and knee osteoarthritis over the full cycle of care. The impact of a technology-enabled decision aid incorporating predictive analytics with machine learning capabilities on decision quality, activation, experience & limitations of patients in this setting is relatively unknown.

Inclusion Criteria:

• All patients with a presumptive diagnosis of knee OA aged between 45 and 89 (in-line with the decision aid algorithm)
• Radiographic evidence of moderate to severe osteoarthritis (Kellgren and Lawrence grade 3-4)
• KOOS Jr scores between 0-85 (in-line with the decision-aid algorithm)
• Participant able to give informed consent for participation in the study

Exclusion Criteria:

• Kellgren and Lawrence scale for classification of osteoarthritis grade 0-2
• Patients with a prior experience of total joint replacement
• Patient with experience with the pilot form of the decision aid
• Patients undergoing consideration for revision joint replacement
• Patients seeking care for trauma condition or psoriatic/rheumatoid arthritis
• Non-English or Non-Spanish speakers
• Patients with BMI below 20 or above 46 (in-line with the decision-aid algorithm)