Incorporating Patient-Reported Outcomes Into Shared Decision Making With Patients With Osteoarthritis of the Hip or Knee

NCT ID: NCT04805554

Last Updated: 2024-01-05

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 200 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-02-22
• Study Completion Date: 2023-05-30

Brief Summary

Osteoarthritis (OA) of the knee constitutes a major public health problem. Treatment options for knee OA range from lifestyle changes to pharmacological management to total knee replacement surgery. As a "preference-sensitive" condition, management of OA of the knee is ideally suited for shared decision making (SDM), taking into consideration benefits, risks, and patients' health status, values, and goals. Patient-reported outcomes (PROs) reflect health status from the patient's perspective. For knee OA, relevant PROs include pain and other symptoms, functional status and limitations, and overall health. Prior research indicates that patients with higher baseline physical function and/or poor baseline mental health do not benefit as much from total knee replacement. Still, due to logistical challenges, costs, and disruptions in workflow, PROs have not yet achieved their full potential in clinical care.

Musculoskeletal providers at Dell Medical School and UT Health Austin currently collect general and condition-specific PROs from every patient seen in their Musculoskeletal Institute. PROs are collected via an electronic interface and results are pulled into the Athena electronic health record (EHR). Given the promise of combining PRO data with clinical and demographic data, musculoskeletal providers at UT Health Austin have begun utilizing an innovative electronic PRO-based predictive analytic tool at the point of care to guide SDM in patients with knee OA.

This project plans to evaluate the clinical effectiveness and impact of the PRO-guided predictive analytic SDM tool and process in a randomized controlled trial in Austin. Outcomes will include decision quality, as reported by patients; treatment decision (surgical vs. non-surgical); and decisional conflict and regret.

Our project contributes to AHRQ's strategy to use health IT to improve quality and outcomes by evaluating a tool and process for the use of PRO data at the point of care. The model being tested puts patients at the center of their care by enabling them to participate in informed decision making by using their personal health data, preferences, and prognostic models. Knowledge gained will be critical to scaling and spreading use of this PRO-guided SDM tool among patients with knee OA nationally.

Conditions

Osteo Arthritis Knee

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

Joint Insights Decision Aid

Participants view the entire Joint Insights decision aid for knee osteoarthritis including: Education Module with information about knee osteoarthritis and risks and benefits of various treatment options, Preferences and Values elicitation questions, and Personalized Risk/Benefit Report.

Group Type: EXPERIMENTAL

Joint Insights decision aid

Intervention Type: OTHER

The Joint Insights decision aid was developed by Dell Medical School faculty in collaboration with OM1, a health outcomes and predictive analytics company. This decision aid uses patient-report outcome measures (PROMs) - specifically, the PROMIS Global and the KOOS JR - along with patient clinical and demographic information (age, sex, race, ethnicity, chronic narcotic use, body mass index), in machine-learning-based predictive analytic models to provide personalized estimates of likely benefit or harm from total knee replacement surgery. The tool is designed to collect PROMs or pull in PROMs collected through other systems (e.g., an EHR or a third-party PROM platform). It also provides condition-specific education to patients with knee OA and allows a patient to reflect on and document their preferences and goals. The personalized risk/benefit report generated by the decision aid is meant to be discussed with the patient's provider to enhance shared decision making.

Education Module Only

Participants view the Joint Insights Education Module only

Group Type: ACTIVE_COMPARATOR

Joint Insights decision aid

Intervention Type: OTHER

The Joint Insights decision aid was developed by Dell Medical School faculty in collaboration with OM1, a health outcomes and predictive analytics company. This decision aid uses patient-report outcome measures (PROMs) - specifically, the PROMIS Global and the KOOS JR - along with patient clinical and demographic information (age, sex, race, ethnicity, chronic narcotic use, body mass index), in machine-learning-based predictive analytic models to provide personalized estimates of likely benefit or harm from total knee replacement surgery. The tool is designed to collect PROMs or pull in PROMs collected through other systems (e.g., an EHR or a third-party PROM platform). It also provides condition-specific education to patients with knee OA and allows a patient to reflect on and document their preferences and goals. The personalized risk/benefit report generated by the decision aid is meant to be discussed with the patient's provider to enhance shared decision making.

Interventions

Joint Insights decision aid

The Joint Insights decision aid was developed by Dell Medical School faculty in collaboration with OM1, a health outcomes and predictive analytics company. This decision aid uses patient-report outcome measures (PROMs) - specifically, the PROMIS Global and the KOOS JR - along with patient clinical and demographic information (age, sex, race, ethnicity, chronic narcotic use, body mass index), in machine-learning-based predictive analytic models to provide personalized estimates of likely benefit or harm from total knee replacement surgery. The tool is designed to collect PROMs or pull in PROMs collected through other systems (e.g., an EHR or a third-party PROM platform). It also provides condition-specific education to patients with knee OA and allows a patient to reflect on and document their preferences and goals. The personalized risk/benefit report generated by the decision aid is meant to be discussed with the patient's provider to enhance shared decision making.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• New patients
• Presumptive diagnosis of knee OA
• Aged 45 to 89
• K-L Joint OA severity grade 3 to 4 (moderate to severe)
• KOOS JR score 0-85
• Able to consent

Exclusion Criteria

• Prior total knee replacement (TKR)
• Prior consultation with orthopaedic surgeons for TKR
• Prior experience with Joint Insights
• Trauma condition or psoriatic/rheumatoid arthritis
• Non-English or Non-Spanish speakers
• BMI <20 or >46

• Minimum Eligible Age: 45 Years
• Maximum Eligible Age: 89 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Texas at Austin

OTHER

Sponsor Role: lead

Responsible Party

Kevin Bozic

Professor and Chair

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

UT Health Austin Musculoskeletal Institute

Austin, Texas, United States

Countries

United States

References

Jayakumar P, Rathouz PJ, Lin E, Trutner Z, Uhler LM, Andrawis J, Koenig KM, Tsevat J, Bozic KJ. Shared decision making using digital twins in knee osteoarthritis care: a randomized clinical trial of an AI-enabled decision aid versus education alone on decision quality, physical function, and user experience. EClinicalMedicine. 2025 Oct 4;89:103545. doi: 10.1016/j.eclinm.2025.103545. eCollection 2025 Nov.

Reference Type: DERIVED

PMID: 41112505 (View on PubMed)

Lin E, Uhler LM, Finley EP, Jayakumar P, Rathouz PJ, Bozic KJ, Tsevat J. Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol. BMJ Open. 2022 Feb 21;12(2):e055933. doi: 10.1136/bmjopen-2021-055933.

Reference Type: DERIVED

PMID: 35190439 (View on PubMed)

Other Identifiers

R21HS027037

Identifier Type: AHRQ

Identifier Source: org_study_id

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