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

NCT04805554 | Completed

• 1 other identifier: R21HS027037
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

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

Outcome Measures

Primary Outcomes (1)

• Patient perception of decision process and quality as measured by the Knee Decision Quality Instrument (Knee-DQI)

  Patients are asked about whether they were offered a choice between treatments (yes/no), to what extent the pros and cons were discussed (a lot/some/a little/not at all), and whether the health care provider asked for their preferences (yes/no). Participants receive 1 point for a response of "yes" or "a lot/some." The total points are summed and then divided by the total number of items to result in scores from 0-100%, with higher scores indicated a more shared decision making process.

  Immediately following enrollment visit

Secondary Outcomes (1)

• Concordance between patient preferences and actual outcomes

  3 months and 6 months following enrollment visit

Other Outcomes (8)

• Patient perception of the level of shared decision making as measured by the CollaboRATE survey

  Immediately following enrollment visit

• Patient/provider satisfaction with discussion as measured by a numeric rating scale

  Immediately following enrollment visit

• Total consultation time (minutes)

  Enrollment visit

Study Arms (2)

Joint Insights Decision Aid

EXPERIMENTAL

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.

Other: Joint Insights decision aid

Education Module Only

ACTIVE COMPARATOR

Participants view the Joint Insights Education Module only

Other: Joint Insights decision aid

Interventions

Joint Insights decision aid 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; Joint Insights Decision Aid

Eligibility Criteria

• Age: 45 Years - 89 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• University of Texas at Austin: lead

Study Sites (1)

UT Health Austin Musculoskeletal Institute

Austin, Texas, 78712, United States

Location

Related Publications (2)

• 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.

  PMID: 41112505 DERIVED

• 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.

  PMID: 35190439 DERIVED

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor and Chair

Study Record Dates

• First Submitted: March 15, 2021
• First Posted: March 18, 2021
• Study Start: February 22, 2021
• Primary Completion: May 30, 2023
• Study Completion: May 30, 2023
• Last Updated: January 5, 2024

Record last verified: 2024-01

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)