Incorporating Patient-Reported Outcomes Into Shared Decision Making With Patients With Osteoarthritis of the Hip or Knee
Condition: Osteo Arthritis Knee
MeSH terms: Osteoarthritis; Osteoarthritis, Knee; Osteoarthritis, Hip
Study type: Interventional

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.
    


Intervention name(s): Joint Insights decision aid
Intervention type(s): Other
Intervention description(s): 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.
Allocation: Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Other