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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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. |
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| Education Module Only | Active Comparator | Participants view the Joint Insights Education Module only |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| Measure | Description | Time Frame |
|---|---|---|
| Concordance between patient preferences and actual outcomes | A binary (yes/no) measure of whether a patient's response to the Knee Decision Quality Instrument question #1.6 (asking whether a patient wants surgical or non-surgical treatment) matches the observed outcome of whether the patient had TKA within 6 months (based on medical record review). A "yes" indicates greater concordance. | 3 months and 6 months following enrollment visit |
| Measure | Description | Time Frame |
|---|---|---|
| Patient perception of the level of shared decision making as measured by the CollaboRATE survey | Patients are asked three questions, each on a scale of 0-9, about how much effort they perceived their medical provider to have made to help the patient understand their health issues, understand what is important to the patient, and incorporate what is important to the patient in choosing a treatment. The scores range from 0-27 and a higher score indicates greater perceived shared decision making. |
Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UT Health Austin Musculoskeletal Institute | Austin | Texas | 78712 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41112505 | Derived | 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. | |
| 35190439 | 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. |
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| Immediately following enrollment visit |
| Patient/provider satisfaction with discussion as measured by a numeric rating scale | Patients and providers rate their satisfaction with the discussion on a 10 point scale (single question) in which a higher score indicates greater satisfaction. | Immediately following enrollment visit |
| Total consultation time (minutes) | Duration of surgeon/patient consultation in minutes as measured by research assistant. Continuous variable, no set scale. | Enrollment visit |
| Patient-reported overall health as measured by the PROMIS Global-10 tool | Patients answer ten survey questions regarding their overall physical and mental health; the measure produces two sub-scores, one each for physical and mental health. The physical health sub-score is scored on a scale of 16.6 to 67.7, with higher scores indicating better physical health. The mental health sub-score is scored on a scale of 21.2 to 67.6 with higher scores indicating better mental health. | Change in overall health from baseline visit to 3 month and 6 month follow up |
| Patient-reported capability level as measured by the KOOS JR tool | Patients answer seven Likert-scale survey questions about their degree of stiffness, pain, and difficulty in performing everyday tasks. The tool is scored from 0-100 with higher scores indicating higher levels of capability or functionality. | Change in limitations from baseline visit to 3 month and 6 month follow up |
| Treatment selected/TKR rate | Treatment choice (arthroplasty vs non-surgical treatment). Categorical. | 3 months and 6 months after initial visit |
| Patient perception of decisional conflict as measured by the Decisional Conflict Scale 10 (DCS-10) | The decisional conflict scale measures personal perceptions of : a) uncertainty in choosing options; b) modifiable factors contributing to uncertainty such as feeling uninformed, unclear about personal values and unsupported in decision making; and c) effective decision making such as feeling the choice is informed, values-based, likely to be implemented and expressing satisfaction with the choice. The likert scales are scored as 1-5, with the scoring reversed for negatively-phrased items. The mean is then taken and converted to a score ranging 0-100 with 100 being the least decision regret.10-item survey in which each item is scored as 0 (yes), 2 (unsure) or 4 (no). The items are summed, divided by 10, and multiplied by 25 to get a score ranging from 0-100 in which the patient is extremely uncertain about their decision. | Immediately following enrollment visit |
| Patient perception of decision regret, as measured by the Decision Regret Scale (DRS) | The Decision Regret Scale measures distress or remorse after a health care decision through five agree/disagree statements. The likert scales are scored as 1-5, with the scoring reversed for negatively-phrased items. The mean is then taken and converted to a score ranging 0-100 with 100 being the least decision regret. | 3 and 6 months following enrollment visit |