Incorporating Patient-Reported Outcomes into Shared Decision Making with Patients with Osteoarthritis of the Hip or Knee

膝关节骨关节炎（OA）是一个主要的公共卫生问题。膝关节OA的治疗选择范围 从生活方式的改变到药物治疗再到全膝关节置换手术。作为一种“偏好- 膝关节OA的管理非常适合于共享决策（SDM）， 考虑利益、风险和患者的健康状况、价值观和目标。患者报告结局 （PRO）从患者的角度反映健康状况。对于膝关节OA，相关PRO包括疼痛和其他 症状、功能状态和限制以及整体健康状况。先前的研究表明， 较高的基线身体功能和/或较差的基线心理健康状况不会从全膝关节置换术中获益 更换.尽管如此，由于物流挑战、成本和工作流程中断，PRO尚未实现 他们在临床护理中的全部潜力。 戴尔医学院和UT Health Austin的肌肉骨骼提供商目前收集一般和条件- 从他们的肌肉骨骼研究所看到的每一个病人的特定PRO。PRO通过电子 接口和结果被拉入雅典娜电子健康记录（EHR）。考虑到结合 PRO数据与临床和人口统计数据，肌肉骨骼提供者在UT健康奥斯汀已经开始 在护理点使用创新的基于PRO的电子预测分析工具， 膝关节OA患者。然而，到目前为止，该工具尚未集成到EHR和流程中 还没有无缝集成到临床工作流程中。因此，它还没有准备好传播。 在这个为期2年的有效性和实施（混合型2）项目中，我们计划：1）评估临床 PRO引导的预测分析SDM工具和过程在随机 对照试验在奥斯汀;和2）实施和评估使用PRO指导的预测分析SDM工具 在圣安东尼奥进行，这是一个对PRO和SDM具有不同经验水平的环境， 不同的人口，不同的EHR。结果将包括患者报告的决策质量;治疗 决策（手术与非手术）;以及利益相关者对工具和SDM过程的满意度。 我们的项目有助于AHRQ的战略，使用卫生信息技术，以提高质量和成果，通过评估一个 在护理点使用PRO数据的工具和过程。我们正在测试的模型将患者置于 他们的护理中心，使他们能够参与知情的决策，利用他们的个人健康 数据、偏好和预测模型。获得的知识对于扩大和推广使用 在全国膝关节OA患者中使用PRO指导的SDM工具。

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. To this point, however, the tool hasn’t been integrated into the EHR and the process hasn’t been integrated seamlessly into clinic workflow. As such, it is not yet ready for dissemination. In this 2-year effectiveness and implementation (hybrid type 2) project, we plan to: 1) evaluate the clinical effectiveness and impact of the PRO-guided predictive analytic SDM tool and process in a randomized controlled trial in Austin; and 2) implement and evaluate use of the PRO-guided predictive analytic SDM tool and process in San Antonio, a setting with a different level of experience with PROs and SDM, different clinical population, and different EHR. Outcomes will include decision quality, as reported by patients; treatment decision (surgical vs. non-surgical); and stakeholder satisfaction with the tool and SDM process. 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 we are testing 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.