Division of Medical Oncology, Department of Medicine, Duke University Health System, Duke University Medical Center (DUMC), Durham, NC 27710, USA.
Med Care. 2010 Jun;48(6 Suppl):S32-8. doi: 10.1097/MLR.0b013e3181db53a4.
"Rapid learning healthcare" presents a new infrastructure to support comparative effectiveness research. By leveraging heterogeneous datasets (eg, clinical, administrative, genomic, registry, and research), health information technology, and sophisticated iterative analyses, rapid learning healthcare provides a real-time framework in which clinical studies can evaluate the relative impact of therapeutic approaches on a diverse array of measures.
This article describes an effort, at 1 academic medical center, to demonstrate what rapid learning healthcare might look like in operation. The article describes the process of developing and testing the components of this new model of integrated clinical/research function, with the pilot site being an academic oncology clinic and with electronic patient-reported outcomes (ePROs) being the foundational dataset.
Steps included: feasibility study of the ePRO system; validation study of ePRO collection across 3 cancers; linking ePRO and other datasets; implementation; stakeholder alignment and buy in, and; demonstration through use cases.
Two use cases are presented; participants were metastatic breast cancer (n = 65) and gastrointestinal cancer (n = 113) patients at 2 academic medical centers.
(1) Patient-reported symptom data were collected with tablet computers; patients with breast and gastrointestinal cancer indicated high levels of sexual distress, which prompted multidisciplinary response, design of an intervention, and successful application for funding to study the intervention's impact. (2) The system evaluated the longitudinal impact of a psychosocial care program provided to patients with breast cancer. Participants used tablet computers to complete PRO surveys; data indicated significant impact on psychosocial outcomes, notably distress and despair, despite advanced disease. Results return to the clinic, allowing iterative update and evaluation.
An ePRO-based rapid learning cancer clinic is feasible, providing real-time research-quality data to support comparative effectiveness research.
“快速学习医疗保健”呈现出一种新的基础设施，以支持比较有效性研究。通过利用异构数据集（如临床、行政、基因组、登记和研究）、健康信息技术和复杂的迭代分析，快速学习医疗保健提供了一个实时框架，在这个框架中，临床研究可以评估治疗方法对各种措施的相对影响。
本文描述了在一个学术医疗中心努力展示快速学习医疗保健在实际操作中可能是什么样子。本文描述了开发和测试这种新的综合临床/研究功能模型的各个组成部分的过程，试点地点是一个学术肿瘤诊所，电子患者报告的结果（ePRO）是基础数据集。
步骤包括：ePRO 系统的可行性研究；在 3 种癌症中进行 ePRO 收集的验证研究；ePRO 和其他数据集的链接；实施；利益相关者的协调和认可；以及通过用例来演示。
提出了两个用例；参与者是 2 个学术医疗中心的转移性乳腺癌（n=65）和胃肠道癌症（n=113）患者。
（1）使用平板电脑收集患者报告的症状数据；患有乳腺癌和胃肠道癌症的患者报告了高水平的性困扰，这促使了多学科反应、干预设计和成功申请资金来研究干预措施的影响。（2）该系统评估了为乳腺癌患者提供的心理社会护理计划的纵向影响。参与者使用平板电脑完成 PRO 调查；数据表明，尽管疾病已经很严重，但对心理社会结果，特别是困扰和绝望，有显著影响。结果返回给诊所，允许迭代更新和评估。
基于电子患者报告的快速学习癌症诊所是可行的，提供实时的研究质量数据，以支持比较有效性研究。
