@文章{信息:doi/10.2196/37714，作者=“Franklin, Patricia D和Oatis, Carol A和Zheng, Hua和Westby, Marie D和Peter, Wilfred和Laraque-Two Elk, Jeremie和Rizk, Joseph和Benbow, Ellen和Li, Wenjun”，标题=“基于web的系统捕获全膝关节置置术后物理治疗干预的一致和完整的真实世界数据:“设计与评价研究”，期刊=“JMIR Rehabil Assist Technol”，年=“2022”，月=“10月”，日=“27”，卷=“9”，数=“4”，页=“e37714”，关键词=“结构化数据;基于网络的临床数据采集;物理疗法;全膝关节置换术;电子健康记录;真实的证据;现实世界的数据;数据;治疗; knee; knee replacement; clinical intervention", abstract="Background: Electronic health records (EHRs) have the potential to facilitate consistent clinical data capture to support excellence in patient care, quality improvement, and knowledge generation. Despite widespread EHR use, the vision to transform health care system and its data to a ``learning health care system'' generating knowledge from real-world data is limited by the lack of consistent, structured clinical data. Objective: The purpose of this paper was to demonstrate the design of a web-based structured clinical intervention data capture system and its evaluation in practice. The use case was ambulatory physical therapy (PT) treatment after total knee replacement (TKR), one of the most common and costly procedures today. Methods: To identify the PT intervention type and intensity (or dose) used to treat patients with knee arthritis following TKR, an iterative user-centered design process refined an initial list of PT interventions generated during preliminary chart reviews. Input from practicing physical therapists and national and international experts refined and categorized the interventions. Next, a web-based, hierarchical structured system for intervention and intensity documentation was designed and deployed. Results: The PT documentation system was implemented by 114 physical therapists agreeing to record all interventions at patient visits. Data for 161 patients with 2615 PT visits were entered by 83 physical therapists. No technical problems with data entry were reported, and data entry required less than 2 minutes per visit. A total of 42 (2{\%}) interventions could not be categorized and were recorded using free text. Conclusions: The use of user-centered design principles provides a road map for developing clinically feasible data capture systems that employ structured collection of uniform data for use by multiple practitioners across institutions to complement and augment existing EHRs. Secondarily, these data can be analyzed to define best practices and disseminate knowledge to practice. ", issn="2369-2529", doi="10.2196/37714", url="https://rehab.www.mybigtv.com/2022/4/e37714", url="https://doi.org/10.2196/37714", url="http://www.ncbi.nlm.nih.gov/pubmed/36301608" }