ASPIRE: Advancing Safety Process Innovation in Rheumatology

 描述(申请人提供)：尽管人们普遍认识到美国医疗保健系统中普遍存在的患者安全问题，但开发可行的、可扩展的解决方案的研究一直滞后，特别是在门诊环境中。在使用高风险免疫抑制药物的门诊患者的护理中，尤其迫切需要新的方法来提高安全性，因为关于这类药物中可预防的不良事件的报道有所增加。到目前为止，还没有研究仔细定义这些安全风险的流行病学。拟议的使用登记表推进安全流程创新(ASPIRE)项目将使用先进的电子健康记录(EHR)数据分析来确定接受高风险药物治疗的患者的门诊患者安全错误和不良事件的严重程度(目标1)。我们还将描述这些风险在种族/民族、社会经济地位和医疗复杂性方面的差异。将审查三类患者安全流程：1)减少不良用药事件的预防做法，2)对使用高风险免疫抑制药物的患者进行安全监测，以及3)管理药物毒性监测的异常结果。这些发现将被用来为eMeasures的开发提供信息，这是一种新的质量测量方法，使用自动提取的eHR信息为临床医生和卫生系统提供有关特定患者安全问题的信息(目标2)。我们将使用电子测量标准，包括质量数据模型(QDM)、健康质量测量格式(HQMF)和其他结构化编码术语来开发、指定和测试系统范围内的电子测量原型。HIT-解决方案，如eMeasures，可以应用于整个EHR数据存储库，作为医学研究所设想的持续学习医疗保健系统的基础。这里提出的工作为进一步测试和在全国范围内传播电子措施奠定了基础，以监测和提高在门诊环境中使用高风险药物的人的安全性。

 DESCRIPTION (provided by applicant): Despite widespread recognition of pervasive patient safety problems in the U.S. health care system, research to develop feasible, scalable solutions has lagged, particularly in the ambulatory setting. The need for new approaches to improve safety is especially pressing in the care of ambulatory patients using high-risk immunosuppressive medications, as reports of preventable adverse events among this category of drugs have increased. To date, no studies have carefully defined the epidemiology of these safety risks. The proposed Advancing Safety Process Innovation Using Registries (ASPIRE) project will use advanced electronic health record (EHR) data analytics to define the magnitude of ambulatory patient safety errors and adverse events for patients receiving high risk medications (Aim 1). We will also characterize disparities in these risks across race/ethnicity, socioeconomic status, and medical complexity. Three categories of patient safety processes will be examined: 1) preventive practices that reduce adverse medication events, 2) safety monitoring for patients using high-risk immunosuppressive medications, and 3) management of abnormal results from medication toxicity monitoring. These findings will be used to inform the development of eMeasures, a new approach to quality measurement that uses automatically extracted EHR information to give clinicians and health systems information regarding specific patient safety problems (Aim 2). We will use eMeasurement standards, including the Quality Data Model (QDM), Health Quality Measures Format (HQMF) and other structured coded terminologies to develop, specify and test system-wide prototype eMeasures. HIT-solutions such as eMeasures that can be applied across EHR data repositories serve as a foundation for a continuous learning health care system, as envisioned by the Institute of Medicine. The work proposed here builds the groundwork for further testing and nationwide dissemination of eMeasures to monitor and improve safety for those using high-risk medications in the ambulatory setting.