Timmerman Livie, Dutton Heather, McDannald Nicholas, Smitherman Emily A, Mannion Melissa L
Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, United States.
Information Technology, Children's of Alabama, Birmingham, AL, United States.
Front Pediatr. 2024 Aug 13;12:1428792. doi: 10.3389/fped.2024.1428792. eCollection 2024.
This report describes our experience in electronic health record (EHR) note modification and creation of an external dashboard to create a local learning health system that contributes to quality improvement and patient care within our pediatric rheumatology clinic.
We applied quality improvement methodology to develop a more reliable and accurate system to identify patients with juvenile idiopathic arthritis and track important measures that aide in improving patient care and performance outcomes. From 2019 to 2021, we iteratively modified our outpatient clinic EHR note to include structured data elements to improve longitudinal monitoring. We then validated data transferred to an electronic dashboard external to the EHR and demonstrated utility for identifying an accurate patient population and tracking quality improvement initiatives.
Creation of the structured data elements improved the identification of patients with JIA with >99% accuracy and without requiring manual review of the chart. Using the dashboard to monitor performance, we improved documentation of critical disease activity measures that resulted in improvement in those scores across the local population of patients with JIA. The structured data elements also enabled us to automate electronic data transfer to a multicenter learning network registry.
The structured data element modifications made to our outpatient EHR note populate a local dashboard that allows real time access to critical information for patient care, population management, and improvement in quality metrics. The collection and monitoring of structured data can be scaled to other quality improvement initiatives in our clinic and shared with other centers.
本报告描述了我们在电子健康记录（EHR）笔记修改以及创建外部仪表盘方面的经验，以建立一个本地学习型健康系统，促进我们儿科风湿病诊所的质量改进和患者护理。
我们应用质量改进方法来开发一个更可靠、准确的系统，以识别幼年特发性关节炎患者，并跟踪有助于改善患者护理和绩效结果的重要指标。从2019年到2021年，我们反复修改门诊EHR笔记，纳入结构化数据元素以改善纵向监测。然后，我们验证了传输到EHR外部电子仪表盘的数据，并证明其在识别准确患者群体和跟踪质量改进举措方面的效用。
结构化数据元素的创建提高了幼年特发性关节炎患者识别的准确性，准确率超过99%，且无需人工查阅病历。通过使用仪表盘监测绩效，我们改进了关键疾病活动指标的记录，这使得当地幼年特发性关节炎患者群体的这些指标得分得到改善。结构化数据元素还使我们能够自动将电子数据传输到多中心学习网络登记处。
对我们门诊EHR笔记所做的结构化数据元素修改填充了一个本地仪表盘，该仪表盘允许实时获取用于患者护理、群体管理和质量指标改进的关键信息。结构化数据的收集和监测可以扩展到我们诊所的其他质量改进举措，并与其他中心共享。
