Isabelle Mark, Ip Ivan K, Bakhtin Michael, Schneider Louise, Raja Ali S, Dutta Sayon, Landman Adam, Lacson Ronilda
Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA 02120, United States.
Covenant Health, Inc, Tewksbury, MA, 01876, United States.
JAMIA Open. 2025 Jul 30;8(4):ooaf085. doi: 10.1093/jamiaopen/ooaf085. eCollection 2025 Aug.
To evaluate clinical decision support (CDS) of varying complexities and care settings represented using Health Information Technology (HIT) standards-Clinical Quality Language (CQL) for representing clinical logic and Fast Healthcare Interoperability Resources (FHIR) for health information exchange.
This Institutional Review Board-approved, retrospective study was performed at an academic medical center (January 1, 2023-December 31, 2023). Recommendations extracted from patient-centered outcomes guidelines were translated into standardized syntax (SNOMED CT) and representations (CQL, FHIR). Clinical decision support Hooks applications were developed for: CDS1-provides education for emergency department (ED) patients with venous thromboembolism; CDS2-recommends CT pulmonary angiogram in ED patients with suspected pulmonary embolism (PE) and uses FHIR Questionnaire resources for representing interactive content; CDS3-recommends mammography/breast magnetic resonance imaging surveillance in outpatients with breast cancer history. We randomly selected 50 ED patients with suspected PE and 50 outpatients undergoing breast imaging surveillance. We compared outcomes of false-positive alerts and the accuracy of CDS1, the more complex CDS2, and CDS3 for outpatients.
Clinical decision support Hooks applications used CQL logic for trigger expressions and logic files and provided recommendations to ED and outpatient providers. CDS1 had a false-positive alert and accuracy of 11.1% and 98%, respectively, not significantly different from CDS2 (0.0% false-positive alerts, = .33 and 96% accuracy, = .56) or from CDS3 (0.0% false-positive alerts, = .15 and 100% accuracy, = .31).
Health Information Technology standards can represent recommendations of varying complexities in various care settings.
The potential to represent CDS using standardized syntax and formats can help facilitate the dissemination of CDS-consumable artifacts.
使用健康信息技术(HIT)标准——用于表示临床逻辑的临床质量语言(CQL)和用于健康信息交换的快速医疗互操作性资源(FHIR),评估不同复杂程度和护理环境下的临床决策支持(CDS)。
这项经机构审查委员会批准的回顾性研究在一家学术医疗中心进行(2023年1月1日至2023年12月31日)。从以患者为中心的结局指南中提取的建议被转化为标准化语法(SNOMED CT)和表示形式(CQL、FHIR)。开发了临床决策支持挂钩应用程序用于:CDS1——为急诊科(ED)静脉血栓栓塞患者提供教育;CDS2——为疑似肺栓塞(PE)的急诊科患者推荐CT肺动脉造影,并使用FHIR问卷资源表示交互式内容;CDS3——为有乳腺癌病史的门诊患者推荐乳房X线摄影/乳腺磁共振成像监测。我们随机选择了50例疑似PE的急诊科患者和50例接受乳房成像监测的门诊患者。我们比较了假阳性警报的结果以及CDS1、更复杂的CDS2和门诊患者的CDS3的准确性。
临床决策支持挂钩应用程序使用CQL逻辑进行触发表达式和逻辑文件,并向急诊科和门诊提供者提供建议。CDS1的假阳性警报率和准确率分别为11.1%和98%,与CDS2(假阳性警报率0.0%,P = 0.33,准确率96%,P = 0.56)或CDS3(假阳性警报率0.0%,P = 0.15,准确率100%,P = 0.31)无显著差异。
健康信息技术标准可以在各种护理环境中表示不同复杂程度的建议。
使用标准化语法和格式表示CDS的潜力有助于促进CDS可消费工件的传播。