Dolin Gay, Saitwal Himali, Bertodatti Karen, Mueller Savanah, Bierman Arlene S, Suls Jerry, Brandt Katie, Camara Djibril S, Leppry Stephanie, Jones Emma, Gallego Evelyn, Carlson Dave, Norton Jenna
Namaste Informatics, Gold Hill, OR 97525, United States.
EMI Advisors, Sugar Land, TX 77479, United States.
JAMIA Open. 2024 Sep 11;7(3):ooae095. doi: 10.1093/jamiaopen/ooae095. eCollection 2024 Oct.
The Multiple Chronic Conditions (MCCs) Electronic Care (e-Care) Plan project aims to establish care planning data standards for individuals living with MCCs. This article reports on the portion of the project focused on long COVID and presents the process of identifying and modeling data elements using the HL7 Fast Healthcare Interoperability Resources (FHIR) standard.
Critical data elements for managing long COVID were defined through a consensus-driven approach involving a Technical Expert Panel (TEP). This involved 2 stages: identifying data concepts and establishing electronic exchange standards.
The TEP-identified and -approved long COVID data elements were mapped to the HL7 US Core FHIR profiles for syntactic representation, and value sets from standard code systems were developed for semantic representation of the long COVID concepts.
Establishing common long COVID data standards through this process, and representing them with the HL7 FHIR standard, facilitates interoperable data collection, benefiting care delivery and patient-centered outcomes research (PCOR) for long COVID. These standards may support initiatives including clinical and pragmatic trials, quality improvement, epidemiologic research, and clinical and social interventions.By building standards-based data collection, this effort accelerates the development of evidence to better understand and deliver effective long COVID interventions and patient and caregiver priorities within the context of MCCs and to advance the delivery of coordinated, person-centered care.
The open, collaborative, and consensus-based approach used in this project will enable the sharing of long COVID-related health concerns, interventions, and outcomes for patient-centered care coordination across diverse clinical settings and will facilitate the use of real-world data for long COVID research.
多重慢性病(MCCs)电子护理(e-Care)计划项目旨在为患有MCCs的个体建立护理计划数据标准。本文报告了该项目中专注于新冠后长期症状的部分内容,并介绍了使用HL7快速医疗保健互操作性资源(FHIR)标准识别和建模数据元素的过程。
通过由技术专家小组(TEP)参与的共识驱动方法,确定了管理新冠后长期症状的关键数据元素。这包括两个阶段:识别数据概念和建立电子交换标准。
TEP识别并批准的新冠后长期症状数据元素被映射到HL7美国核心FHIR配置文件以进行句法表示,并开发了来自标准代码系统的值集以进行新冠后长期症状概念的语义表示。
通过此过程建立通用的新冠后长期症状数据标准,并用HL7 FHIR标准表示这些标准,有助于实现可互操作的数据收集,有利于新冠后长期症状的护理提供和以患者为中心的结局研究(PCOR)。这些标准可能支持包括临床和实用试验、质量改进、流行病学研究以及临床和社会干预在内的举措。通过建立基于标准的数据收集,这项工作加快了证据的开发,以更好地理解和提供有效的新冠后长期症状干预措施,以及在MCCs背景下患者和护理人员的优先事项,并推进提供协调的、以患者为中心的护理。
本项目采用的开放、协作和基于共识的方法将能够在不同临床环境中共享与新冠后长期症状相关的健康问题、干预措施和结局,以进行以患者为中心的护理协调,并将促进在新冠后长期症状研究中使用真实世界数据。