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Guiding Principles for Data Sharing and Harmonization: Results of a Systematic Review and Modified Delphi From the Society of Critical Care Medicine Data Science Campaign

数据提取 协调 医学 系统回顾 德尔菲法 数据共享 标准化 概念化 医疗保健 梅德林 数据科学 计算机科学 知识管理 政治学 替代医学 病理 人工智能 法学 物理 操作系统 声学
作者
Donna Lee Armaignac,Smith F. Heavner,Michelle Rausen,Xiaohan Tanner Zhang,Tamara Al-Hakim,Yulia Levites Strekalova,Neel Shah,Kenneth E. Remy,Sean T. Manion,Melissa Haendel,Andrew A. Kramer,Elizabeth Scruth,Teresa Rincon,Soojin Park,Laura Evans,Tezcan Ozrazgat‐Baslanti,Vitaly Herasevich,Krzysztof Laudański,David J. Murphy,Heidi J. Engel
出处
期刊:Critical Care Medicine [Lippincott Williams & Wilkins]
被引量:1
标识
DOI:10.1097/ccm.0000000000006578
摘要

Objectives: This study aimed to establish a set of guiding principles for data sharing and harmonization in critical care, focusing on the use of real-world data (RWD) and real-world evidence (RWE) to improve patient outcomes and research efficacy. The principles were developed through a systematic literature review and a modified Delphi process, with the goal of enhancing data accessibility, standardization, and interoperability across critical care settings. Data Sources: Data sources included a comprehensive search of peer-reviewed literature, specifically studies related to the use of RWD and RWE in healthcare, guidelines, best practices, and recommendations on data sharing and harmonization. A total of 8150 articles were initially identified through databases such as MEDLINE and Web of Science, with 257 studies meeting inclusion criteria. Study Selection: Inclusion criteria focused on publications discussing health-related informatics, recommendations for RWD/RWE usage, data sharing, and harmonization principles. Exclusion criteria ruled out non-human studies, case studies, conference abstracts, and articles published before 2013, as well as those not available in English. Data Extraction: From the 257 selected studies, 322 statements were extracted. After removing irrelevant definitions and off-topic content, 232 statements underwent content validation and thematic analysis. These statements were then consolidated into 24 candidate guiding principles after rigorous review and consensus-building among the expert panel. Data Synthesis: A three-phase modified Delphi process was employed, involving a conceptualization group, a review group, and a Delphi group. In phase 1, experts identified key themes and search terms for the systematic review. Phase 2 involved validating and refining the prospective guiding principles, while phase 3 employed a Delphi panel to rate principles on acceptability, importance, and feasibility. This process resulted in 24 guiding principles, with high consensus achieved in rounds 2 and 3 on their relevance and applicability. Conclusions: The systematic review and Delphi process resulted in 24 guiding principles to improve data sharing and harmonization in critical care. These principles address challenges across the data lifecycle, including generation, storage, access, and usage of RWD and RWE. This framework is designed to promote more effective and equitable data practices, with relevance for the development of artificial intelligence-based decision support tools and clinical research. The principles are intended to guide the responsible use of data science in critical care, with emphasis on ethics and equity, while acknowledging the variability of resources across settings.
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