“A Road Map to Creating a High-Quality Clinical Database in Plastic Surgery”

数据库 医学 质量保证 数据质量 数据收集 质量(理念) 数据完整性 计算机科学 运营管理 工程类 病理 公制(单位) 哲学 统计 外部质量评估 数学 认识论
作者
Zhazira Irgebay,Madeleine K. Bruce,Jennifer A. Fantuzzo,Justin Beiriger,Erin Anstadt,Lucas A. Dvoracek,John Smetona,Joseph E. Losee,Jesse A. Goldstein
出处
期刊:Plastic and Reconstructive Surgery [Lippincott Williams & Wilkins]
卷期号:153 (2): 515-523
标识
DOI:10.1097/prs.0000000000010590
摘要

Background: Detailed in-house databases are a staple of surgical research and a crucial source of data for many studies from which clinical guidelines are built. Despite the importance of generating a clear and thorough developmental design, the literature on database creation and management is limited. In this article, the authors present their stepwise single-institution process of developing a clinical facial fracture database. Methods: The authors outline the process of development of a large single-institution clinical pediatric facial fracture database. The authors highlight critical steps from conception, regulatory approval, data safety/integrity, human resource allocation, data collection, quality assurance, and error remediation. The authors recorded patient characteristics, comorbidities, details of the sustained fracture, associated injuries, hospitalization information, treatments, outcomes, and follow-up information on Research Electronic Data Capture. Protocols were created to ensure data quality assurance and control. Error identification analysis was subsequently performed on the database to evaluate the completeness and accuracy of the data. Results: A total of 4451 records from 3334 patients between 2006 and 2021 were identified and evaluated to generate a clinical database. Overall, there were 259 incorrect entries of 120,177 total entries, yielding a 99.8% completion rate and a 0.216% error rate. Conclusions: The quality of clinical research is intrinsically linked to the quality and accuracy of the data collection. Close attention must be paid to quality control at every stage of a database setup. More studies outlining the process of database design are needed to promote transparent, accurate, and replicable research practices.
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