Center for Advanced Evidence Generation, Real-World & Analytic Solutions, IQVIA, Cambridge, Massachusetts.
Center for Advanced Evidence Generation, Real-World & Analytic Solutions, IQVIA, Research Triangle Park, North Carolina.
Sports Health. 2019 Sep/Oct;11(5):440-445. doi: 10.1177/1941738119854759. Epub 2019 Jul 2.
"Research-ready" evidence platforms that link sports data with anonymized electronic health records (EHRs) or other data are important tools for evaluating injury occurrence in response to changes in games, training, rules, and other factors. While there is agreement that high-quality data are essential, there is little evidence to guide data curation.
We hypothesized that an EHR used in the course of clinical care and curated for research readiness can provide a robust evidence platform. Our purpose was to describe the data curation used for active injury surveillance by the National Football League (NFL).
Dynamic cohort study.
Level 2.
Players provide informed consent for research activities through the collective bargaining process. A league-wide EHR is used to record injuries that come to the attention of the teams' athletic trainers and physicians, NFL medical spotters, or unaffiliated neurotrauma consultants. Information about football activities and injuries are linkable by player, setting, and event to other sports-related data, including game statistics and game-day stadium quality measures, using a unique player identification designed to protect player privacy. Ongoing data curation is used to review data completeness and accuracy and is adjusted over time in response to findings.
The core data curation activities include monthly injury summaries to team staff, queries to resolve incomplete reporting, and periodic external checks. Experiences derived from producing more than 100 reports per year on diverse topics are used to update coding training and related guidance documents in response to missing data or inconsistent coding that is observed. Roughly 20% more injuries were recorded for the same "reportable" injuries after switching from targeted reporting to an EHR.
Research-ready databases need systematic curation for quality and completeness, along with related action plans. More injuries were reported through EHR than through targeted reporting.
Evidence-driven decision-making thrives on reliable data fine-tuned through systematic use, review, and ongoing adjustments to the curation process.
将运动数据与匿名电子健康记录（EHR）或其他数据相链接的“研究就绪”证据平台是评估比赛、训练、规则和其他因素变化引起的伤害发生情况的重要工具。尽管人们一致认为高质量的数据至关重要，但几乎没有证据可以指导数据管理。
我们假设在临床护理过程中使用并为研究准备好的 EHR 可以提供一个强大的证据平台。我们的目的是描述国家橄榄球联盟（NFL）主动伤害监测中使用的数据管理。
动态队列研究。
2 级。
球员通过集体谈判过程对研究活动表示同意。联盟范围内的 EHR 用于记录运动员训练员和医生、NFL 医疗观察员或独立神经创伤顾问注意到的伤害。通过使用专门设计用于保护球员隐私的独特球员身份，可将有关足球活动和伤害的信息按球员、设置和事件链接到其他与运动相关的数据，包括比赛统计数据和比赛日体育场质量指标。正在进行的数据管理用于审查数据的完整性和准确性，并根据发现情况进行调整。
核心数据管理活动包括每月向团队工作人员提交伤害总结、查询以解决不完整的报告和定期外部检查。从每年编写关于各种主题的 100 多份报告中获得的经验用于更新编码培训和相关指导文件，以解决缺失数据或观察到的不一致编码问题。从有针对性的报告切换到 EHR 后，记录的相同“可报告”伤害增加了约 20%。
研究就绪的数据库需要系统的管理，以确保质量和完整性，以及相关的行动计划。通过 EHR 报告的伤害比通过有针对性的报告更多。
基于可靠数据的循证决策通过系统使用、审查和对管理过程的持续调整而蓬勃发展。
