Pathways to Real World Evidence From the Real World of School-Based Physical Fitness Testing (SB-PFT)

IF 2.3 Q2 HEALTH POLICY & SERVICES
Anita Walden, Allen Yiu, Gregory Welk, Yawen Guo, Shlomit Radom-Aizik, Margaret Schneider, Allyson Reeds, AbdulMalik Shakir, Dan M. Cooper
{"title":"Pathways to Real World Evidence From the Real World of School-Based Physical Fitness Testing (SB-PFT)","authors":"Anita Walden,&nbsp;Allen Yiu,&nbsp;Gregory Welk,&nbsp;Yawen Guo,&nbsp;Shlomit Radom-Aizik,&nbsp;Margaret Schneider,&nbsp;Allyson Reeds,&nbsp;AbdulMalik Shakir,&nbsp;Dan M. Cooper","doi":"10.1002/lrh2.70108","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Introduction</h3>\n \n <p>Unique challenges of data quality, standardization, and interoperability face non-traditional sources of real world data (RWD), those outside of the common RWD source, the electronic health record (EHR). The experience of our clinical, research, and community group in addressing the endangered school-based physical fitness testing (SB-PFT) data set may be useful as a paradigm for a variety of nontraditional instances of health-related RWD. Until recently, SB-PFT was mandated annually within public schools in ~60% of U.S. children and adolescents representing one of the most robust and inclusive data sets available in youth. When implemented rigorously, SB-PFT produced data that improved pediatric health and student learning. Driven by perceived and real gaps in data quality, inconsistent and insensitive school-site implementation, and uneven evidence for health-relevance, calls for revamping (and, in some cases, ending) school testing are growing.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>To preserve and enhance this unique resource, SB-PFT must incorporate emerging science and technology. We describe here the rationale, structure, and process involved in our building an HL7-associated Domain Analysis Model for SB-PFT. Our team consisted of clinicians, exercise scientists, school personnel, publish health officials, parents and students. The structure of the DAM was facilitated by data standard experts and skilled Unified Modeling Language professionals. Administrative support was rendered by our institution's NIH-funded Clinical Translational Science Award.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The DAM will serve as a necessary first step in integrating Fast Healthcare Interoperability Resources (FHIR) and Learning Health Systems (LHS) models essential to realize the full potential of SB-PFT data in advancing child health.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>The experience presented here can serve as a roadmap for addressing critical issues of data standardization and RWE generation in nontraditional instances of RWD. The DAM can be deployed in SB-PFT data exchange in real world settings.</p>\n </section>\n </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 3","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2026-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13402859/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/lrh2.70108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction

Unique challenges of data quality, standardization, and interoperability face non-traditional sources of real world data (RWD), those outside of the common RWD source, the electronic health record (EHR). The experience of our clinical, research, and community group in addressing the endangered school-based physical fitness testing (SB-PFT) data set may be useful as a paradigm for a variety of nontraditional instances of health-related RWD. Until recently, SB-PFT was mandated annually within public schools in ~60% of U.S. children and adolescents representing one of the most robust and inclusive data sets available in youth. When implemented rigorously, SB-PFT produced data that improved pediatric health and student learning. Driven by perceived and real gaps in data quality, inconsistent and insensitive school-site implementation, and uneven evidence for health-relevance, calls for revamping (and, in some cases, ending) school testing are growing.

Methods

To preserve and enhance this unique resource, SB-PFT must incorporate emerging science and technology. We describe here the rationale, structure, and process involved in our building an HL7-associated Domain Analysis Model for SB-PFT. Our team consisted of clinicians, exercise scientists, school personnel, publish health officials, parents and students. The structure of the DAM was facilitated by data standard experts and skilled Unified Modeling Language professionals. Administrative support was rendered by our institution's NIH-funded Clinical Translational Science Award.

Results

The DAM will serve as a necessary first step in integrating Fast Healthcare Interoperability Resources (FHIR) and Learning Health Systems (LHS) models essential to realize the full potential of SB-PFT data in advancing child health.

Conclusion

The experience presented here can serve as a roadmap for addressing critical issues of data standardization and RWE generation in nontraditional instances of RWD. The DAM can be deployed in SB-PFT data exchange in real world settings.

Abstract Image

从校本体能测试(SB-PFT)的真实世界中获得真实世界证据的途径。
简介:非传统的真实世界数据(RWD)来源面临着数据质量、标准化和互操作性方面的独特挑战,这些非传统的真实世界数据(RWD)来源是电子健康记录(EHR)。我们的临床、研究和社区小组在处理濒危的基于学校的身体健康测试(SB-PFT)数据集方面的经验可能对各种非传统的健康相关RWD实例有用。直到最近,每年约有60%的美国儿童和青少年在公立学校被强制要求进行SB-PFT,这代表了青少年中最可靠和最具包容性的数据集之一。当严格实施时,SB-PFT产生的数据改善了儿科健康和学生的学习。由于数据质量存在明显差距和实际差距,学校现场实施不一致和不敏感,以及与健康相关的证据不均衡,要求改革(在某些情况下甚至终止)学校考试的呼声越来越高。方法:为了保护和增强这种独特的资源,SB-PFT必须结合新兴的科学和技术。我们在这里描述了为SB-PFT构建hl7相关领域分析模型所涉及的基本原理、结构和过程。我们的团队由临床医生、运动科学家、学校工作人员、出版卫生官员、家长和学生组成。数据标准专家和熟练的统一建模语言专业人员促进了DAM的结构。行政上的支持是由我们机构的nih资助的临床转化科学奖提供的。结果:DAM将作为整合快速医疗互操作性资源(FHIR)和学习健康系统(LHS)模型的必要的第一步,这些模型对于实现SB-PFT数据在促进儿童健康方面的全部潜力至关重要。结论:本文介绍的经验可以作为解决非传统RWD实例中数据标准化和RWE生成关键问题的路线图。DAM可以部署在实际环境中的SB-PFT数据交换中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书