CentraleSupélec, Laboratoire de Génie Industriel, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.
Department of Medical Oncology, Université Paris Est Créteil, AP-HP, CHU Henri Mondor and Albert Chenevier, 94000 Créteil, France.
J Am Med Inform Assoc. 2024 Nov 1;31(11):2699-2707. doi: 10.1093/jamia/ocae244.
Clinical Data Warehouses (CDW) are the designated infrastructures to enable access and analysis of large quantities of electronic health record data. Building and managing such systems implies extensive "data work" and coordination between multiple stakeholders. Our study focuses on the challenges these stakeholders face when designing, operating, and ensuring the durability of CDWs for research.
We conducted semistructured interviews with 21 professionals working with CDWs from France and Belgium. All interviews were recorded, transcribed verbatim, and coded inductively.
Prompted by the AI boom, healthcare institutions launched initiatives to repurpose data they were generating for care without a clear vision of how to generate value. Difficulties in operating CDWs arose quickly, strengthened by the multiplicity and diversity of stakeholders involved and grand discourses on the possibilities of CDWs, disjointed from their actual capabilities. Without proper management of the information flows, stakeholders struggled to build a shared vision. This was evident in our interviewees' contrasting appreciations of what mattered most to ensure data quality. Participants explained they struggled to manage knowledge inside and across institutions, generating knowledge loss, repeated mistakes, and impeding progress locally and nationally.
Management issues strongly affect the deployment and operation of CDWs. This may stem from a simplistic linear vision of how this type of infrastructure operates. CDWs remain promising for research, and their design, implementation, and operation require careful management if they are to be successful. Building on innovation management, complex systems, and organizational learning knowledge will help.
临床数据仓库 (CDW) 是用于访问和分析大量电子健康记录数据的指定基础架构。构建和管理此类系统意味着需要进行大量的“数据工作”,并需要多个利益相关者之间进行协调。我们的研究重点是这些利益相关者在设计、运营和确保 CDW 可用于研究的持久性方面所面临的挑战。
我们对来自法国和比利时的 21 名从事 CDW 工作的专业人员进行了半结构化访谈。所有访谈均进行了录音、逐字记录,并进行了归纳式编码。
受人工智能热潮的推动,医疗机构启动了重新利用他们为护理生成的数据的举措,但没有明确的愿景来创造价值。运营 CDW 很快就出现了困难,由于涉及的利益相关者的多样性和多样性,以及对 CDW 可能性的宏大论述,与实际能力脱节,这些困难更加严重。由于信息流没有得到适当的管理,利益相关者难以建立共同的愿景。这在我们的受访者对确保数据质量最重要的因素的不同看法中显而易见。参与者解释说,他们努力在机构内部和机构之间管理知识,导致知识流失、重复错误,并阻碍了本地和国家的进展。
管理问题严重影响 CDW 的部署和运营。这可能源于对这种基础设施如何运作的简单线性看法。CDW 仍然对研究具有很大的潜力,如果要成功,它们的设计、实施和运营需要精心管理。借鉴创新管理、复杂系统和组织学习知识将有所帮助。