Key data elements for clinical management and outcomes of patients with coronary artery disease: definitions from Coronary Artery Disease and Creative Antithrombotic Clinical Research Collaboration (CardiaCare) / 中华心血管病杂志

ABSTRACT

Objective: To develop a set of data elements and standardized definitions of Coronary Artery Disease and Creative Antithrombotic Clinical Research Collaboration (CardiaCare), aiming to facilitate the exchange of disparate data sources, enhance the abilities to support multicenter researches, and subsequently ensure the databases use under standardized process and criteria. Methods: The Cardiacare writing committee members reviewed data elements and definitions from published guidelines, clinical trials, databases, and standardized documents, then determined the data elements and standardized definitions, which should be included in CardiaCare. The writing committee also considered the specific domestic clinical management strategies during the establishment of Cardiacare. The resulting documents provide a series of key data elements and standardized definitions used in the management of coronary artery disease patients. Key data elements from CardiaCare could be sorted by clinical management flowsheet and outcome from hospitalization to long-term follow-up. Results: The Cardiacare standardized set comprised 864 data elements from admission to post-hospital follow-up visit. There were 8 tables in the documents, including demographic and admission information (23 elements), medical history and risk factors (102 elements), clinical presentations and diagnosis (22 elements), diagnostic and laboratory tests (111 elements), interventional diagnosis and treatment (118 elements), pharmacological therapy (213 elements), clinical outcomes (161 elements), and special subpopulations (114 elements 87 elements for transcatheter valve replacement and 27 elements with cardiac rehabilitation). Conclusions: The Cardiacare standardized data elements set could provide support for real-world clinical research in consecutive data collection and databases mining. A wider applicability in various settings of CardiaCare needs to be explored further.