Key Clinical Data Elements and Definitions for ACS and CAD

Updated:May 12,2015

What's the Significance of the 2013 ACCF/AHA Key Data Elements and Definitions in Contemporary Cardiac Practice?

Dr. Klein has nothing to disclose.
Pub Date: Tuesday, January 29, 2013
Author: Lloyd W. Klein, MD
Affiliation: Rush Medical College and Advocate Illinois Medical Center, Chicago IL

Article Text

Citation: Cannon CP, Brindis RG, Chaitman BR, Cohen DJ, Cross JT Jr, Drozda JP Jr, Fesmire FM, Fintel DJ, Fonarow GC, Fox KA, Gray DT, Harrington RA, Hicks KA, Hollander JE, Krumholz H, Labarthe DR, Long JB, Mascette AM, Meyer C, Peterson ED, Radford MJ, Roe MT, Richmann JB, Selker HP, Shahian DM, Shaw RE, Sprenger S, Swor R, Underberg JA, Van de Werf F, Weiner BH, Weintraub WS. 2013 ACCF/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes and coronary artery disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Acute Coronary Syndromes and Coronary Artery Disease Clinical Data Standards). Circulation. 2013: published online before print January 28, 2013, 10.1161/CIR.0b013e3182831a11.




A cynic might suspect that the clinician perusing the subject of this commentary will rapidly conclude that its subject is safely ignored, and presume it to be a tedious collection of words irrelevant to clinical practice. In reality, this is an essential document that sets the standard for what data are collected, how commonly used terms should be defined, which outcomes are assessed, and ultimately how quality is measured, in the setting of acute coronary syndromes (ACS). In a brave new world of electronic health records (EHR) and administrative and professional databases, it is critical to facilitate clear communication among the various stakeholders and assure the accurate interchange of data and information. It is of no benefit to anyone if the physicians managing the patient and the administrative personnel assessing a system-wide approach are not communicating. The purpose of these newly published data elements and definitions is to ensure that everyone is on the same page: no small task in an increasingly complex and electronic healthcare arena.

For these reasons, every cardiologist should be thoroughly familiar with the information in this publication. These standard terms should be used by all clinicians in all EHR systems exactly as defined when documenting the evaluation and follow-up of patients with ACS. Utilizing a common language for describing the evaluation, treatment and outcomes of ACS patients improves our comprehension of clinical trial results and registries, eases the evaluation of clinical performance measures, and focuses our efforts in improving quality-of-care. 

Clinical data standards are sets of standardized elements and related definitions collected in a reference structure. The expert authors selected and defined these particular data elements because they represent a critical demographic or clinical presentation variable, describe an implanted device or treatment modality, and/or are included in standard models of risk or outcome, or other form of quality reporting. They include basic demographic and clinical definitions pertaining to ACS diagnosis and management. A number of these definitions parallel those used in clinical trials, and many of the outcome elements have been validated by national and regional registries. Some of these elements may be combined to provide risk scores that assist in clinical decision-making.

The article is organized in tabular form to simplify its use as a working, everyday tool. Each element is followed by its definition. The accompanying text is spare; the point is an explanation of why the included elements were collected. The structure of the element set is based on classification into useable domains: demographics, medical history, presentation, diagnostic and therapeutic procedures and medications, and outcomes. No risk scores are included, as these can be derived from the included elements.

Special attention is given to variables predictive of outcomes, including laboratory results and clinical presentation. The latter information is particularly valuable clinically, since these are inherently subjective in nature. Objectifying these findings is an especially important contribution. Specific diagnostic criteria for myocardial infarction by cardiac enzymes are not included, as this is covered by the Universal Definition. However, table 7 goes into some detail as to classification of late enzyme elevation and chest pain post infarction. These are problematic diagnoses as they often carry connotations of procedural complications or missed diagnosis, when in fact they are often observed within the natural history of ACS. These are among the most useful new elements since the 2011 edition.

For clinical investigators, quality assurance personnel, and research nurses, this document is mandatory. For clinical cardiologists, the latest terminology and methods may seem obvious at first glance, but the most sophisticated practitioner will discover better ways of communicating and describing situations of ambiguity, and will find that the clarification that accompanies precise classification improves one’s clinical approach. Moreover, accurate identification of the evolving myocardial infarction patient or the high/intermediate risk patient leading to the implementation of the appropriate management pathway impacts favorably on the patient's outcome. Additionally, the development and utilization of clinical practice guidelines and appropriate use criteria requires standard terminology.

The significant challenge on the horizon is to incorporate these elements into EHR and clinical management tools, thus allowing data collection to seamlessly correspond with clinical care. The uniform electronic collection of standardized ACS data is the shared dream. This set of elements and definitions constitute a clinical data standard, and represents a necessary step in the development of a truly universal system that streamlines the medical records process by creating a common structure.

Additionally, it is hoped that these elements prove useful within the everyday clinical environment. Risk stratification correctly focuses on the characteristics early in the admission that drive the choice of time and resource dependent treatments. However, the seasoned clinician recognizes that the diagnostic classification of patients often evolves during the hospital admission when further clinical data or recurrent events, such as in-hospital myocardical infarction, emerge. Retrospective professional critiques of management based on discharge diagnoses that were not evident on presentation lead to unproductive discussion and action. It is a fundamental requirement of accurate quality assurance that these complexities are built into the fabric of system evaluation and not merely passed off as outliers. Without a common language, how can one hope to have a meaningful discussion of the implications of these realities with other physicians and administrators?

These data standards are the foundation of the future. When physician report cards, third party assessments of hospital and physician quality, ties between outcomes and reimbursement, and the public reporting of outcomes become a reality, who will define what is quality practice? And, on what basis? It is obligatory that cardiologists lead the process of developing the most rigorous and accurate means to measure quality, develop tools for quality assurance and support improvement initiatives through standardized assessment of risk, risk adjustment, clinical process and outcome.

-- The opinions expressed in this commentary are not necessarily those of the editors or of the American Heart Association --


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