This Acute Coronary Syndrome (ACS) data set specification is not mandated for collection but is recommended as best practice if ACS data are to be collected. This data set specification enables individual hospitals or health service areas to develop collection methods and policies appropriate for their service.
The scope for the ACS data set specification is to collect data on the period between when a person with ACS symptoms was first referred to a hospital or directly presented at a hospital, and when a person leaves the hospital, either from the emergency department or is discharged from the hospital. Some of the data relevant to the management of patients attending hospital with ACS symptoms is specified for collection at follow-up visits with a specialist or as a non-admitted patient.
Acute coronary syndromes reflect the spectrum of coronary artery disease resulting in acute myocardial ischaemia, and span unstable angina, non-ST segment elevation myocardial infarction (NSTEMI) and ST-segment elevation myocardial infarction (STEMI). Clinically these diagnoses encompass a wide variation in risk, require complex and time urgent risk stratification and represent a large social and economic burden.
The definitions used in this data set specification are designed to underpin the data collected by health professionals in their day-to-day acute care practice. They relate to the realities of an acute clinical consultation for patients presenting with chest pain/ discomfort and the need to correctly identify, evaluate and manage patients at increased risk of a coronary event.
The data elements specified in this metadata set provide a framework for:
promoting the delivery of evidenced-based acute coronary syndrome management care to patients;
facilitating the ongoing improvement in the quality and safety of acute coronary syndrome management in acute care settings in Australia and New Zealand;
improving the epidemiological and public health understanding of this syndrome; and
supporting acute care services as they develop information systems to complement the above.
This is particularly important as the scientific evidence supporting the development of the data elements within the ACS data set specification indicate that accurate identification of the evolving myocardial infarction patient or the high/intermediate risk patient leading to the implementation of the appropriate management pathway impacts on the patient's outcome. Having a nationally recognised set of definitions in relation to defining a patient's diagnosis, risk status and outcomes is a prerequisite to achieving the above aims.
The ACS data set specification is based on the American College of Cardiology (ACC) Data Set for Acute Coronary Syndrome as published in the Journal of the American College of Cardiology in December 2001 (38:2114-30) as well as more recent scientific evidence around the diagnosis of myocardial infarction presented in the National Heart Foundation of Australia/Cardiac Society of Australia and New Zealand Guidelines for the management of acute coronary syndromes (MJA 2006;184;S1-S32). The data elements are alphabetically listed and grouped in a similar manner to the American College of Cardiology's data set format. These features of the Australian ACS data set should ensure that the data is internationally comparable.
Many of the data elements in this data set specification may also be used in the collection of other cardiovascular clinical information.
Where appropriate, it may be useful if the data definitions in this data set specification were also used to address data definition needs in non-clinical environments such as public health surveys etc. This could allow for qualitative comparisons between data collected in, and aggregated from, clinical settings (i.e. using application of the ACS data set specification), with that collected through other means (e.g. public health surveys, reports).
A set of ACS data elements and standardised definitions can inform the development and conduct of future registries at both the national and local level.
The working group formed under the National Heart Foundation of Australia (Heart Foundation) and the Cardiac Society of Australia and New Zealand (CSANZ) initiative was diverse and included representation from the following organisations: the Heart Foundation, the CSANZ, the Australasian College of Emergency Medicine, the Australian Institute of Health and Welfare, the Australasian Society of Cardiac & Thoracic Surgeons, Royal Australian College of Physicians (RACP), RACP - Towards a Safer Culture, National Centre for Classification in Health (Brisbane), the NSW Aboriginal Health & Medical Research Council, the George Institute for International Health, the School of Population Health at the University of Western Australia and the National Cardiovascular Monitoring System Advisory Committee.
To ensure the broad acceptance of the data set specification, the working group also sought consultation from the heads of cardiology departments, other specialist professional bodies and regional key opinion leaders in the field of acute coronary syndromes.
Collection and usage attributes
Guide for use:
There are six data clusters in the Acute Coronary Syndrome (Clinical) DSS. To ensure a complete description of the clinical management of acute coronary syndromes (ACS) it is recommended that all clusters be collected along with the individual data elements during the current ACS event by the individual hospital or health service area.
The six data clusters in this DSS include:
Acute coronary syndrome clinical event cluster
Functional stress test cluster
Ventricular ejection fraction cluster
Acute coronary syndrome pharmacotherapy cluster
Coronary artery cluster
This data set specification is primarily concerned with the clinical use of ACS-Data. Acute care environments such as hospital emergency departments, coronary care units or similar acute care areas are the settings in which implementation of the core ACS data set specification should be considered. A wider range of health and health related establishments that create, use or maintain, records on health care clients, could also use it.