Types of data

What types of data can be linked?

Any data can be linked with the appropriate linkage variables such as name, address, date of birth and sex.  The types of data most commonly linked for health and health-related research include:

Administrative data

Clinical data

Clinical registry data

Project-specific data

Administrative data

Administrative data is information that is collected as part of service delivery. The collection of this information, or data, is generally required or authorised by law and therefore includes the entire population accessing the service.  Administrative data is less detailed than the service records generally collected and maintained by individual service providers.

Examples

Birth records, hospital admission data, prescription data, medical benefits data, aged care data, disability, child development, child protection, justice (including courts and police. 

Key features

  • Collected during service delivery
  • Mandated reporting requirements typically allow this data to be collected without patient consent 
  • Collection by government generally required or authorised by law 
  • Used by government departments for planning, monitoring, and funding
  • Population level coverage
  • Availability of historical data

“Very important research can be conducted with data collected for purposes other than research.”
Adams C, Allen J, Flack F. Sharing linked data for health research: toward better decision making. Cambridge University Press; 2022 Jun 9

Note: As administrative data are not primarily collected for research purposes, administrative datasets may contain inconsistent, inaccurate, or incomplete data that vary in structure, format, and content.

Clinical data

Clinical data includes detailed patient records collected and used by health professionals during the provision of patient care. 

Examples

Medical notes, pathology results, imaging – for example, X-ray, CT scans – and other health test results

Key features

  • Collected during service delivery  
  • Collected either directly from the patient or with their explicit knowledge and consent 
  • Used by health professionals for the provision of clinical care

Clinical registry data

Clinical registries systematically collect health-related information, within an overall governance and management structure, on individuals who are:

  • Treated with a particular device, drug or surgical procedure (eg. joint replacement)
  • Diagnosed with a particular illness (eg. stroke) or
  • Managed via a specific healthcare resource (eg. treated in an intensive care unit).

Note that a clinical quality registry (CQR) includes patient data and service information collected and used for the purpose of measuring the quality of healthcare.

Examples

Australian Stroke Clinical Registry, The Australia New Zealand Trauma Registry, Australia and New Zealand Dialysis and Transplant Registry (ANZDATA).

Key features

  • Databases that may be disease, health services, or product specific
  • Clinical information collected for a specific area of interest 
  • May support a variety of research questions depending on the depth of clinical detail captured 

Project-specific data

Governments and other entities such as research organisations may collect information from time to time for a particular purpose, such as a survey of health behaviours or a specific research project.

Key features

  • Collected for research
  • Collected with participant consent 
  • Sometimes includes consent for access to other information 
  • Used for research or a specific purpose which is neither administrative nor clinical

Routinely linked datasets

Datasets are often characterised by whether they are routinely linked.

Routine linkage

This occurs where governance approvals allow a Data Linkage Unit (DLU) to routinely link a data collection at an agreed frequency (e.g. monthly).

  • Links can be reused for subsequent projects

Ad hoc linkage

This occurs where datasets are linked on a project-by-project basis.

  • Linked on request
  • Not routinely linked within the jurisdiction by the Data Linkage Unit
  • Links cannot be reused for a new project

Examples of routinely linked datasets

These datasets can be linked within and across jurisdictions.

Linked data assets

Linked data assets (or systems) integrate routinely linked datasets, making it easier for researchers to conduct complex cross-sector and cross-jurisdictional research.

The PHRN supported the development of linked data assets including the National Health Data Hub (NHDH), the National Disability Data Asset (NDDA) and the COVID-19 Register.

Metadata Platform

Explore datasets and linked data assets in our Metadata Platform.