The Medicines Intelligence (MedIntel) Data Platform is an anonymised enduring data platform, established to undertake population-based studies examining the use, safety and (cost)effectiveness of prescribed medicines. 

Population spine

The MedIntel Data Platform cohort comprises 7.4 million unique Medicare-eligible persons (ascertained from the Medicare Consumer Directory) who were aged ≥18 years and resided in NSW at any time from 1 January 2005 until 31 December 2020. The cohort will be updated annually. 

Linkage and data collections

The Australian Institute of Health and Welfare (AIHW) and the NSW Centre for Health Record Linkage (CHeReL) undertook the linkage using best practice privacy preserving protocols.  The content data comprised Commonwealth and New South Wales routinely collected health data (see list below).

  • Pharmaceutical Benefits Scheme (2002-2022)
  • Medicare Benefits Schedule (2002-2022)
  • Herceptin Program (2001-2015)
  • National Death Index - Fact of death (2002-2022)
  • National Death Index - Cause of Death (2002-2020)
  • NSW Admitted Patient Data Collection (2002-2022)
  • NSW Emergency Department Data Collection (2005-2022)
  • NSW Cancer Registry (1972 – 2019)


This research program has ethical approval from: (1) AIHW Human Research Ethics Committee (AIHW HREC) (approval number EO2021/1/1233); (2) NSW Population and Health Services Research Ethics Committee (PHSREC) (approval number 2020/ETH02273). Individual research projects conducted under this ethical approval require the submission of an amendment to the PHSREC along with an AIHW s29 form, for each person requiring data access, prior to commencement (approval within 4-8 weeks).  

Data storage

The data are housed in the Secure Unified Research Environment (SURE), managed by the Sax Institute. SURE is a safe setting offering data controls meeting the highest data governance and security requirements. Housing the data in SURE adheres to the Five Safes framework—safe people, projects, settings and outputs. All access and data analyses are via the SURE.

If you wish to access the MedIntel Data Platform you will need to work with the MedIntel team to: 

  1. Discuss project feasibility and alignment with the HREC approval; 
  2. Submit a one-page Expression of Interest using a standard template;
  3. Agree on project resourcing and costs; 
  4. Submit a PHSREC (and AIHW s29) ethics amendment using a standard template;
  5. Apply for a SURE workspace and complete SURE training. 

Contact details:

For all inquiries, documentation and templates please contact the Data Manager, Medicines Intelligence Research Program, Melisa Litchfield.


The establishment of the MedIntel Data Platform was funded by the UNSW Research Infrastructure Scheme and the NHMRC Centre of Research Excellence in Medicines Intelligence.

Costing Model

Please contact the Data Manager, Medicines Intelligence Research Program, Melisa Litchfield.


See details below of publications from research projects using the MedIntel Data Platform.

  • Summary

    The Medicines Intelligence (MedIntel) Data Platform is a new linked data resource established to generate evidence on prescribed medicine use, safety, costs, and cost-effectiveness in Australia. It adheres to best practice privacy principles, with no identifying information available to researchers. The platform comprises Medicare-eligible people who are ≥18 years and residing in New South Wales (NSW), Australia, any time during 2005-2020, with linked data on dispensed prescription medicines, Medicare services, emergency department visits, hospitalisations, cancer notifications, and deaths. In total, the platform includes 7.4 million unique people across all years, covering 36.9% of the Australian adult population. As of 1 January 2019 (the last pre-pandemic year), the cohort had a mean age of 48.7 years (51.1% female), with most people (4.4M, 74.7%) residing in a major city. In 2019, 4.4M people (73.3%) were dispensed a medicine (most commonly anti-infective, nervous system, and cardiovascular medicines), 1.2M (20.5%) were hospitalised, 5.3M (89.4%) had a GP or specialist appointment, and 54 003 people died. Data are available until 2022 with approval for annual updates. This platform creates opportunities for national and international research collaborations and enables us to address important questions about quality use of medicines and health outcomes.


    Helga Zoega, Michael O Falster, Malcolm B Gillies, Melisa Litchfield, Ximena Camacho, Claudia Bruno, Benjamin Daniels, Natasha Donnolley, Alys Havard, Andrea L Schaffer, Georgina Chambers, Louisa Degenhardt, Timothy Dobbins, Natasa Gisev, Rebecca Ivers, Louisa Jorm, Bette Liu, Claire M Vajdic, Sallie-Anne Pearson. The Medicines Intelligence Data Platform: A population-based data resource from New South Wales, Australia. medRxiv 2024.04.29.24306520; doi:  

  • Summary

    In our study, we looked at the use of new medicines for Type 2 diabetes: SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP-1RAs) in New South Wales. These medicines, taken with traditional diabetes medicines significantly improve blood sugar levels, and reduce the risk of heart and kidney disease. We found only half of patients who were using traditional diabetes medicines also used SGLT2is, and approximately 15% used GLP-1RAs. Importantly, patterns of use varied depending on where people lived. SGLT2is were less commonly used in regions where people have lower incomes and poorer health. One area in north-east NSW showed higher GLP-1RA use than other regions. To increase the use of these highly effective medicines, we recommend lowering costs to patients, changing restrictions on who is eligible to access them, and educating care providers about their benefits for patients. Monitoring medicine use by where people live allows us to focus interventions in specific locations to maximise use in people who will benefit the most. For researchers, our findings highlight the importance of considering local prescribing patterns when exploring medicine use across geographies (e.g. urban and regional area) - as these can overshadow any broader trends observed.

    de Oliveira Costa, J., Lin, J., Milder, T. Y., Greenfield, J. R., Day, R. O., Stocker, S. L., Neuen, B. L., Havard, A., Pearson, S. A., & Falster, M. O. (2024). Geographic variation in sodium-glucose cotransporter 2 inhibitor and glucagon-like peptide-1 receptor agonist use in people with type 2 diabetes in New South Wales, Australia. Diabetes Obes Metab. 

  • Summary

    Prescription medicines for strong pain relief known as opioids, such as oxycodone, morphine, or tramadol, are an important tool for reducing moderate to severe pain in the short-term and are often prescribed when patients have been discharged from a hospital or Emergency Department visit. However, they also have significant side effects, particularly when used for a long time. Until recently, Australia’s use of prescription opioids was increasing, and with it worries about dependence, overdose and death. Because of this, we were interested in looking at how often people continue using these medicines in NSW long-term (more than 90 days) after leaving hospital.

    Our study was the first whole-of-population Australian study to estimate long-term opioid use following Emergency Department presentations and hospital admissions. The study used non-identifiable health data to follow all hospitalisations and Emergency Department visits in NSW between 2014-2020. We found that during this period, the overall number of people starting opioids for the first time decreased by 16%, from 8.7% to 7.2% of hospital/Emergency Department visits. Long-term opioid use decreased by 33%, from 1.3% to 0.8%.

    Other important findings were about the use of these painkillers after visiting a hospital for different reasons. For example, the study found that one in four people admitted for traumatic injuries, like a physical injury or road accident, started an opioid and 2.3% of them went on to long-term use. This rate of long-term use is somewhat lower than reported in previous Australian research. We also found one in 15 people attending an ED started an opioid and only 1.0% of them went on to long-term use - lower than estimates from the US. 

    Insights from such large studies like ours inform opioid prescribing policies in hospitals and promote quality prescribing practices. 

    Gillies MB, Chidwick K, Bharat C, Camacho X, Currow D, Gisev N, Degenhardt L, Pearson, S-A. Long-term prescribed opioid use after hospitalization or emergency department presentation among opioid naïve adults (2014–2020)—A population-based descriptive cohort study. Br J Clin Pharmacol. 2024; 1-13. doi: