The Burden of Cardiovascular Disease in Aotearoa New Zealand

New Zealand faces a significant challenge from cardiovascular disease (CVD), which accounts for around 11,000 deaths annually and imposes an economic burden of NZ$3.3 billion. Ischemic heart disease remains the leading cause of death, with Māori populations experiencing a CVD burden more than 1.5 times higher than non-Māori, often with earlier onset. These disparities underscore the urgent need for robust research to inform prevention and treatment strategies.

Electronic health records (EHRs) play a pivotal role in addressing this crisis by enabling large-scale, population-level analyses. Recent advancements in data linkage and collection have positioned New Zealand as a leader in leveraging health data for CVD insights.

Evolution of New Zealand's Electronic Health Infrastructure

New Zealand's health data ecosystem has matured over decades, anchored by the National Health Index (NHI), a unique identifier covering approximately 95% of the population. Administrative datasets like the National Minimum Dataset (NMDS) for hospital discharges since 1988 and the Pharmaceutical Collection since 1992 form the backbone, with monthly updates ensuring timeliness.

The upcoming Shared Digital Health Record (SDHR), set to launch mid-2026, promises enhanced interoperability across primary and secondary care, potentially revolutionizing real-time data access for researchers and clinicians alike.

A Groundbreaking New Review on NZ EHR for CVD Research

Published on March 5, 2026, in Clinical Epidemiology, the review "New Zealand Electronic Health Data for Cardiovascular Research: A Review" by researchers including University of Auckland's Rod Jackson, Andrew J Kerr, Susan Wells, and Katrina K Poppe evaluates the scope and utility of these datasets. Led primarily from the School of Population Health at the University of Auckland, with Danish collaborators, it highlights how linked data supports observational studies, pragmatic trials, and risk prediction modeling.

The authors note: "New Zealand’s electronic health data represent a valuable resource for cardiovascular research, with applicability to both observational studies and clinical trials." This work positions NZ data as comparable to Nordic and UK systems, opening doors for international collaborations.Read the full review here.

Core Data Sources Driving Cardiovascular Discoveries

Key administrative sources include the Mortality Collection (near-complete since the 1960s), Laboratory Claims (subsidized tests since 2000), and Virtual Diabetes Register (307,400 patients by 2022). Clinical registries like the Cardiac Inherited Diseases Registry (since 2000) and New Zealand Cardiac Surgery Registry (99% capture) provide granular details on procedures and outcomes.

• National Minimum Dataset (NMDS): Hospital discharges, ICD-10-AM coded, timely for public hospitals.
• Pharmaceutical Collection: >97% linkage for subsidized meds, vital for adherence studies.
• NZDep Index: Socioeconomic deprivation metrics, essential for equity analyses.

These are linked via NHI, enabling comprehensive cohorts for university-led investigations.

PREDICT-CVD: University of Auckland's Flagship Cohort

The PREDICT-CVD cohort, developed by University of Auckland researchers since 2002, auto-enrolls primary care patients using CVD risk assessment software, now exceeding 600,000 individuals—one-third of eligible adults. Integrated with general practice EHRs, it links to national datasets for robust risk equations used in NZ and Australia.

Landmark outputs include sex-specific 5-year CVD risk models validated in 400,000 patients, outperforming international tools for NZ's diverse population.Explore related registries. For academics, PREDICT exemplifies how university innovation drives policy—check research jobs at NZ universities advancing such tools.

Photo by Kind and Curious on Unsplash

ANZACS-QI Registries: Acute Care Quality Improvement

The All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registries, covering CathPCI (213,254 cases), ACS (101,332), and DEVICE implants, capture 95-99% of public hospital events. University of Auckland teams embed studies like MENZACS (2,015 post-ACS patients) within ANZACS-QI, linking to administrative data for prognostic models.

These have supported trials like High Flow Oxygen (40,872 patients) and international efforts like REDUCE-AMI, demonstrating registry-enabled trial efficiency.

Landmark Studies and Real-World Impacts

NZ EHR data has fueled studies on post-earthquake CVD spikes, rheumatic heart disease outcomes, and comorbidity predictions validated against Danish models. PREDICT-derived equations inform national guidelines, reducing inequities for Māori and Pacific peoples.

University researchers at Auckland have validated tools showing Māori risks 1.5x higher, guiding targeted interventions. VAREANZ, another Auckland initiative, links labs for vascular equity studies covering 2.5 million adults.

Navigating Challenges in Data Utilization

Despite strengths, challenges persist: variable completeness (e.g., ejection fraction missing in registries), limited primary care clinical data, and ethnic linkage biases for Pacific/Asian groups. Access requires ethics approval, and privacy under the 2020 Act mandates encryption.

• Data quality validations are sporadic, unlike Nordic systematic reviews.
• Probabilistic linkage in IDI excludes some clinical depth.
• Unsubsidized meds and OTC data gaps affect comprehensiveness.

Addressing these demands interdisciplinary university efforts in data science and epidemiology.

University Leadership in NZ Cardiovascular Data Research

The University of Auckland dominates, with its School of Population Health spearheading PREDICT and ANZACS-QI linkages. Collaborations with Middlemore Hospital and international partners like Aarhus University amplify impact. Other institutions contribute via VAREANZ and specialized registries.Explore opportunities in New Zealand higher education.

This research ecosystem fosters PhD/postdoc roles; see postdoc positions in public health.

Future Outlook: SDHR and Global Collaborations

The mid-2026 SDHR rollout will integrate primary/secondary data, boosting real-time research. Enhanced primary care capture and AI integration promise refined predictions. Cross-country pooling with Nordic/UK data could tackle global CVD.

Universities must invest in training for these tools, positioning NZ as a data-driven CVD leader.

Photo by Nik Schmidt on Unsplash

Career Opportunities in CVD Data Research

For aspiring researchers, NZ universities offer pathways in epidemiology and health informatics. The review highlights demand for skills in linkage, AI modeling, and equity analysis. Platforms like Rate My Professor and higher ed career advice aid navigation.Browse higher ed jobs, including research jobs and university jobs in NZ. Share insights in comments below.