Precise and Timely Healthcare

Bringing it All Together

For this research theme, we utilise disparate data sources, analyses, and technologies to enable more precise and timely healthcare by way of the following:

  • Develop methods for combining community-sourced data to quantify patient health outside of a clinical environment.
  • Determine how data can enable more accurate and timely care, by providing contextual information to healthcare providers.

View our projects in this theme below.

In Progress

A Deep Learning Platform for GP Referral Triage

Countering bias in the health system Heart disease is the leading cause of preventable mortality in Aotearoa, New Zealand. It is a disease that disproportionately affects certain groups such as Māori – who have higher rate of ischaemic heart disease ...
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Smart Search: Clinical Document Semantic Search

A ‘Google’ for Electronic Health Records  Ten minutes can be an eternity for medical professionals that need to make split-second decisions to save lives. If they miss a single piece of vital information it could prove critical – but equally, ...
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Spatio-Temporal Big Data Analysis of Adherence Behaviour in Chronic Disease

Many patients in New Zealand don’t receive the benefits from their medications due to poor medication behaviour, referred to as medication adherence. Previously, data related to medication adherence has been gathered using questionnaire surveys based on the Health Belief Model ...
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Vital Sign Monitoring and Decision Support System

During admission to hospital, patients often show signs of acute physical deterioration before a serious event occurs. Current variation in vital signs charts, early warning scores, skills and knowledge of responders and availability of responders in hospitals means these patients ...
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Data Analysis Saves Lives – HOPE (AAA)

Māori are nearly three-times more likely to have Abdominal Aortic Aneurysms (AAA) – a condition described as “the silent killer” – than non-Māori. To address this, an innovative data analysis project helped identify and save patients with AAA, demonstrating the ...
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Improved planning for the scheduling of surgeries

Summer of Research project by Thomas Adams, supervised by Dr Michael O’Sullivan, University of Auckland. To better allocate resources and plan for surgeries, Counties Manukau District Health Board (CMDHB) require data-driven analysis of their surgical scheduling. This will help them ...
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Machine readable clinical guidelines and pathways

Summer of Research project by David Bassett, supervised by Dr. Patrick Gladding (University of Auckland) There has recently been rapid growth in the use of clinical guidelines and pathways for the assessment, diagnosis and management of medical conditions. These guidelines ...
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