Category: In Progress

cute girl sitting in between her grandparents

Patients Like This

It is important to provide patients with reliable, accurate and personalised information about their health conditions, to engage them in their health. Often, this is done by doctors, based on their textbook knowledge and prior clinical experience in communicating with and managing similar patients under their direct care. Whilst this usually works well for experienced …

Smart Patient Cohort Builder

Triaging GP referrals is a time-consuming task for doctors in New Zealand. It is common for doctors to spend more than ten hours per week on triaging electronic referrals to various risk categories or direct to investigation tests. Presently, there are over 200 untriaged referrals at Waitematā District Health Board (WDHB) which are close to …

Developing a Decision Support System at ED triage for predicting health outcomes

Our previous two-year research project on Surgical Outcome Calculators examined surgical outcomes in NZ patients to help produce a surgical risk prediction tool: nzRISK, which produces a risk score for that patient at one month, one year and two years after surgery. NZ clinicians are now using the tool, which has produced tremendous interest and …

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 (or coronary heart disease) and stroke but have lower access to health care. Intervention must …

Telehealth as a Model for Health Care Delivery for Underserved Populations

In New Zealand, Telehealth provided health care during the COVID-19 lockdown, but its use has declined back to pre-COVID levels. Despite the fact that Telehealth is equivalent to in-person care, the lack of guidelines for design and implementation may result in risks to patient safety. Telehealth has not been widely adopted in New Zealand and …

Feasibility of Analysis of Lab Result Patterns for Patient Results

Vensa has embarked on this project to enable the analysis of laboratory result patterns that aims for faster and safer dissemination of results to patients. It addresses the problem of increasing diagnostic laboratory tests being ordered which therefore requires the burden for ongoing clinical interpretation once the results are received to determine appropriate actions. The …

Interpretable Machine Learning

The “black box” metaphor is commonly used to refer to the lack of understanding of how modern Machine Learning (ML) systems make decisions.  Researchers are actively trying to remedy this situation which is especially problematic in healthcare, largely because legal accountability and ethics have greater emphasis and importance in the healthcare decision-making process than in …

Missing Health Data Imputation

Medical professionals analysing electronic health data often have to deal with data sets that are incomplete. If this data is not handled correctly it can result in negative outcomes such as bias, complications and ultimately invalid conclusions. Finding ways to deal with missing data is at the heart of the project Value added by Multiple …

Automated De-identification

Separating patients from their records The idea that a patient’s Electronic Health Record (EHR) has a secondary value, beyond the immediate treatment of a single individual, is becoming more prevalent as medical research incorporates machine learning (ML) practices. The information an EHR contains, such as symptoms, treatment plans, response to medication, can be extracted using …

message map

Automated Message Mapping

This project involves automation of systems for mapping target fields to and from HL7 messages to enable automation of this previously laborious, manual process. PI: Junjae Lee, Orion Health Junjae Leeprecisiondrivenhealth.com/researchers/junjae-lee/