Countering bias in the health system Heart disease is the leading cause of preventable mortality in Aotearoa, New Zealand. It is a disease which disproportionately affects certain groups such as ... Read More
An Automated Approach Towards Prioritisation and Preoperative Assessment The path to an elective surgery can contain many difficulties for both patients and clinicians. It is a lengthy, as well as ... Read More
Calibrated for Kiwis As a small country in the South Pacific, our uniqueness is often overlooked by health science researchers. Medical assessment tools are created and used based on research ... Read More
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 ... Read More
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 ... Read More
Recent studies have indicated that the current risk calculators are out of date and not specific to local contexts and population. This project is testing the hypothesis: Can we build ... Read More
As Electronic Health Records (EHRs) become more ubiquitous, healthcare providers are beginning to appreciate the benefits of using this data for ‘secondary applications’, such as disease diagnosis and readmission prediction, ... Read More
This feasibility study, in partnership with Vensa Health, is answering the following questions: How can we accurately automate interpretation and dissemination of lab results to save clinician time, while keeping ... Read More
Health Outcome Prediction Engine (HOPE), comprising HOPE for Stroke HOPE for AAA (Abdominal Aortic Aneurysm) HOPE for Patient Reported Outcome Measures Treatment decisions for elective interventions such as hip replacement ... Read More
Data-driven healthcare will result in a “tsunami” of information from existing and new data sources including patient-generated data from genetic testing, consumer devices such as wearable fitness apps, and social ... Read More
Primary and secondary healthcare data has the potential to enhance the accuracy of healthcare decision making; however, it is often siloed and difficult to share and access these data types ... Read More
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 working actively to remedy this ... Read More
New Zealand has excellent health data due to national ID number and high quality data scientists. We seek to link them together by making health data easier to access for ... Read More
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 ... Read More
In partnership with Cure Kids and the National Science Challenge A Better Start, PDH supports the work led by The University of Auckland’s Gayl Humphrey on the project “See how they ... Read More
Automating for accuracy Patients’ regular medicines are often inaccurately prescribed when they transfer from hospital to home; a major source of medication errors and iatrogenic harm. Medicines reconciliation (MedRec) is ... Read More
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 ... Read More
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 ... Read More
Student Projects Successful in 2016-2017 The Precision Driven Health partnership had an exciting summer of research in 2016-2017 with 11 students completing precision medicine projects. The students, from the University ... Read More
Present methods for describing surgical outcomes greatly underestimate the risks to patients. The aim of this project is to find a method that describes post-operative risk more accurately and then ... Read More
In its first phase, this research developed a real-time mobile-based vital signs monitoring application in the hospital context using medical devices and clinical decision support techniques. The application, VitalsAssist, was ... Read More
