Ehealth MaskHelper Tool - QnFIT testing to inform AI based facial recognition

Overview

Initiative type

Service Improvement

Status

Deliver

Published

03 August 2021

Topic

Showcase 2021

Summary

Townsville University Hospital (TUH) pioneered the first Quantitative Fit Testing (QnFIT) for N95 masks in Queensland and, in collaboration with the University of Queensland (UQ), developed the innovative eHealth MaskHelper tool. This enables operational standardisation, reduces wastage, informs manufacturers of mask requirements, and has the potential to develop a mathematical model using facial recognition software.

Key dates

Aug 2021 - Aug 2021

Implementation sites

Townsville University Hospital

Partnerships

Phase1: THHS, Queensland Department of Health, University of Queensland. Phase 2: THHS, Q Health, Griffith University

Aim

To leverage facial recognition analysis gained during employer mandated Quantitative Fit Testing to achieve operational standardisation and cost efficiency by reducing wastage and enabling smarter central procurement.

Outcomes

achieve uniformity, standardisation and ensuring repeatability across Queensland Health through a comprehensive package
cost saving via central procurement and has further ability to inform mask design through innovation
preparedness for future airborne pandemics
minimising annual fit-testing requirement using AI based evaluation
ability to create a Fit Test Passport between HHSs.
potentially create a mathematical model that uses facial recognition software to obviate the need for the estimated 100,000 annual fit testing requirements throughout Queensland as part of employment safety law.

Background

Maintaining safe and high-quality care systems and services during COVID-19 has been a major challenge for health providers. The use of technology has been a driving force in improving health outcomes, for Queensland’s First Nations people in particular.

Methods

More than 1,200 participants were fit tested via a research methodology capturing facial characteristics (September 2020 to March 2021)
Tripartite collaboration with COVID-19 analytics team and University of Queensland to develop an AI based tool to reduce mask wastage and improve efficiency
First HHS in the state to take a scientific research based approach
AS1715:2009 standards were applied, using a four-test protocol to remove individual bias
Creation of a ehealth MaskHelper tool, hosted on the Queensland Health intranet with current expressions of interest from 10 HHSs, the Queensland Ambulance Service and Mater Hospital, Brisbane with the ability to deliver real time solutions and feedback statewide.

Discussion

Phase 1 proof of concept study has been completed across 1,200 participants at the Townsville Hospital and Health Service (THHS) site.

The results have been presented as part of the Statewide PPE working group, endorsed by the Deputy Director-General, Clinical Excellence Queensland and also as of 8 June; the COVID-19 Response Group.

Lessons learnt

Even though the project commenced in Townsville, we learnt to steadfastly drive an inherently sound and innovative idea with patience and determination by bringing all aspects of our diverse healthcare areas together. We have shown that by uniting and collaborating together we can aim for a greater goal that has game changing potential.

Open minded discussions, keeping the sanctity of the process uppermost, listening and acknowledging challenges across a massive organisation such as Queensland Health, leaning on local champions and some wonderful people especially when chips are down have been some of the other amazing lessons.

Key contact

Dr Arjun Chavan

Senior Staff Specialist PICU

Townsville Hospital and Health Service

Email: arjun.chavan@health.qld.gov.au

Last updated: April 2025