AITHM James Cook University


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22 July 2019

The Cohort Doctoral Studies Program engages practising health professionals in research degrees. The industry partners for the Cohort Doctoral Studies Program are predominantly the institutions delivering health services to Northern Australia including hospitals, private practices and public health services. The program also partners with Health Services and private practices in other states and territories including New South Wales, Victoria, Northern Territory and Tasmania. Typically, Cohort Doctoral Studies candidates begin their research candidature already employed in one of these industries. The Cohort Doctoral Studies Program is therefore reverse engineered with industry partners coming to the program to engage in research degrees rather than research candidates being placed with industry. The main aim of the program is to create an environment in which health professionals working full or part time can successfully undertake a research degree. Thus, Cohort Doctoral Studies candidates often integrate research into their work rather than undertake work-integrated learning typical of higher degree by research (HDR) industry placements.

Blood study aims to minimise patient risk

Medical laboratory scientist, Andrew Cross, is on a quest to reduce mislabelled patient blood samples – and their potentially catastrophic consequences – with the assistance of the AITHM Cohort Doctoral Studies Program.

This year, the Townsville Hospital haematology supervising scientist has embarked on a Master of Philosophy (Medical and Molecular Sciences) degree at JCU. His aim is to develop a mathematical formula to help detect blood samples bearing the wrong patient name.

“We see wrong blood in tubes throughout our whole career. It is a world-wide issue,” observed Andrew, who also lectures fourth-year Medical Laboratory Science students at the university.

“At the moment, detection comes down to the skill of the scientist or some checks in laboratory information systems. We are trying to improve on that, by developing a mathematical formula that automatically predicts the likelihood of mislabelling, based on past and present results.

“This will provide a support network for the scientist, doctors and patients, so that when we analyse the sample, we can say with a degree of mathematical certainty that this sample is from the correct patient.”

There is a great deal at stake, if mislabelled blood samples are not identified.

“It could lead to treatment delays, because a disease picked up in the blood is attributed to the wrong patient. Or someone may receive treatment they were not meant to get,” Andrew said. “In the worst case scenario, it could result in the transfusion of the wrong blood type to a patient, resulting in death.”

It is almost 30 years since he last viewed the world as a student. Born and raised in Sydney, he graduated with a Bachelor of Applied Science (Medical Laboratory Science) degree from Charles Sturt University in 1990.

“Now here I am doing research in the field that I both lecture and work in, so it is actually a really nice fit,” he observed.

This year, keen to revitalise his study skills, Andrew enrolled in Cohort 16 of the AITHM Cohort Doctoral Studies Program, which provides a comprehensive support network for students.

“Working with the Cohort Program is fantastic for people like me, who haven't studied for quite a long period of time,” he said. “It has been great from week one.

“It is helping us transition back into that field, providing a good stable background of information and resources; the tools to successfully do our research. Everything, from time management, to how to write a thesis and literature review. I'm always using references that I have downloaded from the Program website.

Andrew met other members of the 14-strong cohort, during an induction block week held on the JCU Townsville campus, in February. He is confident that they will form a strong peer support network, based on their shared commitment to health research.

He is already energised by new, unexpected avenues opening in his own research.

“We are looking into machine-based learning at the moment, which is something I didn’t know anything about before,” he said. “So writing a mathematical formula to detect mislabelled blood samples is one option, but another way is to actually teach a machine to recognise wrong blood in tubes. That’s exciting. It is another pathway to explore.”


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