Charles Sturt University (CSU) researchers working with colleagues from the Murrumbidgee Local Health District (MLHD) have been recognised for their collaborative efforts to develop advanced software that aims to improve patient care.

The CSU research team, led by Associate Professor Zahid Islam and Professor Mark Morrison, worked closely with MLHD managers, clinicians and data scientists to develop advanced software that can automatically collect, process and analyse patient data.

The system can automatically discover patterns of avoidable hospital admissions among groups of patients and use the patterns to predict future avoidable admissions and re-admissions by patients. 

"MLHD came to us with a problem; how to reduce the number of avoidable admissions in our hospitals by identifying patients who are likely to take avoidable admission in the future," Professor Islam said.

"The team comprising CSU and MLHD experts and users then developed a web-based system to automatically collect and process MLHD patient data from various sources and then apply our own data mining algorithm to discover any patterns of avoidable admissions that emerge from the data.

"The system then applies this knowledge to predict patients who may make avoidable admissions in future, and alerts clinicians about at-risk patients who are likely to make avoidable admissions and reasons why they are identified to be at-risk," he said.

"This helps MLHD clinicians to plan necessary services and health interventions to reduce the number of avoidable admissions."

Ms Summa Stephens, MLHD Project Lead, said the project required close collaboration between MHLD and CSU staff involved in health services, data informatics, and advanced computing.

"The web-based system can improve patient convenience and health condition by circumventing avoidable admissions in future," she said.

"It can also be used for currently admitted patients to give them careful treatment by analysing their re-admission possibility before releasing them from hospital.

"MLHD identified that there may be opportunities to better identify and  manage the health care of larger patient cohorts across a rural setting. We reached out to Charles Sturt University understanding they have an interest in health research and data mining. We saw there would be benefits in partnering with the University for this particular project and the development a long time collaborative relationship. 

"We now have a system that can be simultaneously accessed by a number of users in multiple locations, an important feature for a rural-based medical service," Ms Stephens said.

The project, titled "The Provision of a Predictive Risk Stratification Tool for the Chronic/Complex Healthcare: Engaging Stakeholders and Services (CHESS) Initiative" has been awarded by the MLHD with the Murrumbidgee LHD Excellence Award in the Collaborative team category, in recognition of excellent collaboration between MLHD and CSU in achieving a high quality outcome.

The project aligns with the University's ethos encapsulated in the Wiradjuri term 'Yindyamarra Winhanganha', or 'the wisdom of respectfully knowing how to live well in a world worth living in'.

"We wanted to use our expertise in solving real life problems and challenges and make an impact on our world through meaningful outcomes for industry, government, business and communities. This project demonstrates how the University's expertise can benefit the health of our community," Professor Islam said.