Macquarie University: using patient data in real-time clinical decisions

This is the first in a series of articles showcasing the Sax Institute members’ diverse range of research with implications for future health policy and practice.

BiancaGallegoLuxan_web3
Dr Bianca Gallego Luxan

Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University

Deciding how to treat a patient by examining the experience of previous, similar patients is far from a new concept in medicine, but research from the Centre for Health Informaticsaims to bring that idea into the 21st century.

Head of Health Analytics and Senior Research Fellow at the Centre, Dr Blanca Gallego Luxan, said researchers were working on projects that could see electronic patient records and hospital data used at the bedside to guide clinicians’ decisions about patient management.

“A lot of people are doing epidemiological studies using clinical records, but we are separating ourselves a bit from this trend and moving into the area of doing real-time analytics for decision support,” Dr Gallego Luxan said

Patients like mine

The “patients like mine” project is looking at how an electronic health record (EHR) database could be used to support clinicians to manage individual patients for whom the clinical guidelines do not apply, due to comorbidities or other complications.

“The idea is that the patient arrives at the clinic, and if there is no evidence-based guidelines about what to do to treat that patient, the clinician would have the option of pressing a button and seeing what has happened to other patients like him or her,” Dr Gallego Luxan said.

Findings from a ’virtual cohort’ of similar patients drawn from the EHR would form an alternate source of evidence to inform decision-making.

As detailed in a recent paper in the Journal of Comparative Effectiveness Research, the project relies on patients having an electronic health record that follows them throughout the health system.

“Real-time interrogation of EHRs via virtual cohorts will offer more personalised care by complementing existing evidence, clinical guidelines and clinician experience,” the paper stated.

Dr Gallego Luxan added: “Looking at what happened to similar patients is a concept that is old in medicine, but only now that we have new technology are we able to look at doing it in a systematic way.”

Patient trajectory management

The Centre is also researching the development of predictive models to show the probability of hospital patients being discharged, staying in hospital, dying or being readmitted within a specific timeframe, such as the next seven days.

The models, which researchers are now validating, would enable hospitals to come up with a daily “forecast” showing the likely future trajectory of individual patients ‒ information that would be valuable in planning for patients’ discharge or looking at ways to avoid readmission in those at highest risk.

“It would help doctors to make decisions at very early stages,” Dr Gallego Luxan said.

She said there was currently a wealth of patient data being collected throughout the health system that was not being fully utilised.

“It’s a very exciting area of research and it definitely will have a role at some point in clinical decision support.”

The Sax Institute’s unique organisational structure, with 47 members from public health and health services research groups and their universities, connects us with a powerful public health network and world‑leading research expertise.

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