New technology developed by the Royal Melbourne Hospital (RMH) neurosurgery team has the potential to predict a patient’s health-related quality of life post-surgery.
Predicting the quality of life of a benign or low-grade brain tumour provides the opportunity for early intervention and a targeted use of the available supportive care resources.
The technology was developed by Dr Roshan Karri, a surgery trainee at the RMH.
Roshan is a self-taught data science expert, after growing up with parents with computer engineering backgrounds. The program uses a data base of previous patients and is coded to enable the machine learning (ML) algorithm to work out possible outcomes for a patient.
The ML will assess if it’s likely a patient would have persisting symptoms or a decline in quality of life between 12-60 months from tumour resection. The code uses similar technology to what Netflix uses to understand what it should recommend a person to “watch next”.
“The technology allows us to understand if a patient may need some extra support such as physical therapy, psychological and/or other supports to make their post-surgery recovery as effective and comfortable as possible,” said Dr Roshan.
RMH head of neurosurgery, Professor Kate Drummond has over a decade of data relating to quality of life, while data is subjective validated questionnaires have ensured a level of consistency. And in this case meant the data gathered can be used to assist in understanding outcomes for patients in the future.
“Quality of life is a key measure of our decision making when it comes to surgery and treatment of brain cancer – there is always a wedding, baby or event a patient wants to be a part of and where possible we always try to help our patients achieve their goals while they undergo treatment,” said Prof Drummond.
The program is yet to be used on a patient, as a larger database is needed to confidently pass on results.
“So far the research we have done demonstrates there is a lot of promise based on routine demographic data and peri-operative data to predict quality of life outcomes in patients,” added Dr Roshan.
The hope is this technology can be used beyond neurosurgery and into other areas across the hospital and healthcare system more broadly.
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