The improved use of existing databases could help to save billions of euros in healthcare costs arising from osteoporosis-related bone fractures.
According to a study carried out by researchers at Lero, the Science Foundation Ireland Research Centre for Software, billions of euros in global healthcare costs arising from osteoporosis-related bone fractures could be eliminated using big data to target vulnerable patients.
The study of 36,590 patients who underwent bone mineral density scans in the West of Ireland between January 2000 and November 2018 found that many fractures are potentially preventable by identifying those at greatest risk before they fracture, and initiating proven, safe, low-cost effective interventions.
The research, led by Lero’s Professor John Carey, Consultant Physician in Medicine and Rheumatology, Galway University Hospital, Mary Dempsey, Mechanical Engineering, and Dr Attracta Brennan, Computer Science, NUI Galway, has been published in the British Medical Journal.
Risk prediction
Carey highlights that there is a global osteoporosis health crisis, with predictions of American medical costs associated with osteoporotic-related fractures potentially exceeding $94bn (€77.6bn) annually by 2040. Previous studies have shown that in 2010, for example, approximately 43,000 European deaths were fracture-related, while expenditure related to osteoporosis exceeded €37bn.
He also points out that, while Ireland has one of the highest osteoporosis rates globally, currently there is no national public or government policy to address the healthcare requirements of osteoporotic fractures, with costs rising rapidly.
The Irish dual-energy X-ray absorptiometry (DXA) Health Informatics Prediction (HIP) project on bone mineral density now plans to assess current diagnostic classification and risk prediction algorithms for osteoporosis and fractures.
Professor Carey said: “This will identify which predictors are most important for Irish people at risk for osteoporosis, and develop new, accurate and personalised risk prediction tools using the large, multicentre, longitudinal follow-up cohort. Furthermore, the dataset may be used to assess, and possibly support, the assessment and management of other chronic conditions such as cardiovascular disease, cancer, and other illnesses due to the large number of variables collected in this project.
“In Ireland, public hospital bed days have increased by almost 50% in the past decade for osteoporotic fractures and outnumber heart attacks, cancer, diabetes, and many other illnesses that receive much greater attention.
“Preliminary estimates suggest the number of fragility fractures and deaths following fracture for Irish adults aged 50 years and older in 2020 was similar or greater to the numbers with COVID-19 infection, but there is no daily report on the numbers tested, hospitalised, or who die following a fracture. Use of these and other data could help close those gaps. A modest 5% reduction in those costs would result in an annual saving of €1.85bn at 2010 prices.”
Using Artificial Intelligence
Professor Carey highlights that there are big data sets across the globe like the one utilised in the study.
He said: “Cost-effective, innovative forms of data interrogation such as Artificial Intelligence (AI) will enable the timely identification and treatment of patients vulnerable to osteoporosis fractures, providing them with better care and using precious resources efficiently. There will be many opportunities to provide better patient outcomes and save billions of euros.”
Carey believes this collaboration between clinicians, big data scientists, engineering and computer scientists in Ireland, Britain, and China will help leverage innovation, critical thinking, and international partnerships to accelerate their programme and opportunities.
Director of Lero, Professor Brian Fitzgerald, said the utilisation of AI shows how software development initiatives can directly impact people’s lives at a fundamental level.
