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National Centre for Healthy Ageing (NCHA), a partnership between Monash University and Peninsula Health, have developed a novel method for improving dementia detection in hospitals by combining traditional methods with artificial intelligence (AI).
Approximately 50 million people worldwide live with dementia, a number expected to triple by 2050, according to the World Alzheimer Report.
In Australia, there is still a need to substantially improve our methods for counting people with dementia. Accurate Identification is critical to understanding the true size of the problem nationally, and to be able to effectively plan services. However, routine health data that are currently used for this purpose probably underestimate the numbers of people with dementia.
Regular healthcare contact and hospitalisations provide an important opportunity to address this issue. Currently, in hospitals, dementia is recorded based on the gathering of information in the medical records by medical coders, who find it difficult to look through the vast amount of written information in the records.
In a study involving over 1,000 individuals aged 60 and above in the Frankston-Mornington Peninsula, algorithms using traditional data approaches with AI in electronic health records demonstrated high accuracy in identifying whether or not a person may have dementia. Supported by national health bodies, the initiative could transform how dementia is identified, counted for national estimates, and managed in healthcare settings.
The research team based at Peninsula Health, involving NCHA’s Healthy Ageing Data Platform group and clinicians from Australia and the USA, have tackled this problem using AI and found that a particular type of AI called natural language processing (NLP) applied to written text in medical records significantly enhances dementia identification capacity.
The project was supported by grants from the National Health and Medical Research Council, the Medical Research Future Fund, and the Department of Health & Aged Care.
Their peer-reviewed paper, ‘Dual-Stream Algorithms for Dementia Detection: Harnessing Structured and Unstructured Electronic Health Record Data,’ published in the Alzheimer’s & Dementia Journal showed that algorithms combining traditional methods with AI demonstrated very high accuracy for detecting the presence of dementia from information in electronic health records.
Dr Taya Collyer, Lead author, said the study was based on people aged 60 and over with dementia diagnosed by specialists using gold standard methods, and a comparison group without dementia.
“Accessing high-quality curated electronic health records from our Healthy Ageing Data Platform helped assemble the data efficiently to address this problem. Special software was used to harness the large amount of free text data in a way that NLP could then be applied,” Dr Collyer said.
Professor Velandai Srikanth, NCHA Director and project lead said the future impact of this novel approach is exciting, not only for the better counting of numbers of people with dementia, but also for the efficient identification of people with high probability of dementia who may need care and support but who may get missed otherwise.
“Given that clinical recognition of people diagnosed with dementia presenting to hospitals is poor, using this new approach we could be identifying people earlier for appropriate diagnostic and clinical care. I am sure that many people are missing out on good care because we are not very good at identifying them or their needs,” Professor Srikanth said.
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