The demand for long-term care (LTC) services is rising due to ageing populations across the world who are facing more disabilities. Governments require the best available evidence for public programmes to ensure older adults have access to high-quality LTC services.
The WHO Centre for Health Development (WHO Kobe Centre) is supporting research on the organization and financing of LTC. One of these studies is on “Initiatives to improve the coverage, quality, financial protection and financial sustainability of long-term care: a rapid scoping review” by Marilyn Macdonald, Erin Langman and Julie Caruso of the JBI Centre of Excellence at Dalhousie University, Canada.
Using artificial intelligence - a machine learning tool called Computer Assisted Learning (CAL) – they were able to rapidly scope over 70 000 documents of recent public initiatives to improve long-term care coverage, quality, financial protection, and financial sustainability for those aged 60 years and older. Using specific search criteria, this mass of information was whittled down by CAL and human reviewers to a manageable 24 reports.
“The use of a machine learning tool provided a dataset of relevant studies within 6 weeks. Doing rapid reviews is essential to provide timely evidence for clinicians, decision- and policy-makers for optimal patient care, and CAL can clearly facilitate this,” say the researchers. This work was recently presented at the Global Evidence Summit in Prague, Czech Republic.
The WHO Kobe Centre conducts and promotes innovations and research in sustainable financing to accelerate progress towards service coverage in the context of population ageing to inform policies in countries.
Read more about this long-term care work here.