Healthcare leaders in Singapore are committed to using artificial intelligence (AI) and predictive analytics to extract the most value out of the information they have. Nearly four in ten (38%) are already investing heavily in AI, while 74% predict it will become a top investment area within the next three years.
Currently, the highest AI investment is for operational settings. However, AI is expected to increasingly support clinical decisions – such as uses related to diagnosis or treatment recommendations, early warning scores, automatic disease detection and clinical decision guidelines – three years from now.
The Singapore Future Health Index 2022 report by Royal Philips also reveals that 45% of hospitals or healthcare facilities in Singapore have already adopted the technology, while 47% are currently in the process of doing so.
Similar to AI adoption, predictive analytics is mainly used in operational settings today, supporting tasks such as financial forecasting (26%), capacity planning (22%), and maintenance prediction (22%).
“Big data and AI present enormous opportunities for Singapore’s healthcare leaders to improve the quality, cost and speed of care, but a number of limiting factors – including data silos and staff shortages – need to be urgently addressed,” said Ivy Lai, country manager of Philips Singapore.
According to the same study, 77% of Singapore’s healthcare leaders cite data silos as the primary challenge hindering their ability to use data effectively. Respondents also say their staff are overwhelmed by the volume of data available.
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As such, 22% agree that the availability of data specialists would support them in using data more effectively, and 36% believe that greater staff expertise would help their facility to do more with data.
Besides that, healthcare leaders in Singapore believe that joining forces with health technology companies could provide healthcare facilities with counsel on contingency planning (32%), support technology integration (28%), and provide guidance on regulatory issues (27%) and data analysis (27%).
