Healthcare leaders in the Asia-Pacific region are focusing on improving operational efficiencies through workflow prioritisation, data integration, and AI-enabled innovation to improve patient care impacted by workforce shortages, financial challenges, and growing demand.
This is according to a report from Philips, which covered nearly 3,000 healthcare leaders in 14 countries, including Australia, Indonesia, and Singapore.
“While long wait times and staff shortages are making it difficult for people to get the care they need, when they need, we are also observing our healthcare leaders taking bold and thoughtful changes to deliver better patient care for more people,” says Mark Burby, VP of health systems for Philips APAC.
“They are determined to overcome data integration challenges to fully uncover its utmost potential and are excited to embrace the next level of AI implementation for critical decision making and improved efficiencies,” said Burby.
Seven in every 10 (71%) of healthcare leaders in APAC are concerned about staff shortages resulting in delays in care for patients.
Furthermore, 92% of healthcare leaders in APAC highlight that financial challenges are impacting their organisation’s ability to provide timely, high quality-care, with 59% of them currently improving operational efficiency at their organization as a financial strategy.
Other countries are doing the same, including Singapore (64%), Indonesia (57%), and Australia (56%).
To deal with the high volume of patients without compromising on quality, workflow prioritisation is seen as the biggest opportunity for automation to improve productivity and ease staff shortages worldwide. In APAC, close to half (45%) have already implemented workflow optimisation.
Also, healthcare leaders in APAC believe that the benefits from having data-driven insights include optimising treatment plans/care pathways (36%), identifying evidence-based best practices (36%), forecasting and managing patient demand (36%), predicting and reducing adverse patient events (33%), reducing hospital readmissions (33%), and reducing diagnostic and elective care procedure waiting lists (31%).
However, 93% reported that they experienced at least one data integration challenge.
These challenges affect their ability to provide timely and high-quality care, and include an increased risk of errors, reduced patient safety and/or quality of care (36%), limited coordination between care providers/departments (33%), increased operational costs due to inefficiencies (32%), spending time accessing/integrating data resulting in less time caring for patients (31%), and missed opportunities for preventive care or early intervention (31%).
To fully uncover the benefits of data integration, 67% of healthcare leaders in APAC highlighted the importance of quality data.
They identified improved accuracy of data (36%), improved data security/privacy (34%), full patient access to their own health data (34%), and improved interoperability between platforms/healthcare settings (31%) as areas to be changed when handling data.
In APAC, successful adoption in AI is observed with healthcare leaders increasingly embracing AI for clinical decision support.
The findings show how they have implemented and are planning to implement AI for clinical decision support in the next three years across different areas of care including preventive care (91%), medication management (90%), in-hospital patient monitoring (89%), treatment planning (89%), remote patient monitoring (87%), in clinical command centers (83%), radiology (79%), and pathology (79%).
In APAC, 36% of healthcare leaders are currently investing in generative AI technologies, with 62% planning to invest in these technologies in the next three years, consistent with interest in Indonesia (74%), Singapore (64%), and Australia (49%).
Overall, APAC’s interest in generative AI is ahead of global healthcare leaders currently investing (29%) and planning to invest in the next three years (56%).
While there is widespread excitement about the possibilities of AI in healthcare, 95% of healthcare leaders in APAC are concerned about data bias in AI applications widening disparities in health outcomes.
