Transforming Healthcare with AI
Addressing Workforce Shortages, Enhancing Patient Care, and Driving Digital Transformation
1) How AI is transforming healthcare in the context of the current healthcare landscape affected by workforce shortages, financial pressures, and increasing healthcare demand?
a) In what ways can AI enhance workforce efficiency, particularly in overburdened healthcare systems?
b) How do you see AI changing the roles of doctors, nurses, and other healthcare workers?
Today, healthcare is simply not working as it needs to be as pressing challenges such as healthcare workforce shortages are making it more difficult for healthcare systems to deliver timely, high-quality care to patients. The latest findings of the Future Health Index (FHI) 2024 report which surveyed nearly 3,000 healthcare leaders in 14 countries globally show that that 71% of healthcare leaders in APAC countries are concerned about staff shortages resulting in delays in care for patients . In Japan, 80% of healthcare leaders indicated that staff shortages are leading to increased burnout and mental health problems among healthcare workers.
The need for healthcare digital transformation to ease this burden has never been greater. Artificial intelligence (AI) has already made a positive impact by automating processes to reduce the administrative burden on healthcare staff and streamlining services for patients and is increasingly finding its way into clinical practice to support clinical decisions. Generative AI tools with the potential of converting complex health data into actionable insights will further enable healthcare staff to make informed decisions efficiently and quickly. These developments are changing the way care is delivered, optimizing workflows and improving operational efficiency for healthcare organizations, and giving time back to healthcare staff to focus on patient care.
2) From your experience, are healthcare leaders more inclined to adopting AI for operational efficiency or for enhancing patient care?
a) Can you provide examples of real-world applications of AI in healthcare that have proven to improve outcomes for patients or streamline clinical processes?
While AI has already been deployed for a wide range of administrative processes to improve operational efficiency, the applications of AI will play an increasingly vital role in enhancing patient care. In APAC, healthcare leaders surveyed in the FHI study reported that they have implemented and are planning to implement AI for clinical decision support in the next three years across a wide range of areas including preventive care, radiology and pathology services, in-hospital and remote patient monitoring, treatment planning and in clinical command centers1.
We are seeing some exciting capabilities in imaging technologies powered by AI. For example, AI-enabled cardiovascular ultrasound platforms can speed up cardiac ultrasound analysis and automate the diagnostic process, supporting clinicians' decision making, allowing them to detect, diagnose, and monitor various cardiac conditions with greater confidence and efficiency. This ultimately improves patient care and outcomes in the management of coronary and valvular diseases.
In magnet resonance imaging (MRI), AI can significantly enhance a patient journey at every single step from autonomous planning, scanning, to post-processing, reading and reporting. AI algorithms integrated into MRI systems can significantly increase imaging speed and improve image quality. This addresses patient needs for faster and more accurate diagnosis and treatment for various complex and urgent medical conditions.
3) What are some of the most exciting AI developments on the horizon for healthcare? How do you see these innovations transforming the healthcare industry in the next 5-10 years?
a) How can AI be used to anticipate and prevent health crises, such as managing chronic diseases or preventing hospital readmissions?
Generative AI is set to be the next game changer in healthcare. According to the 2024 FHI report, 36% of healthcare leaders in APAC are currently investing in generative AI technologies and 62% are planning to invest in the next three years. This is ahead of global healthcare leaders currently investing (29%) and planning to invest in the next three years (56%)1.
As diagnosis and treatment become ever more complex and patient-specific, generative AI with its ability to distill complex information into easily understandable formats, can empower patients to more actively participate in their healthcare journey, leading to improved health outcomes and a more engaged patient population.
Actionable insights generated by these advanced tools will offer a range of opportunities to improve patient care. According to the FHI survey, healthcare leaders in Japan believe that data-driven insights could help to optimize treatment plans and care pathways (53%) and to identify evidence-based best practices (43%)2. By combining predictive analytics capability with data from other sources such as the patient’s medical record, a more accurate and robust clinical prediction can be achieved, where clinicians can intervene and prevent poor clinical outcomes. For example, in the ICU setting, AI-based prediction technology is already being used to reduce the number of cardiac arrests.
Another technology that has proven to support ICU settings is telemedicine. Tele-ICU is defined as a system in which ICU professionals remotely support critically ill patients and on-site staff. With Tele-ICU, Showa University Hospital in Japan showed proven results in lowering overall mortality rates in ICU settings by more than half, from 8.5% to 3.8%. Access frequency of the on-site physicians was also reduced by 25%. These results suggest that the Tele-ICU could resolve the shortage of intensivists and reduce the regional disparities in intensive care resources.
4) What are the significant barriers to implementing AI in healthcare settings?
a) AI relies on vast amounts of patient data to function effectively. What are some of these concerns/ challenges?
b) How can these issues be mitigated or addressed?
While there is widespread excitement about the possibilities of AI in healthcare, there is a shared recognition that AI needs to be implemented in a responsible way to avoid unintended consequences.
In APAC, 95% of healthcare leaders surveyed are concerned about data bias in AI applications widening disparities in health outcomes1. Making AI more transparent and interpretable for healthcare professionals (45%), ensuring staff diversity in data and AI (43%), continuous training and education in AI (40%), and implementing policies for the ethical use of data and AI (39%) were listed as strategies to mitigate the risk of data bias1. Cross-sector collaboration and coalition-building are key to the successful implementation of these strategies.
5) As AI continues to evolve, how important is collaboration between tech companies, healthcare providers, and governments in fostering responsible innovation and ensuring the ethical deployment of AI?
Collaboration across stakeholders and sectors is paramount. One of the barriers to the adoption of AI is the lack of consensus around its implementation and regulation . Partnerships across sectors and countries through dialogues, guiding principles, testbeds, and policies could help address this so that AI can be developed and adopted in a safe manner.
At Philips, we combine the power of AI with deep clinical knowledge to create solutions that integrate into the workflows of healthcare providers. By leveraging our AI and informatics capabilities to innovate across imaging, interventional and monitoring, while also ensuring that AI and data are being used in a responsible way, we are supporting healthcare organizations in driving a successful digital health transformation and in providing better care for more.
Reference:
1. Philips Future Health Index 2024 Report: APAC Healthcare leaders taking bold and thoughtful changes to deliver better care for more people. Philips. From: https://www.philips.com.sg/a-w/about/news/archive/standard/news/articles/2024/20240916-philips-future-health-index-2024-report-apac-healthcare-leaders-taking-bold-and-thoughtful-changes-to-deliver-better-care-for-more-people.html
2. Philips Future Health Index 2024: Japanese Report Better care for more people. Philips. From: https://www.philips.co.jp/a-w/about/news/future-health-index/reports/2024/better-care-for-more-people.html
3. Subbe, C.P., Duller, B. & Bellomo, R. Crit Care (2017) 21: 52. doi:10.1186/s13054-017-1635-z
4. Watanabe, T., Ohsugi, K., Suminaga, Y. et al. (2023) https://doi.org/10.1186/s40560-023-00657-4
5. Boosting healthcare capacity with AI. World Economic Forum. From: https://www.weforum.org/agenda/2024/01/ai-in-healthcare-could-bridge-a-significant-capacity-gap/
