A new report by Royal Philips warns that the 鈥榯rust gap鈥� around deploying AI in healthcare systems threatens to stall progress at a time when innovation is crucial.
笔丑颈濒颈辫蝉鈥� analysed priorities and perspectives among 6,000 patients and 1,900 healthcare professionals (HCP) across 16 countries, including the US, UK, China, and India.
The average global wait time to see a specialist was revealed to be 70 days. Patients in some countries reported delays of four months or more. The average wait time in the UK stood at 109 days 鈥� the third highest globally.
A third of surveyed patients experienced worsening health due to delays in seeing a doctor, with over one in four ending up in the hospital due to long wait times.
According to Philips’ chief medical officer, Dr Carla Goulart Peron, cardiac patients face 鈥渆specially dangerous鈥� delays, with 31% of those surveyed being hospitalised before even seeing a specialist.
鈥淲ithout urgent action, a projected shortfall of 11 million health workers by 2030 could leave millions without timely care,鈥� Dr Peron added.
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By GlobalDataAmong HCPs, 77% reported losing clinical time due to inaccessible patient data, with over a third reporting a time loss of over 45 minutes per shift, equating to 23 days per year.
To alleviate the reported challenges, a key part of the FHI is to assess the perceived role AI can play in addressing pain points and helping HCPs deliver better care to more people.
Of the surveyed HCPs, 46% said that slow adoption of AI is contributing towards missed opportunities for early diagnosis and intervention, 46% said that it was worsening burnout from non-clinical tasks, and 42% reported that it was worsening patient backlogs.
In addition, 82% of HCPs said AI and predictive analytics could save lives by enabling earlier interventions while 75% stated that digital health technologies such as AI will reduce hospital admissions in future.
The 鈥榯rust gap鈥�
According to the report, while there is a clear desire for greater AI implementation, challenges exist around closing the 鈥榯rust gap鈥� around the technology.
While HCPs generally express high confidence in the use of AI, patients are more reserved, with their comfort level around AI varying significantly across different uses.
The report stated that patients want AI to work 鈥渟afely and effectively鈥� to reduce errors, improve outcomes, and enable a more personalised care provision. But their confidence levels around AI鈥檚 ability in more critical areas of healthcare delivery are variable.
For instance, HCPs鈥� confidence in using AI for triaging patients to prioritise urgent cases stood at 81% versus 63% among patients, with 83% of HCPs comfortable using AI to create tailored care plans versus 66% of patients.
Scepticism around AI also remained among HCPs. 69% reported being involved in AI and digital technology development, yet only 38% believed these tools meet real-world needs.
In addition, more than 75% of HCPs reported being unclear about liability for AI-driven errors, expressing that trust around AI implementation is predicated on clear legal and ethical standards, strong scientific validation, and continuous oversight.
Philips’ chief innovation officer Shez Partovi said: 鈥淭o realise the full potential of AI, regulatory frameworks must evolve to balance rapid innovation with robust safeguards to ensure patient safety and foster trust among clinicians.
鈥淏y 2030, AI could transform healthcare by automating administrative tasks, potentially doubling patient capacity as AI agents assist, learn, and adapt alongside clinicians.
鈥淭o that end, we must design AI with people at the centre 鈥� built in collaboration with clinicians, focused on safety, fairness, and representation 鈥� to earn trust and deliver real impact in patient care.鈥�
