“Healthcare productivity has been declining since the 1980s, but AI & virtual health tools can drive more clinical care without expanding the workforce”, says Senior Managing Director at Accenture Health Dr. Safavi.
“More data has been created in the past two years than in the history of the human race” was one of the opening lines at the Intelligent Health AI conference 2018 in Basel. From clinicians, pharmaceutical companies to hospitals and the top regulators – the summit brought together the entire ecosystem around AI in healthcare. While the headliners were dominated by speakers of the pharm groups Novartis and Roche, the latter would also emphasize that startups are the most relevant partners to accelerate progress in this field.
When talking about healthcare policy as an iron triangle – consisting of access, cost and quality – Dr. Safavi (see picture) illustrated the classic inherent trade-offs in health care systems. If you improve 1 of these items, it has to come at the expense of one of the other two. Leveraging AI technology to disrupt and change traditional care models, next to developing a collaborative mindset among involved industries, was one of the central messages delivered by all speakers on stage.
One of the issues that could be solved using tech solution particularly caught my attention: loss of productivity due to administrative tasks. An estimated 10-15% loss of productivity roots in health care providers medical transcriptions and clinical documentation. In an effort to make this workload less burdensome AI-driven virtual assistants are a rising area of interest in the healthcare sector.
It is also one of the central aspirations at Nodus Medical to trigger a new work flow evocation around surgical cases. While focusing on outcome improvements for patients, this would also give time back to doctors to do what they were trained for – caring for patients. At Nodus we further want to act at the forefront of surgical intelligence and use standardized data generated by our digital solution to boost numbers in surgical case studies and create a community platform to bring key players together and ultimately make surgery as safe as possible.
Finally, a talk given by Ada illustrated how far AI has already come in integrating medical decision making into a personal health guide. Allowing millions of people worldwide to have access to healthcare that comes at low costs but high quality also challenges the iron triangle. Clinical decision tools today may raise the question of liability when using such algorithms in diagnosing a patient, but who says that in 5 years it won’t be the other way around? When AI progress will make medical decision much safer, should a doctor that does not check with data-proven tools be held liable for not guaranteeing the best possible care and therefore putting his patient at risk?