Every September the Dutch ‘prinsjesdag’ will be held. On this day the king speeches about the important cabinet’s plans for upcoming year in the Netherlands. One of the plans is regarding the healthcare costs, and sadly, every year the king announces an increase in these costs. So, it came by no surprise that the forecasted care premium of 2019 will increase by 124 Euros, which results into an estimate of 1432 Euros per year (ANP, 2018). But what causes this annual increase in healthcare cost?
The main cause is the inefficiency of the healthcare industry. Efficiency is described as the maximum feasible level of output for a given set of inputs (Cyclus, Papanicolus, Smith, 2016.). In the healthcare industry, this means that measuring efficiency will be done by the ratio of consumed resources to the valued health system outputs it created. An example of showing the seriousness of inefficiency in the healthcare is consuming excess resources or providing inefficient treatment. This may take away treatment to other patients who could have benefited from the treatment if the resources had been used better. Therefore, to increase the healthcare efficiency, aiming for improvements in resource mobilization and allocation is the solution (WHO, N.A.). Luckily, this can easily be achieved by adopting artificial intelligence (AI) in the whole healthcare industry.
Common artificial intelligences in today’s healthcare are not robots who can perform surgeries on their own, at least not yet. Algorithmic solutions form the everyday artificial intelligence (Pearl, 2018). When doctors and researchers insert data and evidence-based approaches into the algorithms, the computer is able to view and extract the information in order to apply it to a problem. In 2015 doctors were bewildered by a case of an old Japanese women who they thought had acute myeloid leukemia (Kirve, 2018). However, the treatments were unsuccessful for years. Then IBM’s Watson, an AI system, were consulted and found the right treatment. It reviewed approximately 20 million published oncological research studies and cross/referenced data to come to the solution: a rare form of leukemia which could not be detected through conventional methods. When you think about it, it is an enormous waste for the Japanese women to get the wrong treatment for years while the right treatment could have been detected at once by the AI. Therefore, we should not wait to adopt these AI into our whole healthcare industry. Is it not more efficient when AI recommends the treatment first, which can then be verified by the doctors?
References
APN. 2018. ZORGPREMIE VOLGEND JAAR STEVIG OMHOOG DOOR HOGE KOSTEN IN DE ZORG. Retrieved on 5-10-2018 from https://www.nationalezorggids.nl/zorgverzekering/nieuws/44562-zorgpremie-volgend-jaar-stevig-omhoog-door-hoge-kosten-in-de-zorg.html
Cyclus, J., Papanicolus, I., Smith, P. 2016. A framework for thinking about health system efficiency. Retrieved on 5-10-2018 from https://www.ncbi.nlm.nih.gov/books/NBK436891/
Kirve, P. 2018. Can artificial intelligence give us a more efficient health care system? Retrieved on 5-0-2018 from https://geneticliteracyproject.org/2018/09/10/can-artificial-intelligence-give-us-a-more-efficient-health-care-system/
Pearl, R. 2018. Artificial Intelligence In Healthcare: Separating Reality From Hype. Retrieved on 5-10-2018 from https://www.forbes.com/sites/robertpearl/2018/03/13/artificial-intelligence-in-healthcare/#2767dc661d75
WHO. N.A. Addressing health system inefficiencies. Retrieved on 5-10-2018 from http://www.who.int/health_financing/topics/efficiency/system-inefficiencies/en/
Very interesting thoughts! I fully agree that especially the health sector is still lacking significant capabilities when it comes to leveraging technologies especially with regards to the utilisation of big data. However, I believe this is often caused by barriers imposed by governmental institutions, which are meant to protect patient data and privacy but also impedes a lot opportunities. Imagining the access to anonymised patient data in order to analyse symptoms, diagnosis and correct treatment would have tremendous effects on healthcare costs and efficiency – not mentioning the physical and psychological benefits for the patient. Specifically the health sector would increase its value and efficiency when creating information networks and leveraging its resulting effects. I am pretty curious in which direction this will go in the future!