Artificial Intelligence (AI) is already assisting humans in most of their daily routines, like dealing with emails, getting driving directions, or looking for movie recommendations. But what about AI in the healthcare sector? Is it a cost-effective solution in the long run, and what is the role of healthcare management in implementing AI programs?
Although at the moment there is currently not enough evidence on the cost-effectiveness of AI solutions, it is already possible to deduce the positive impact of AI on healthcare by looking at some of the potential benefits. As an example, human errors and healthcare-related adverse events occur in 8% to 12% of hospitalisations, whereas AI and machines have a margin of error of 3% (WHO, 2020). Therefore, using AI and, consequently, decreasing the percentage of human error can prevent more than 3.2 million days of hospitalisation each year in the EU, thus reducing the cost of care (Deloitte, 2015). Moreover, AI can also be employed for managing clinical documentation and medical records, which would result in saving 25% of time for nurses. It is estimated that 35% of UK jobs could be automated by AI over the next 10 to 20 years (Deloitte, 2015). However, AI systems will ultimately not replace clinicians; rather it will provide clinicians with more time to focus on patients and practices that draw uniquely on human skills (empathy, persuasion, big-picture integration).
The benefits of AI in the healthcare sector are promising, but questions remain on how to move from theory to practical implementation. Surely health managers are key players in this process, so how can they facilitate the implementation of AI programs in healthcare?
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References:
Deloitte (2015). From brawn to brains. The impact of technology on jobs in UK. [online] Available at: https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/Growth/deloitte-uk-insights-from-brawns-to-brain.pdf
[Accessed: 31 July 2020]
WHO (2020). Data and statistics. [online] Available at: https://www.euro.who.int/en/health-topics/Health-systems/patient-safety/data-and-statistics
[Accessed: 31 July 2020]