If ever there were an industry that could reap the benefits of AI, it is healthcare. The adoption of this technology to actually make medicine better is obvious. However, with this adoption comes a slew of ethical issues.
Let’s start with some numbers: In 2018, the US spent $3.65 trillion on healthcare. That works out to $11,121 per capita, a 4.4% increase over 2017. In addition:
- Spending on hospitals, doctors, and other clinic services was $2.16 trillion, holding steady at 59% of total health care spending.
- The spending category that experienced the most substantial year-over-year increase was the general cost of administering health insurance, which rose 7.7% in 2018.
- Spending on prescription drugs purchased in retail pharmacies went up 3.3% in 2018, higher than the 0.4% rate in 2017.
- A majority of the more significant spending totals were due to higher overall prices, while the “use and intensity” of health care services played a smaller role.
The per capita spend in western economies, other than Switzerland, which was about 80%, was 50% or less. The worse news is that the US has slipped to 36th in the world in quality of healthcare. (The above data is from Centers for Medicare & Medicaid Services and CIA World FactBook.)
Another lesser-known statistic is the magnitude of iatrogenic disease. From Wikipedia: an iatrogenic disorder occurs when the deleterious effects of the therapeutic or diagnostic regimen causes pathology independent of the condition for which the regimen is advised.
In other words, they are harmed by medical practice. According to a Johns Hopkins study, 251,454 deaths stemmed from a medical error – making it the third leading cause of death in the US, just behind cancer and heart disease.
All industries are facing the problem of which areas to apply AI. In an article in Healthcare IT News, some advice for the healthcare industry was: while AI may have the potential to discover new treatment methods, the report finds strongly entrenched ‘ways of working’ in the healthcare industry that are resistant to change. The authors warn that ‘simply adding AI applications to a fragmented system will not create sustainable change.’ Good advice for any industry.
To continue this: http://bit.ly/2lUwsZj