Medicine is ripe for disruption. As David Lawrence, former Chairman and CEO of the Kaiser Foundation Health Plan, wrote in his 2005 book chapter Bridging the Quality Chasm:
The costs that result from poor quality trickle down to consumers and patients, who shoulder much of the burden of ever-increasing healthcare costs. In order to improve healthcare accessibility, the utilization of medical resources must be made more accurate, more efficient, and more secure.
Two cutting-edge technologies, in particular, show significant potential for elevating the use of data and other resources in the medical industry. These technologies are blockchain and artificial intelligence. By utilizing the latest advancements in these technologies, the medical industry can improve quality, bring down cost, and democratize healthcare like never before.
Here are four key ways in which the healthcare field can leverage blockchain and AI technology.
Originally developed for cryptocurrency in 2008, blockchain allows collaborating parties with competing interests to keep a tamper-proof, distributed, digital ledger.
As we have seen, the implications of this technology for finance are highly disruptive. However, the implications of blockchain in medicine are more subtle and far-reaching because they involve medical ethics including consent, privacy, and accuracy of clinical measurements, as well as financial transactions.
Blockchain isn’t only for financial transactions. It holds value for any agreement between two parties that needs to be auditable. In the legal profession, this means revolutionizing property law, notary public functions, and chain-of-custody. But for pharmaceutical companies worried about the burgeoning costs of clinical trials blockchain has value in smart contracts.
Potentially protecting patient anonymity, and even enabling profit sharing, smart contracts can make research results available without the bias of human data collection and data analytics.
Today’s most cutting-edge AI programs are capable of “contextual normalization,” which allows them to simultaneously generate and test new hypotheses by analyzing complex sets of biological data. AI holds significant promise for innovation within the healthcare industry, particularly in a pharmaceutical context.
AI is significantly increasing the variety and breadth of data that is analyzed during the course of drug research and development. Furthermore, AI accelerates the rate of analysis to speeds unattainable by human researchers. Today’s AI is also capable of generating and testing novel hypotheses with greater efficiency, which enables more accurate, efficient, and timely clinical trials.
Improved data analysis in pharmaceutical R&D means higher success rates, more innovation, and more affordable drugs for patients. Major companies such as Merck & Co. and Johnson & Johnson have already been investing in AI-driven innovation, and others are sure to follow.
There is increasing divergence between the convenience of consumer software such as mobile phones and the achingly inefficient and out-of-date software that is sold to hospital systems at an enterprise level.
