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Healthcare Analytics: How A.I. and blockchain can curb rising healthcare costs

The cost of insurance premiums for 2018 ACA policies rose between 17 percent and 32 percent compared to 2017.

Rajib GhoshBy Rajib Ghosh

The new year began with a surge in enrollment at Health Insurance Exchanges despite the Trump administration’s decision to cut by 90 percent funding of advertising for Obamacare and shortening the enrollment period to six weeks. In addition, Congress passed a tax reform bill at the very end of 2017, which included the removal of the tax penalty for individuals who chose not to buy health insurance. Insurance companies viewed this as a potential reduction of their healthy population pool, further skewing the risk profile of the population they cover. They cited that as a reason for insurance premiums to spike for everyone who buys insurance on the Affordable Care Act (ACA) marketplace.

The cost of insurance premiums for 2018 ACA policies rose between 17 percent and 32 percent compared to 2017 depending on the tier of the plan. For many people, the out-of-pocket cost was largely offset by ACA subsidies. Many others tried to get their coverage for 2018 locked in before the expected price spike occurred. Some stability did come back to the healthcare industry as the Affordable Care Act (ACA) repeal efforts were put on hold by the Republican-led Congress. Until that changes, the widespread fear of unfavorable Medicaid and Medicare reform possibilities have somewhat subsided.

Increase is Not a New Phenomenon

From a data standpoint, this year-over-year cost increase in health insurance is not unprecedented; it has been happening for quite some time. The cost of medical care delivery in the United States is ever increasing, and insurance premiums follow suit. Ongoing innovations in medical devices and new drug discoveries to tackle complex or previously untreatable diseases contribute to the higher cost of drugs and procedures year-over-year. For example, Hepatitis C used to be an untreatable disease but not anymore. Thanks to the groundbreaking discovery of Gilead Life Sciences, the disease is now curable but with a hefty cost of $94,500 for a 12-week treatment regimen. Recently, the FDA approved a gene therapy for the treatment of childhood blindness, but the cost of the treatment could be several hundreds of thousands of dollars according to some analysts.

There is no denial that such groundbreaking work of scientists and researchers has saved or extended the lives of many people, but it has also increased the overall cost for healthcare. That, in turn, led to an increase in the cost risk for insurance companies, and they responded by increasing their premiums. It is political posturing to blame all of the premium increases on the ACA, a program that brought 20 million Americans under the purview of health insurance.

While the increase in the cost of healthcare delivery is a large contributor to the increase in health insurance premiums, it is interesting to note that the policy tools used in ACA were able to curb the cost increase. Costs still increased but at a lower rate than before. Unless Congress applies direct price control on new drugs and therapies, insurance costs can’t be contained. On the other hand, microeconomic theories suggest price control acts as a serious deterrent for groundbreaking innovation. Therein lies the dilemma in this very complex industry. Can today’s technologies help?

There is no denial that groundbreaking work has saved or extended the lives of many people, but it has also increased the overall cost of healthcare. Photo Courtesy of | © everydayplus

There is no denial that groundbreaking work has saved or extended the lives of many people, but it has also increased the overall cost of healthcare.
Photo Courtesy of | © everydayplus

Key Contributors to the Healthcare Cost

Let’s consider new drugs that act as a big contributor to the overall cost in healthcare. In this scenario, pharma companies are usually painted as greedy and heartless corporations. In reality, big pharma companies are thousand-pound gorillas with billions of dollars of budget to develop and market new, lifesaving drugs that are protected by long-lasting patents. In 2016, U.S. pharmaceutical companies spent $59 billion in research and development. Most pharmaceutical companies aim to develop two to three drugs per year at a cost of about $2 billion, with a success rate of only 4.9 percent when the entire process from molecule identification to launch is considered. If pharma companies are not allowed to market their product at a high market entry price, there would be little incentives for those publicly traded companies to invest in drug discovery and development.

From discovering a potential drug in the laboratory to actually launching it in the market could take 10 years or more, following myriad steps, tests, data collection, monitoring, reporting and other regulatory hurdles. Once all of those are cleared, marketing a new drug requires an additional large investment. In a capitalistic society, for-profit companies don’t exist to serve altruistic motives, albeit in many cases they do demonstrate philanthropy in specific geographical areas. If the upfront cost to get a new drug to market could be reduced and market introduction could be expedited, that would incentivize the pharmaceutical companies to price their products at a more affordable level for the masses.

How A.I. Can Help Reduce Costs

In the artificial intelligence (A.I.) universe, a lot of conversation is currently ongoing regarding what futurists and A.I. scientists call “The Third Wave.” The “Second Wave” is where the technology is at currently, i.e., machine learning and deep learning based on statistical patterns in the data. Typically, a large and carefully selected and tagged training data set is required to train a deep learning algorithm to learn behaviors. Such algorithms are still useful when it comes to processing a large amount of clinical trial data sets captured via electronic data capture systems or from electronic health record systems as medical data is getting increasingly digitized.

As the technology matures and becomes smarter, the Third Wave A.I. systems will have the ability to test different hypotheses within a given context. This will potentially accelerate analysis of the variety and veracity of data at a speed that no human can ever match. New hypotheses can be tested with a high level of efficiency and accuracy during clinical trial periods that will reduce the overall time for drug trial and associated labor costs. Such software power will not come cheap, but just like computing power, the price will come down over time. A.I. systems and technologies will continue to become democratized by the big technology companies and research communities, making access to such systems and software cheaper. Early adopter big pharma companies such as GlaxoSmithKline, Merck & Co and Sanofi have started to explore and invest in this new technology-enabled paradigm.

Blockchain Can Also Help in Cost Reduction

Blockchain is the emerging tamper-proof digital ledger technology that can potentially have a major impact on drug discovery, data collection and the prevention of unforeseen shortages of critical drugs reporting. In addition, drug counterfeiting, which is a major issue for the pharmaceutical industry costing them $200 billion of losses annually, can be addressed with the help of blockchain technology.

With blockchain, patients can provide their medical data securely with the researchers working on the trial. The trust between data owners and data researchers and regulators along with the transparency of all data-access-related-transactions could eliminate the inefficient processes of today. That would lead to a cost reduction of drug discovery, development and distribution. An impressive example use of blockchain in healthcare is the MediLedger Project, which was launched in 2017 under the leadership of The LinkLab and Chronicled, Inc. The project brought together pharmaceutical manufacturers and wholesalers to design and implement a blockchain that would improve track-and-trace capabilities for prescription medicine.

As what happens with many groundbreaking technologies, the key use cases come from the government. This project was built to meet the requirements of the U.S. Drug Supply Chain Security Act (DSCSA) to support enforcement of the law, but it also led to efficiency improvement within the notoriously inefficient value chain. The workgroup will continue to explore such an industry platform, as well as launch a commercial solution that could ultimately transform the pharmaceutical supply chain.

If the healthcare industry does not receive further unforeseen shocks from the political front, I am very hopeful that the above technological advancement will change healthcare for the better. However, no change in this trillion-dollar industry will happen overnight. It will take time, patience and innovation that will continuously challenge the status quo.

Rajib Ghosh ( is the founder and CEO of Health Roads, LLC, a consulting company for enabling digital transformation in healthcare organizations. He has 25 years of technology experience in various industry verticals where he had management roles in software engineering, data analytics, program management, product management, business operations and strategy development. Ghosh spent a decade and half in the U.S. healthcare industry as part of a global ecosystem of medical device manufacturers, medical software vendors, telemedicine and telehealth solution providers. He’s held senior positions at Hill-Rom, Solta Medical and Bosch Healthcare. His recent work includes leading data-driven digital transformation in the public health space, including county-level healthcare agencies and organizations focused on underserved populations.

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