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Healthcare Analytics — 2017: The year of ambiguities, AI and blockchain

Despite legislative and budget cuts, the pace in innovation in healthcare is not going to slow down.

Rajib GhoshBy Rajib Ghosh

In my first column of the new year I usually summarize what happened during the previous year in terms of healthcare technology and analytics. 2017 was a very interesting year for healthcare. On the political front, we saw continued assault on the Affordable Care Act, aka Obamacare, the signature legislative accomplishment of the 44th president. Interestingly, the premise for the “overhaul” is to make healthcare more affordable for the country’s rank and file. The average premiums of health insurance plans in exchanges are due to increase by about 27 percent in 2018. However, the annual tax subsidy for qualifying individuals will also increase to help defray the cost.

Meanwhile, the number of plans available for people to purchase in the health insurance marketplace was reduced due to several insurance companies pulling out of the exchanges, especially in rural areas. Rising prices of premium and lack of options became the catalyst for a series of ACA alternative bills that came out of Congress in 2017, none of which won the hearts of the people. Despite much debate and many attempts to “repeal and replace” Obamacare, no such bill passed through Congress. Nevertheless, the ACA could be further damaged by the proposed tax bill, which would remove the individual penalty for not having health insurance.

The ACA is far from perfect; it is an intricate piece of legislation and taking any of the legs out might crumble the whole structure. By the time this column is posted, we should know what happened to the tax bill . . . and what future awaits the ACA in 2018 and beyond.

Lots of Macro Ambiguities but Innovation Still Strong

In a nutshell, 2017 for healthcare was a year of utmost ambiguities. It took almost seven years to align our ailing healthcare system with the needs of the future – driving patients to more low-cost care delivery options rather than high-cost ones, i.e., from emergency rooms to the primary care clinics and community-based services. During the last five years, we have seen the emergence of two major payment model shifters: accountable care organizations (ACO) and value-based purchasing. Population health management took the center stage while care coordination became the mantra for many health systems and healthcare institutions.

Those of us who are in the business of healthcare know how difficult it is to shift the closed-door hospital boardroom conversation from “get a head in the bed and maximize revenue” to keeping patients away from hospitals in exchange of shared savings. This wasn’t an easy change and there is much more work to do to promote such a model of care nationally. But health systems across the country, driven by Centers for Medicare & Medicaid Services (CMS) and leading payers, are slowly but surely getting used to the change. The past year put the brakes on the nascent momentum of this movement, but the train is still moving albeit at a slower speed. Since healthcare is a major employer and represents a big chunk of the economy, more ambiguities in 2018 and beyond can potentially trigger a downturn or even a recession of the broader economy.

Artificial Intelligence is Arriving Rapidly

In 2015 and 2016, “predictive model” and “machine learning” were two of the biggest buzzwords in the industry. Healthcare analytics was just emerging from the bottom of the analytics pyramid with “descriptive analytics,” which essentially means “after the fact” reports and dashboards of key performance indicators (KPIs). Mathematical models to identify future hospitalization risks among the “high utilizer” patient population were among the first few use cases that evolved to address the penalty clause of the 30-day bundle payment and shared saving programs, two payment reforms triggered by the ACA. In 2017, the floodgate seemed to have opened for innovations and investments in artificial intelligence (AI) systems. More than $1 billion was invested in healthcare analytics, including $200 million in AI during the first nine months. The hype was caused by technological advancements in AI and fast computing achieved by Google, Facebook, Microsoft and IBM. Google’s deep learning technology stack started an avalanche of AI system development, by startups as well as by established companies. Accenture predicts that adoption of AI in healthcare will lead to about $150 billion in annual savings in U.S. healthcare by 2026. (Many of the use cases Accenture identifies have been discussed in this column during the past year.)

I am a firm believer in Roy Amara’s law, which states that we overestimate technology in the short term and underestimate in the long term. Despite the current hype around AI in 2017, which might not produce immediate impact, I think AI in healthcare will become a game changer in the next five years (Figure 1). In addition, we are in an early cusp of user interface (UI) transformation; form-based UI will give in to natural language and AI-powered voice and voice-text-hybrid UI. Interaction models will have to be rethought by designers; the process has just begun.

Figure 1: AI, machine learning and blockchain-type cycle 2017. Source: Gartner

Figure 1: AI, machine learning and blockchain-type cycle 2017.
Source: Gartner

Blockchain Made Strides into Healthcare

2017 was also the year when blockchain became a steady conversational stream both within large insurance payer organizations, as well as in healthcare-focused VC-startup ecosystems. Blockchain is a decentralized P2P architecture of trust network. Based on an IBM survey of 200 healthcare executives, 16 percent of respondents expect to have a commercial blockchain solution in 2018. Blockchain can solve the data interoperability problem if a public healthcare version can be developed. A new company called Skychain is claiming that its blockchain-powered medical AI network can beat IBM Watson by allowing it to host “pluralism of multi-institutional knowledge” in its network versus Watson’s single institutional knowledge base. It is too early to comment on this claim. However, we need to keep an eye on blockchain’s impact on healthcare since it might change the entire foundation for analytics programs in the future.

While I believe the onslaught on healthcare will continue in 2018 from various legislative measures and budget cuts, the pace in innovation in healthcare is not going to slow down. After seeing the recent enthusiasm among start-up healthcare companies despite the chaos, I have reason to believe that healthcare technology and analytics will not only survive but thrive despite the current environment. The train to change healthcare has already left the station, and it is on an irreversible track.

Rajib Ghosh ( is an independent consultant and business advisor with 20 years of technology experience in various industry verticals where he had senior-level management roles in software engineering, program management, product management and business and strategy development. Ghosh spent a decade in the U.S. healthcare industry as part of a global ecosystem of medical device manufacturers, medical software companies and telehealth and telemedicine solution providers. He’s held senior positions at Hill-Rom, Solta Medical and Bosch Healthcare. His recent work interest includes public health and the field of IT-enabled sustainable healthcare delivery in the United States as well as emerging nations.

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