While these deals did not come as a surprise to most of us in the health sector, given that big technology companies have been vying to gain access to medical data, they raised some concerns not just among end users but also among policymakers and regulators, notably in the US, regarding how health data may be used.
Google is just one example of major technology companies that is moving beyond its core business and focusing on healthcare. Apple and Amazon are also getting into this potentially lucrative game. A global health expenditure study reported that spending on healthcare worldwide reached US$8 trillion in 2016, of which 41.7 percent was in United States alone.
By 2050, projections show that this figure will almost double. While healthcare costs are escalating and health has become a major political issue, if not the topmost concern of voters, companies are recognizing the huge opportunities that they could exploit by disrupting the sector through digitalization, bringing down costs and potentially improving value for money.
These major technology platforms, however, have two problems when it comes to healthcare: data acquisition and the very nature of the healthcare sector itself.
These technology platforms all have high fixed and development costs but low variable cost in their operations. They are dependent on data. As such, they resemble pipelines but with data – what is often called “the new oil” – flowing through. This puts governments and other custodians of medical data in a difficult position as to how best to use this information to drive costs down but at the same time preserve privacy and confidentiality.
Health data is becoming more attractive not only to big tech companies but also to cyber attackers. The health sector now has the second highest number of breaches compared to other sectors, higher even than banking and government. This should not come as a surprise, considering how comprehensive medical records are – from demographics and financial data to the most sensitive clinical information.
The second challenge for digitalization of healthcare is the sector’s uniqueness. Working in it requires a great deal of sensitivity and empathy. While an AI algorithm may diagnose cancer in the patient, a human is required to comfort and assure the patient and to deliver the prognosis and treatment of choice. A host of issues may be involved including the question of liability if something goes wrong – is it the responsibility of the practicing clinician, the service providers, the centers for disease control, or the company that developed the diagnostic algorithm?
What the best practices are is not clear. Health ethicists and regulators could provide ground rules. But digitalization may well open unanticipated cans of worms. Moreover, health care systems are complex, with many non-aligned elements along a large value chain, often lacking standardization and set processes. In an environment where there is more tacit than explicit knowledge and significant variation in practice and outcomes, it is difficult to apply specified processes and algorithms as intelligently they could be. In other words, merely importing and applying ready-made tools in healthcare is not possible. As healthcare analysts Carl Macrae and Kevin Stewart put it, ”patients are not aeroplanes, and hospitals are not production lines”.
There is a plethora of other issues that need to be overcome such as data privacy, legal principles, royalties and other payments before there can be a full-scale diffusion of digitalization. The potential is there – and it is huge. But the disruptions are across the board and the many players involved are not yet ready for them.
Some years ago, I discussed these challenges with Aetna’s chairman and CEO at that time, Mark Bertolini. He was getting his company ready for the dramatic changes – the disruptive innovations – that are now happening, ushering this new age for payers (a health maintenance organization, insurance firm, management services provideer, or any other entity that pays for or arranges for the payment of any health or medical care service, procedure or product). The mantra of the day: “We need to creatively destroy our business to improve health”. Aetna, an insurance company, sought to evolve into a healthcare enterprise by managing health rather than risk and by activating end users into individuals with personalized data and personal care needs. While all this made perfect sense, the biggest challenge was how to achieve this transformation in practice.
Several years later, after the US Department of Justice blocked its merger with health insurance giant Humana, Aetna was acquired by the retail and healthcare company CVS. In his book Mission-Driven Leadership: My Journey as a Radical Capitalist, which was published last year, Bertolini explained the rationale behind this surprising move.
Among the many reasons he cited, one of the main drivers was that, in the age of data-driven healthcare where individuals will be empowered by their personal data and demand more personalized care, payers would need a more consumer-oriented approach and broader reach to consumers than they currently have.
CVS, known widely in the US for its chain of pharmacies and stores, seemed a logical go-to partner to achieve this deeper penetration into communities and to enable this new model of business. They would do so by translating the knowledge from data into more personalized care for customers.
Digital technology disruption fueled by health data is not just happening in the US. In China, Ant Financial, the parent company of Alipay and the highest-valued financial technology, or fintech, company in the world, is making a big push into healthcare. These days not only that you can use Alipay to schedule a hospital appointment, but millions of health insurance contracts are now digitalized through blockchain technology.
These transformations not only reduce the cost of transactions in the health sector by significantly reducing the tedious and lengthy cycle of claims management and reimbursement, but they also minimize potential fraud and abuse. They improve patient experience through more efficient use of their data.
Another example is China’s Ping An group, the biggest insurer in the world with 393 million claims a day – 140 billion claims a year involving 196 million customers. They integrate all of this data into several ecosystems with 575 million users. AI-driven data analysis can improve disease screening and diagnosis, as well as disease incidence prediction, leading to better outcomes and lower cost per member. The ability of Ping An to apply AI tools to the vast amounts of data it accumulates gives the company a significant competitive advantage.
What these examples demonstrate is that health data and digital technology will be major transformation forces in healthcare in the next decade. It is not yet clear which areas of the value chain will be mostly affected. While digitalization is certainly not a panacea for healthcare, initial indications are that the expected and unexpected disruptions are likely to result tremendous benefits for patients and customers.