Technology-led innovation in digital health: The law of inverse relationships
Digital health solutions, especially those built on emerging technologies, face a conundrum of high investments and low returns in the near term. Crossing the chasm requires an understanding of key market factors.
While researching for my upcoming book, I asked the nationally recognized CIO of a health system what he thought of the market for emerging technologies such as AI, cognitive, blockchain and digital health solutions in healthcare. His response was: The teacher is ready, but the student is not.
What he meant was that the technology vendor community is developing innovative solutions at a faster rate than the ability of the healthcare sector to adopt it.
It’s no secret that healthcare IT is a couple of steps behind other sectors such as banking and retailing. I have been keenly noting the seeming contrasts in the outlook for healthcare IT when I speak with healthcare industry executives and technology providers.
Here are some examples:
- Healthcare policy uncertainty is taking a toll on discretionary spending in IT. However, VC funding for digital health funding has been on a tear this year.
- While VC-funding for digital health has been robust, most of the money is going to a select few companies.
- The select few companies that are cornering VC money are in no way guaranteeing a successful exit for their financiers. Witness some of last year’s stars that look like dogs this year — such as the wearables market, which saw one major company reportedly on the verge of folding and another major player effectively pulling the plug on their program.
- For all the noise about emerging technologies such as AI, cognitive and blockchain, the top clinical IT priorities are IT security and electronic health records (EHR).
So what gives? At one level, it’s the old story of hype exceeding reality for early-stage technologies. While larger health systems are making progress in experimenting with new technologies and use cases (read my earlier blog on AI in healthcare), the vast majority of the healthcare providers are focused on optimizing EHR systems, as per the findings of the 2017 Leadership and Workforce Survey by HIMSS. The bulk of the available IT budget is going towards business as usual (BAU) activities. This is not surprising; given the millions (billions) of dollars spent in the past few years on implementing these systems, health system CEO’s are keen to maximize the returns on their investments before looking at a shiny new object.
I call this the law of inverse relationships in technology-led innovation: The more the noise, the less the funding it’s actually getting. Generally speaking.
The HIMSS workforce survey validates this by indicating that there is a “remarkable disconnect” between vendors and healthcare providers on IT providers on EHR as a priority for health systems. Moreover, hospital and non-hospital providers diverged on their business priorities, which flowed through into IT priorities as well. Not surprisingly, vendors seemed to be more aligned to the priorities of hospital providers than non-hospital providers. (The HIMSS survey confirms the yawning gap in IT focus between the hospital and non-hospital providers while suggesting there may be a latent “hunger” for IT solutions among some non-hospital providers.)
Some of this can be explained by the overall structure of the healthcare industry. Of the 5,500 or so hospitals in the U.S., a small percentage (10% or less) are considered target customers for most technology firms. These would be typically large academic medical centers, national health systems or multi-hospital systems that have the budgets and the profit margins to support innovation programs. Non-hospital facilities such as ambulatory care and long-term care are not in the consideration set. The target market shrinks even further when it’s a question of emerging technology solutions.
This poses a challenge for technology vendors, especially those trying to sell innovative technology solutions in a technology environment effectively ring-fenced by EHR vendors ( I refer primarily to healthcare providers; the payer and life sciences markets have a different set of dynamics). A basic assumption in validating the market opportunity is that the target market segment has the propensity to spend on IT solutions and has a dedicated IT function to manage the spend. This assumption is not necessarily valid for a large part of the healthcare provider sector, which results in a relatively low market size and consequently low penetration for advanced technology solutions in the bigger picture.
The near-term implications of these trends are:
- Slow adoption rates for emerging tech and digital health innovations, which will force many young companies to close down as they run out of funding before they can establish a sustainable revenue model.
- Enterprise-level innovation programs will be at risk if new solutions and ideas fail to gain traction quickly enough. Failed initiatives will have a very hard time recovering from setbacks, with implications for ongoing funding support.
- Technology risks arising from immature products; lack of integration with systems of record resulting in increased costs and workloads; and IT security issues related to aggregation and integration of data from an increasing variety of sources.
A big question that arises in this context is: Who pays for all this innovation? In the current structure of the healthcare economy, it is critical for technology-led innovation to be aligned to revenue models for users. In other words, if a technology solution is not covered by a fee-for-service arrangement between a provider and a payer, there needs to be an ROI model that starts to pay off in a relatively short period.
Like the one ring to rule them all, it boils down to this: alignment between vendors and users on the costs and benefits of technology-led innovation.
The good news is that many solutions are indeed crossing this chasm (and are being wooed with more VC funding as a result). The use of advanced analytics models in population health management and the use of mobile-enabled applications for improved patient engagement are two areas where the benefits have been sufficiently established to provide momentum for growth. As more and more use cases go mainstream, we will see the adoption curve climb, especially as the newer solutions get tightly integrated into “core” transaction processing systems. As the Queen would say, keep calm and carry on.
Originally published on CIO