Thinking Out Loud About A New Approach To Digital Health Innovation – PART 2

JLNote To Reader - Today I’m publishing Part 2 of my blog series on digital health innovation. I published Part 1 of the series recently (and was then taken offline by a painful hard drive failure) and will publish the next piece sometime next week. I appreciate your thoughts, suggestions and feedback, so please feel free to comment below. Thanks for your time. JL

What Factors Are Limiting The Use Of Digital Technologies In Health Care Delivery?

In my previous post I argued that while there is a tremendous amount of excitement around digital health (signified by new company formations, investments, exits, etc.) very little of the innovation we’re seeing at the Health 2.0TedMedStanford/MedicineX conferences is making it into health care delivery “enterprise” environments (e.g. hospitals, doctors offices, etc.). What I learned from running the Health 2.0 Developer Challenge and pursuing my own startups is that the underpenetration of digital technologies in the clinical realm is a complex problem with many root causes.

Because the factors limiting digital health innovation (detailed below) are inextricably linked to the history, culture, financing, and organization of the health care industry I don’t think there’s ANY simple “silver bullet” solution that will dramatically accelerate digital health adoption in the short term.  That said, I do believe there are approaches that are working well and that can help us increase the pace of technology adoption, one of which I will detail in my next post.  I also think that by understanding the factors limiting adoption of digital health technologies, we can start to develop new and improved innovation strategies to accelerate progress.

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At a high-level the factors limiting digital health innovation can be broken into those impacting providers (doctors, hospitals, health systems, and academic medical centers) and those impacting innovators (companies creating new technologies to help providers deliver care more effectively):

Provider Facing

  • Fee For Service Is King – In my view, the dominance of the fee-for-service payment model in the United States is the single greatest obstacle to the adoption of digital health innovations in the delivery of health care.  In the fee-for-service model providers only get paid if they can bill a third-party payor for a service that has been previously assigned a reimbursement code.  While telehealth visits (telehealth being arguably the most commonly employed type of digital health technology) are increasingly reimbursed by Medicare, Medicaid and private insurers, few other categories in the digital health space are eligible for third party reimbursement.  Therefore, providers have little incentive to use or try digital health tools to deliver care more efficiently, despite the potential benefits to patients.  CMS (Centers for Medicare and Medicaid Services) and other payors are currently experimenting with new alternative reimbursement models such as the Shared Savings and Readmissions Reduction programs.  These new programs are driving provider organizations to seek out and embrace technologies that may not be reimbursable, but can help them maximize the financial results from these alternative payment arrangements.  In fact, one of the hottest areas in digital health is the “readmissions prevention” sector where dozens of startups are building technologies to engage patients, monitor them at home, and facilitate communication with providers with the goal of preventing readmission to the hospital.  As alternatives to fee-for-service medicine proliferate we will hopefully see greater demand for digital health technologies in the clinic.
  • Risk Aversion - The health industry, in general, is very conservative and for good reason – when you’re providing care to human beings you want to make sure you’re limiting risk and avoiding anything that could hurt a patient.  In the United States there is also the ever-present risk to providers of medical malpractice litigation which resulted in $3.7 billion in payouts to plaintiffs in 2013 .  Providers are generally averse to any technology that hasn’t been thoroughly validated and approved for use (except obviously for new drugs and devices being tested in clinical trials), which makes it difficult for new digital health startups that often have no evidence to support what they’re offering.   In addition to lacking evidence of efficacy, many digital health products and services are further hampered by limited functionality and it’s not uncommon to see applications marketed that have more than a few bugs.  In an industry in which products are expected to work perfectly there is very little patience for “beta” releases and unstable prototypes.  In health care it’s almost always better to be safe than sorry.
  • Organizational Complexity - Another issue that plagues providers and stifles digital health innovation is the organizational complexity of many academic medical centers (AMCs), hospitals, and hospital systems (the org chart for UT San Antonio Health Science Center is illustrative). The typical AMC is an amalgamation of a teaching hospital (or hospitals), a medical school (often associated with a major university), a physician professional service group, and various research institutes (among other things).  Each component of this unwieldy organizational structure generally has its own leadership (often with some overlap), its own mission, and its own priorities.  Coordination of these different entities to support a new digital health initiative can be difficult, if not impossible, particularly as the number of stakeholders increases.  Other sources of complexity include legal and regulatory review processes that may not be optimized to consider new digital technologies, and budgetary approval processes that must go through multiple levels of review.  Even well-defined processes are complicated and proceed at a glacial pace in the typical AMC.  For example, most digital health pilot programs launched at an AMC will require IRB (Institutional Review Board) approval prior to launch, a critical step for any research protocol involving human subjects, but this process can often take months to complete.  Many large provider organizations simply can’t move at innovator pace, which greatly constrains new technology experimentation.

Innovator Facing

  • Health System Access - In addition to being conservative the health care industry is also very insular, with a clear distinction between “insiders”, those who have been granted access (via licensure or certification) to the inner workings of the health care system (i.e. doctors, nurses, administrators, etc.), and “outsiders”, which is pretty much everyone else.  Digital health companies need to get “inside” the delivery system if they want to work on the biggest problems (remember, almost 60% of health care spending goes through providers), but getting inside the typical health system, hospital, academic medical center, physician practice or clinic, however, is really hard.  At large institutions (think health systems), just navigating the organization and finding a decision-maker can be really difficult.  At smaller institutions (think doctors offices) the decision maker is generally heavily defended by an array of gatekeepers.  I have found that unless you have privileged access to the “inside” of the system getting to your target customers can be a long, expensive, and painful process.
  • Understanding The Issues - The $3 trillion U.S. health system is wickedly complex and difficult even for insiders to understand fully.  Because of the complexity of the system and because accessing the inside of the delivery system is so hard, it can be difficult for innovators to get an accurate read on what problems need to be solved.  If they can get a sense of the problems, entrepreneurs sometimes fail to understand the subtleties of the health system, like hidden incentives and arcane regulations.  In addition, innovators often fail to collaborate with all the important stakeholders (think patients, providers, administrators, etc.) and miss key user insights.  As a result, innovators may develop solutions that don’t solve real problems or don’t solve them in a way that benefits the relevant stakeholders.  Unfortunately, many entrepreneurs are RIGHT NOW building products and services for customers who don’t want or need them.
  • Survival - Many entrepreneurs, particularly those coming from the “lean startup” world, don’t understand that success in the digital health space is more-often-than-not a long term proposition.  Digital health companies require significantly more runway to succeed compared to other types of startups and also therefore require more funding.  In digital health everything will take longer than you think and will cost you more than you expect: you’ll have to build more security and privacy features into your product, you’ll need to hire high-quality sales people with deep relationships to sell your product, those salespeople will need more time to sell to large enterprise customers, and you’ll end up doing more legal work to understand issues like HIPAA, among other things.  Fortunately, digital health companies are raising more money now than ever before, which should hopefully increase the chances that new digital health innovations make it to the market.

This list of reasons for why technology is not making into the delivery system is by no means comprehensive.  There are likely many other reasons that I missed and I invite you to add your own thoughts in the comments section below.  The point I’m making, however, is that digital innovation is constrained by a wide variety of limiting factors that will not be easy to overcome in the near term.

Next Up: Thinking Out Loud About A New Approach To Digital Health Innovation – PART 3 (Coming Next Week). In my next post I’ll talk about the most successful innovation program I ran during my time at Health 2.0 and the implications for other digital health innovation efforts.

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