The Health Tech Economy

In an earlier post I introduced the idea that information gaps created by EHRs threaten to undermine the strategic position of many health tech companies. In this post I expand on this idea by illustrating the current state of the health tech economy, and highlight the different ways in which companies depend on access to EHR-derived data. In the interest of giving credit where credit is due: I’d like to acknowledge that this post was inspired by Chris Dixon’s excellent overview of the Internet Economy.

As with internet businesses, understanding a health tech company’s strategic position requires an understanding of 1) how the company generates revenue and 2) how those products relate to other products along the entirety of the loop. The following diagram illustrates a typical clinical encounter, which begins when a patient decides to seek medical attention and ends when:

1. the patient and clinician mutually agree that the issue has been addressed,
2. the patient abstains from further treatment and/or evaluation, or
3. the responsible clinician ceases to offer the patient further treatment and/or evaluation.

Until one of these three events occurs, the entire cycle may repeat itself an infinite number of times.

A few notes about this diagram:

• The diagram includes a sampling of companies operating in the health tech economy. It is not meant to be a comprehensive listing of all players in the space — Rock Health and Crunchbase offer a far more comprehensive overview of the competitive landscape.
• A company’s position along the loop is a reflection of information available through public outlets (e.g. company websites, press releases, blog posts). Some companies, such as EHR vendors, have multiple product lines spanning multiple segments of the loop (not shown).
• I’ve collapsed many ancillary loops under the heading “function-specific loops.” The billing and claims loop is the most mature — and most important — of the ancillary loops. It translates clinical and administrative data (from EHRs and Revenue Cycle Management software, respectively) into ANSI X12 transactions — the mechanism by which health insurance claims are submitted, eligibility is verified, and pre-approvals are obtained.
• Conventional last-mile fulfillment (LMF) differs from tech-enabled LMF in that the latter relies on software as the primary means to scale the delivery of health care goods and services. By comparison, conventional LMF scales through hiring and uses software primarily as a means to manage human resources. Another key difference is that, for the most part, tech-enabled LMF companies do not rely on the billing and claims loop to collect payment for goods and services. Instead, they collect payment directly from patients or employers.

Key observations

• Consumer wearables and digital health companies live on islands. The good thing about being on an island is that these companies do not depend on clinically-derived data to build a great product. The drawback is that they lack access to a patient’s clinical record, which means that it’s exceedingly difficult to build features and apps that are personalized, actionable, and accurate. One way to overcome this obstacle is to ask individuals to enter the information directly into the device/app, but this strategy has not worked well in the past.
• The notion that the patient is “the” health care consumer is a myth. That’s not to say that patients don’t have a say in purchasing decisions — we can clearly see that patients decide when and where they seek care. Even so, employers influence where 66% of non-elderly adults get their care through the types of health insurance they offer their employees. Health insurers, in turn, steer patients toward certain clinicians (“in network”) and away from others (“out of network”). In all cases, clinicians ultimately control much of what gets purchased in all layers downstream of where they sit in the loop. This is because most health insurance will not pay for goods and services unless they are ordered or rendered by a trained and licensed doctor, nurse practitioner, or physician assistant. As a result, there is no such thing as a health care “consumer” — there are only stakeholders with varying degrees of purchasing authority.
• Clinicians are the most influential players in the loop. This follows from the observation that health benefits managers, insurance companies, and comparison-shopping websites derive their insights from claims data. As illustrated above, health care claims are derived from EHR data, which means that clinicians can exert control over this segment through a feedback loop. This is noteworthy because it effectively gives clinicians strategic leverage over the entire health tech economy.
• EHR companies are a direct threat to companies that sell function-specific products. Indeed, the top EHR companies make no secret of their intent to develop products that compete with those downstream. Some are already making their way onto the market, including care coordination products from Cerner, athenahealth, and Epic just to name a few.
• Tech-enabled LMF companies need to develop strategic partnerships with clinicians in order to maximize growth. In the current environment, clinicians have the potential to function like lead gen engines for tech-enabled LMF companies. Just food for thought.

The landscape is always shifting, and this is just a snapshot. In my next post, I’ll explore how data engineering decisions influence a company’s ability to adapt to shifts in the health tech economy.