Prologue
There's a pretty reasonable line of thinking among new entrant provider groups that goes something like this: "Population X is poorly served by incumbent providers for reason Y. Our new Care Model Z overcomes Y and serves X far better than the rest, so we will win." It’s a radically simplified telling of the tale, but you get the point. It makes sense and proof points abound.
Over the last two years, as investment in software-enabled care delivery startups has soared, we’ve met with hundreds of teams and learned that Care Model Z is the hero of the story.
Here's the thing, though — the competitive advantage that will separate wheat from chaff, as they say, is not any given care model, but care model-ing as a core competency.
What follows is a three-part series that dives into the challenges startups face when defining an initial care model and growing the competency of care modeling, navigating vital decisions around your technology strategy, and standing up your tech infrastructure.
In Part I, we introduce the seven elements of care modeling: Patient Sourcing and Intake, Ongoing Interaction Modes and Utilization Policies, Diagnostic Range and Inputs, Scope of Interventions and Safety Framework, Care Team Composition and Sourcing, Content and Automation, Pricing and Payments. These seven elements are the building blocks of any care model and inform investment decisions in tooling, teams and processes.
In Part II, we clarify the terms “system of record” and "headless EMR" before laying out four strategies for approaching buy vs. build decisions. This is a high-level cheat sheet to help you plan your infrastructure investments and select your technology partners.
In Part III, we conclude with a set of trade-offs to weigh as you dig in and start choosing technology partners to build your tech stack with, before offering some final thoughts.
As some have observed, not all startup leaders appear ready to describe their care models in public. That's partly due to healthy competitive paranoia. A more fundamental reason is that no system or standard exists for defining care models, let alone deploying, monitoring, and improving them in the wild with real patients. Our intention is to offer our perspective as a place to start.
