The companies that close Series A rounds in digital health are not always the ones with the most impressive seed decks. They're the ones that, 18-24 months after their seed, have answered the specific questions a Series A investor needs answered. Those questions are predictable. The path to answering them is not mysterious. But a surprising number of digital health companies spend their seed capital on the wrong things and arrive at Series A with strong technology and weak evidence that the technology matters.
This is a framework based on what we've seen work across the portfolio companies we've backed or closely watched through Series A processes. It's not universal — biotech operates on a completely different timeline and capital structure, and some digital health sub-sectors have faster paths than others. But for the core enterprise digital health case — software or software-enabled devices selling into health systems or payors — the 24-month structure holds fairly consistently.
Months 1-6: Validate the problem before you validate the product
The most expensive mistake in digital health is building before you understand the exact workflow you're inserting into. Not the general problem — you already know that. The specific workflow. Who touches the patient at what point in the care process? What system are they working in? What are they doing immediately before the moment you want your product to create value? What happens immediately after?
This is clinical discovery work, and it requires being physically present in clinical environments. Not surveys. Not phone calls with clinical advisors. Shadowing. Observation. Watching nurses during a shift change. Sitting in on morning rounds. Talking to the charge nurse about what the last software implementation broke. This work takes 2-3 months and produces insights that can't be extracted from market research reports.
Most seed-stage digital health companies haven't done this. The ones that have almost universally use it to significantly revise either the product or the target buyer. Both revisions are valuable. Discovering them at month 4 of a 24-month runway is vastly cheaper than discovering them at month 18.
Months 6-12: A real pilot with clinical rigor
The pilot definition matters a lot. A "pilot" that means "we have access to some patients and we're collecting anecdotes" is not a pilot. A pilot is a time-bounded, defined-scope deployment with specific inclusion criteria for patients, defined clinical workflows, documented outcome measurement, and clear success metrics known to both parties before it starts.
This is hard to negotiate with health system partners at the seed stage, and many founders settle for looser arrangements because the clinical partner doesn't have time for rigor. Push for it anyway. The evidence package from a rigorous 6-month pilot with 150 patients and documented outcomes is worth 10x the evidence from an open-ended deployment with vague metrics. Series A investors know the difference.
The outcome metrics matter. At minimum: user adoption rate (what percentage of eligible patients enrolled?), retention rate (what percentage completed the program?), and at least one clinical endpoint relevant to the patient population. If you don't have a validated clinical measure yet, start using one now. PHQ-9 if you're in behavioral health. A1c if you're in diabetes. NYHA class or a validated symptoms scale for cardiovascular or pulmonary disease.
Months 12-18: First commercial contract and proof of repeatability
The seed pilot needs to convert to a paid commercial contract. This sounds obvious. A remarkable number of companies have free pilots running 18 months after they started without a clear path to payment. If your pilot partner isn't willing to pay after 12 months of deployment, that's a signal worth examining honestly. It might mean the evidence isn't there yet. It might mean the budget process requires more lead time. It might mean this isn't the right buyer type for your go-to-market motion.
The second contract matters as much as the first. An investor pattern-matching on digital health Series A knows that health system contracts are highly individual — the champion, the budget cycle, the competitive dynamic, the patient population all vary. One contract is an anecdote. Two contracts, particularly with different buyer profiles or in different geographies, starts to look like a repeatable motion.
If you can close a second contract with a buyer type that's meaningfully different from your first — say, a large academic medical center if your first was a regional health system, or vice versa — that's strong signal. It tells investors the product can travel, not just perform in a single context.
Months 18-24: Build the Series A story, not just the product
A lot of founders treat the 6 months before a Series A raise as execution time. It is execution time, but it's also narrative construction time. By month 18, you should know what the Series A story is. What is the specific question you've answered with the past 18 months of work? What do you know now that you didn't know at seed? What does the investor see in 24 months of operation that they couldn't have seen on day one?
The clinical evidence dossier should be packaging-ready: a clean summary of the pilot results, methodology, and key metrics that can be shared in diligence. If you've published or presented at a clinical conference, include that. If you have Letters of Intent from additional health systems pending the Series A close, include those too.
Start investor relationship development at month 15, not month 22. The best Series A deals in healthcare rarely close with investors who met the founders two months before term sheet. The relationship — and the investor's understanding of the clinical market, which takes time to build — matters for getting to conviction. Give investors the runway to do that work on their own schedule.
The 24-month roadmap isn't a guarantee. But the founders we've backed who followed something like this structure arrived at Series A conversations with answers to the questions we were going to ask. The conversations moved faster and the terms were better. That's not a coincidence.
Digital health is hard in ways that are specific to healthcare — the buyers are slow, the evidence bar is high, the regulatory complexity is real. The companies that succeed don't move faster than the constraints allow. They move deliberately within them and build evidence that makes the next step less uncertain than the last one. That's the roadmap.
