Clinical strategy is the plan that links a real clinical need to your product, your evidence, your regulatory path and the buyer who will pay for it. In a digital health company, it is the work that decides whether clinicians use the product, whether health systems buy it and whether investors believe it can scale. This guide walks through each part in the order a founder meets it, with U.S. sources for every rule and framework.
TL;DR
- Clinical strategy means understanding the clinical need, designing how the technology meets it, and keeping the roadmap tied to impact. It is related to product strategy but not the same thing.
- Define one consequential clinical problem, in one workflow and one care setting, before you define features.
- Build an evidence plan that matches your product, risk level and stage, and revisit it as the product matures.
- Check early whether your software falls under FDA device policy, and plan privacy, cybersecurity and interoperability alongside the product.
- Buyers and investors look for the same things: an institutional problem, a payment model, workflow fit, engagement and ROI.
Table of Contents
- What clinical strategy means for a digital health company
- Start with a defined clinical problem
- Build an evidence plan that fits the product
- Know where FDA and other U.S. rules apply
- Fit the product into clinical workflow, privacy and interoperability
- Connect clinical value to a payment pathway
- How investors and boards can read a clinical strategy
- Our perspective
- Work with a clinical leader on your strategy
- A practical order of operations
- FAQ
- Sources
What clinical strategy means for a digital health company
One account of the chief medical officer role in a health tech startup describes clinical strategy as three linked jobs: understanding the fundamental clinical need, designing how the technology addresses it in a meaningful way, and working with technology and product teams on a roadmap that keeps driving impact.
The same source separates it from neighboring responsibilities, which is useful because founders often blur them:
- Clinical leadership develops care protocols and direction.
- Clinical outcomes defines impact metrics and the studies that measure them.
- Regulatory work addresses FDA clearance or approval where it applies.
- Stakeholder engagement connects the company with clinicians, customers, investors and key opinion leaders.
Clinical strategy sits above these and gives them a common direction. It is also distinct from product management. A physician writing on embedding clinical and product teams as peers argues that both should work together through ideation, roadmapping, development, deployment, testing and iteration. Clinical strategy informs the product roadmap. It does not replace the person who owns it.
A useful test: if your clinical lead is only reviewing content or answering safety questions after decisions are made, you have clinical input, not clinical strategy. Strategy shows up before the roadmap is set, in the choice of which problem to solve and for whom.
There is also a question of timing. A 2022 essay on clinical leaders in digital health makes the case for placing clinical leadership in a founding role, so that product design, marketing and regulatory compliance rest on clinical and ethical standards from the start. Retrofitting those standards after launch is slower and usually more expensive. If your team has a gap here, our piece on closing clinical leadership gaps in healthtech startups covers how to spot it.
Start with a defined clinical problem
Most weak clinical strategies fail at the first step: the problem is described as a market category ("remote care," "AI triage") rather than a specific clinical situation. A strong problem statement names four things.
- The clinical problem. What is going wrong today, and how consequential is it?
- The user. Which clinician, care team or patient group acts on your product's output?
- The care setting. Ambulatory clinic, emergency department, inpatient unit, home, payer care management?
- The outcome. What changes in patient care, clinician time or cost if the product works?
The RIVU-AI framework, published for prediction models and decision support, puts the standard plainly: the tool should address a consequential unmet need in current practice and support feasible action within a defined clinical workflow. Both halves matter. A model that predicts something interesting but triggers no realistic action is a research result, not a product.
A quick worksheet
Before you write another feature spec, answer these in one sentence each:
- What decision or task does a clinician make today that your product would change?
- What happens, clinically, when that decision is made poorly or late?
- Who owns the cost or benefit of improving it?
- What would you measure to show the change?
If you cannot answer the third question, you have found your next piece of work. Clinical value and economic value need an owner, and they are often different people.
This step overlaps heavily with finding a market that wants what you build. If you are still testing that, our founder's guide to product-market fit in healthcare goes deeper, and a plain-language explanation of product-market fit is a helpful refresher for non-clinical teammates.
Build an evidence plan that fits the product
Evidence is where clinical strategy becomes visible to outsiders. The mistake is treating it as a single study run once. Guidance from the Digital Therapeutics Alliance notes that an evidence dossier may include clinical evidence, real-world evidence, health economics and outcomes research, and implementation pilots, and that evidence should be fit for the product's intended use, patient population and context.
Two frameworks help you plan across time:
- The Digital Therapeutics Real-World Evidence Framework proposes four iterative phases: design, develop, test and monitor. The authors argue for this because digital interventions are complex and dynamic, so evidence generation should continue across the product lifecycle.
- The Digital Medicine Society describes an Integrated Evidence Plan as a dynamic framework that aligns what regulators, payers, providers and patients each need, which helps allocate resources and supports commercial adoption.
The society's stage-based material adds that effective clinical strategy integrates clinical, real-world, economic and patient-centric data across the product lifecycle to meet stakeholder needs.
How the plan changes by stage
| Stage | Typical evidence question | Typical activity |
|---|---|---|
| Concept | Is the clinical problem real and consequential? | Clinician interviews, workflow observation, literature review |
| Prototype | Can users complete the intended task safely? | Usability testing, small pilots in a defined setting |
| Early commercial | Does it improve a measurable outcome where the buyer owns the benefit? | Implementation pilots, outcomes tracking, early real-world data |
| Scale | Does the effect hold across sites, populations and payers? | Larger real-world studies, economic analysis, ongoing monitoring |
This table is our working model, not a regulatory standard. The point is that the evidence question changes as the company grows, and each stage should leave you with something a buyer can read.
A16z's analysis of virtual care adds an important widening of the lens: clinical rigor should cover the end-to-end care model, not only an intervention's study design. That includes reliable delivery of high-value care, patient experience and continual improvement. For software companies, that means evidence about how the product is used in practice, not only whether the algorithm performs in a dataset.
Know where FDA and other U.S. rules apply
Regulatory questions belong in clinical strategy because they shape what the product is allowed to claim and how it must be built. Three areas come up most often for U.S. software companies.
Clinical decision support
FDA's guidance on clinical decision support software explains that certain functions are excluded from the device definition only if they meet all four statutory criteria, including enabling healthcare professionals to independently review the basis for the recommendations. Functions that do not qualify stay subject to FDA's device policies. The practical consequence: how your interface shows its reasoning is a regulatory decision as much as a design one. We cover the documentation side in 6 documents FDA reviewers want for clinical decision support.
Predictive tools in certified health IT
The ONC's HTI-1 final rule requires developers of certified health IT to apply risk management practices to predictive decision support interventions supplied as part of their health IT modules. If your product ships inside, or alongside, a certified EHR module, your clinical strategy needs to account for it.
Cybersecurity as a patient safety issue
FDA's cybersecurity guidance recommends security controls to help ensure device safety and effectiveness, and notes that cyber incidents can cause clinical hazards such as delayed diagnosis or treatment. That framing is helpful internally: cybersecurity is not only an IT matter, it belongs in the clinical risk file and in conversations with your clinical lead.
Whether your software is a regulated device depends on its intended use and functions. Confirm your classification with qualified regulatory counsel or a regulatory consultant before you finalize claims or marketing language.
Fit the product into clinical workflow, privacy and interoperability
A product can be clinically sound and still fail because it adds clicks, arrives at the wrong moment or cannot receive the data it needs. Health systems evaluate this carefully.
FDA's work on health-system adoption of digital tools names three broad domains for onboarding: the clinical use case, security and privacy review, and governance. Expect your buyer to ask about all three, often through different committees.
A 2022 peer-reviewed review of deploying digital tools in large health systems adds technical specifics. The tool must receive the right data at the needed interval, connect with the health system's information ecosystem, use shared standards such as FHIR where appropriate, and operate under data governance that limits access to necessary data and specifies protection and secondary use.
For device makers, FDA's interoperability guidance asks manufacturers to define the purpose and performance of interfaces, analyze risks involving interoperability, users and foreseeable misuse, test appropriately and communicate interface requirements and limitations.
Workflow questions to answer before a pilot
- Who sees the output, and at what point in the visit or care episode?
- What action is expected, and who is accountable for it?
- What happens when the tool is wrong, unavailable or ignored?
- Which data does it need, and who approves access?
- How will staff be trained, and who supports them after go-live?
These are operational questions with clinical consequences. Our founder's guide to clinical operations covers how to set up the day-to-day side.
Connect clinical value to a payment pathway
Clinical strategy that ignores payment ends up as a good idea with no budget. In the U.S., there are two common routes: reimbursement through payers, and contracting with health systems or other institutional buyers.
Reimbursement signals worth knowing
For remote monitoring, CMS has published specifics:
- Remote patient monitoring requires an established patient relationship, medically reasonable services and an FDA-defined medical device that automatically transmits physiologic data.
- Medicare pays separately for three main components: education and setup, device supply, and treatment management. It pays the same rate regardless of device type or data collected.
- For remote therapeutic monitoring, CMS designated codes 98979, 98984 and 98985 as sometimes therapy services effective January 1, 2026, and revised codes 98976 and 98977 for the 16 to 30 day monitoring period.
Coding and payment rules change every year. Treat this as a starting map and check the current CMS fee schedule and your billing advisor before building a model around any code.
What institutional buyers ask
For health systems, a 2025 peer-reviewed article on selling ROI in digital health reports that buyers emphasized five things: solving an institutional problem, identifying the payment model, fitting existing workflow including EHR integration, measuring patient and provider engagement, and demonstrating ROI.
A sequence that follows from this is to identify a high-friction clinical decision with a concentrated economic consequence, prove the product improves it where the buyer owns the benefit, and then use that evidence to support a reimbursement, contracting or budget path. Evidence first, scale second.
How investors and boards can read a clinical strategy
If you sit on a board or evaluate portfolio companies, the same material gives you a diligence checklist. Digital health pitch decks are generally expected to show clinical relevance, workflow fit, the economic buyer, evidence, and regulatory and privacy readiness. Bessemer Venture Partners recommends calculating clinical and financial ROI from the customer's perspective, defining the method with customers upfront and tracking it over time.
| Question | Strong signal | Warning sign |
|---|---|---|
| Is the clinical problem specific? | One problem, one setting, named users | A broad category with many use cases |
| Who owns the benefit? | A named buyer with a budget line | Value accrues to someone who does not pay |
| Is evidence staged? | A plan that grows with the product | One study, no follow-up plan |
| Is workflow fit tested? | Pilot data on use and engagement | Demos only |
| Is regulatory status understood? | A documented position on device status | Claims made before classification |
A personal-blog observation worth keeping in mind: health systems and payers do not respond to decks alone. They want clinical leaders who can speak their language and show how a product reduces complications and cost. That is a people question as much as a document question.
Our perspective
Across more than 25 years in medicine and business, I have watched the same pattern repeat. A healthcare SaaS team builds something clever, then asks a clinician to validate it. By then the big decisions are made: the problem, the user, the setting, the claims.
We think clinical strategy belongs at the start, and it should be owned by someone who has practiced medicine and also understands what a startup needs to survive. That dual view is the reason we built The StartUp MD around fractional Chief Medical Officer and advisory work for healthcare SaaS companies.
In practice, it means pressure-testing the clinical problem before the roadmap hardens, shaping an evidence plan the buyer will respect, and translating clinical reality for investors and boards. It also means being honest early about regulatory questions, so claims and product design stay aligned.
There is a gap in many young companies between what the product does and what a health system needs to hear. A fractional CMO is built to close it without the cost of a full-time executive hire. If something in your clinical strategy feels misaligned, I would welcome a conversation.
Paul Bergeron MD, MBA
Work with a clinical leader on your strategy
The StartUp MD is a healthcare advisory firm for healthcare SaaS and digital health companies. We offer Fractional Chief Medical Officer support and project-based advisory services, including clinical strategy development, product evaluation, regulatory guidance, clinical operations consulting, market readiness assessment and investor support.
If you are defining your clinical problem, planning evidence or preparing for a raise, see how our Fractional CMO and advisory services work, or start from The StartUp MD home page.
A practical order of operations
Pulling the pieces together, here is a sequence many digital health teams can follow:
- Write the problem statement. One clinical problem, one user, one setting, one outcome.
- Name the economic owner. Identify who benefits and who pays, even if they are different.
- Take a regulatory position. Decide how your intended use and functions relate to FDA device policy, with expert input.
- Draft an integrated evidence plan. Map the evidence you need at each stage, and what each audience will accept.
- Test workflow fit in a pilot. Measure use and engagement, not just accuracy.
- Document risk. Include privacy, cybersecurity, interoperability and foreseeable misuse.
- Package the story for buyers and investors. Use outcomes and ROI in the buyer's own terms.
This is a working order, not a rule. Some companies run steps in parallel, and a product with higher clinical risk will spend more time on steps three and four.
FAQ
What is the difference between clinical strategy and product strategy?
Clinical strategy decides which clinical problem to solve, for whom, and how the product will prove it helps. Product strategy turns that direction into features, sequencing and delivery. The two should be developed together, with clinical and product leaders as peers, but one does not replace the other.
When should a digital health startup bring in a Chief Medical Officer?
Earlier than most founders expect. Commentary on digital health leadership argues for clinical leadership in a founding role so that design, marketing and compliance rest on clinical standards from day one. Many early-stage companies cannot support a full-time executive, which is why a fractional CMO is a common route.
Does my software need FDA clearance?
It depends on intended use and function. FDA guidance excludes certain clinical decision support functions from the device definition only if they meet all four statutory criteria, and functions that fail them remain subject to device policies. Review your product against the guidance with regulatory counsel before you set claims.
What evidence do health systems want to see?
They tend to look for a solved institutional problem, a clear payment model, workflow and EHR fit, engagement data and ROI. Outcomes data from a setting similar to theirs carries the most weight. Plan pilots so they produce those measures from the start.
How do investors judge clinical strategy?
They look for clinical relevance, workflow fit, a defined economic buyer, evidence and regulatory and privacy readiness. They also value ROI measured the way the customer defines it and tracked over time. A specific problem statement and a staged evidence plan make that case easier to see.
Sources
- Choosing a career as chief medical officer at a health technology startup (MDedge)
- Clinical + Product: A Hidden Superpower for Health Tech
- The pathway to high-quality care with clinical leaders
- Identifying and formulating appropriate clinical problems (BMJ Digital Health)
- What is Product-Market Fit?
- Digital Therapeutic Clinical Evidence (DTx Alliance)
- The Digital Therapeutics Real-World Evidence Framework (PMC)
- Integrated Evidence Plans for Digital Health Technologies (DiMe)
- DiMe Resource: IEP Stage B
- Building Clinical Rigor into Virtual Care (a16z)
- Clinical Decision Support Software: Guidance for Industry (FDA)
- Health Data, Technology, and Interoperability: HTI-1 final rule (ONC)
- Cybersecurity in Medical Devices: Quality Management System Considerations (FDA)
- Developing Frameworks and Tools for Integration of Digital Health Tools into Clinical Practice (FDA)
- Deploying digital health tools within large, complex health systems (PMC)
- Design Considerations and Pre-market Submission Recommendations for Interoperable Medical Devices (FDA)
- Telehealth and Remote Patient Monitoring (CMS MLN)
- Remote Patient Monitoring (CMS)
- MM14250 Therapy Code List: 2026 Annual Update (CMS)
- Selling the Return on Investment for Digital Health (PMC)
- The Clinician-Founder's Sequencing Problem (MedTech Pioneers)
- Digital Health Pitch Deck: 12-Slide Guide
- The ABCs of health tech: key metrics to know and grow your business (Bessemer)