Healthtech clinical evidence pipeline — what to build alongside the product

Educational only — not clinical or regulatory advice. Healthtech compliance and clinical-evidence requirements vary heavily by region (FDA / EMA / NMPA) and product class. Consult a qualified regulatory affairs consultant before designing your evidence pipeline.

Healthtech startups that wait until Series A to think about clinical evidence are 18 months behind. The companies that compound have been building evidence — observational, retrospective, prospective — from day one. Not because they had a budget for it, but because they designed the product to generate it as a byproduct of normal use. Here's how that pipeline looks.

The three tiers of clinical evidence

Observational evidence — data generated by real-world use of your product. Patient outcomes, usage patterns, adherence rates. Low rigor in clinical terms; high rigor for product-market signal.

Retrospective studies — analysis of historical data showing your product correlates with outcomes. Cheap to produce ($5-50k), publishable, useful for payer conversations. Not enough for FDA clearance on its own but builds the foundation.

Prospective studies — actually running an intervention and measuring outcomes against a control. Expensive ($100k-$10M depending on scale and rigor), slow (12-36 months), the gold standard for clinical claims.

Build all three in parallel. The observational tier feeds the retrospective tier feeds the prospective tier.

How to design the product to generate evidence

1. Capture structured outcomes from day one. Whatever your clinical claim is (better adherence, lower hospitalisations, faster recovery), build the measurement into the product. Don't depend on retrospective data extraction; capture it prospectively.

2. Build a data dictionary aligned with clinical terminology. SNOMED, ICD-10, LOINC codes mapped from your application data. The first time a researcher asks "show me all patients with condition X" you should be able to answer in 30 minutes, not 3 weeks.

3. Consent for research from day one. Your terms-of-service include de-identified data use for research. Doesn't mean you use it that way immediately; it means the door is open when you're ready. Without this consent at signup, you cannot retroactively turn customer data into research data.

4. Patient-reported outcomes baked into normal flow. Brief, validated PROs (PHQ-9, GAD-7, SF-12 — domain-specific) integrated into the product cadence. Quarterly is usually enough. The data compounds.

5. Anonymisation pipeline live in production. A separate research database with HIPAA-compliant de-identification. Researchers query the research DB, not the operational one. Setup cost: ~80-120 engineering hours; ongoing cost: low.

The first three studies

Study 1 (Year 1) — Real-world evidence paper. Observational data on N=100-500 patients, ~6 months of follow-up. Publishable in a clinical journal. Cost: $5-15k for statistical support and publication fees. Value: first peer-reviewed evidence; usable in payer conversations.

Study 2 (Year 2) — Retrospective comparative effectiveness study. Compares outcomes for your users against a matched cohort from claims data or registries. N=500-2,000. Cost: $30-80k. Value: comparative claims about your effectiveness.

Study 3 (Year 2-3) — Prospective pragmatic study. Real-world randomised or quasi-randomised study at one or more clinical sites. N=200-1,000. Cost: $300k-$2M depending on scope. Value: the clinical claim you can make in marketing, regulatory filings, payer contracts.

By Series B you should have these three threads in motion. Companies that don't have observational + retrospective evidence at Series B struggle to fund the prospective study at Series C and never get a clinical claim that differentiates them.

What's a waste pre-Series-A

• Premature randomised controlled trial. Without observational evidence to inform study design, an RCT is expensive guess-work. Generate observational first.
• Academic partnerships before you have data to share. Researchers don't want to partner on potential; they want to partner on existing data. Build the data; then the partnerships are easy.
• Hiring a Chief Medical Officer in year 1. Fractional CMO at $3-8k/month is more than enough. Full-time CMO at $400k+ is for Series B+.
• FDA/CE pre-submission meetings without a regulatory plan. Bring a strategy, not a question. Otherwise you waste the agency's time and your credibility.

What to do today

1. Identify your one most important clinical claim (the one outcome you want to defend in 3 years).
2. Design the product to capture the data that proves it from day one. Schema, consent, PROs, structured outcomes.
3. Set up the de-identified research database parallel to the production database.
4. Plan the Year-1 observational paper now; commission it 9-12 months from today.
5. Pick a regulatory consultant who's shipped 5+ products in your category. The first conversation is usually free; the relationship matters from day one.