Healthcare products are notoriously slow to launch. Regulatory considerations, integration complexity, and institutional sales cycles all conspire to stretch timelines.

But if your product needs patient data access, that piece doesn't have to be the bottleneck. Here's a practical checklist for integrating health data in 90 days or less.

Before You Start: Strategic Decisions

1. Define your data requirements.

What clinical data does your product actually need? Be specific — requesting data you don't need complicates patient authorization and raises privacy concerns.

2. Determine your coverage requirements.

Which EHR systems matter for your target users?

If you're targeting consumers broadly, you need coverage across multiple systems. If you're focused on a specific health system or specialty, your requirements are narrower.

3. Choose your integration approach.

Option A: Direct integration. Build connections to each EHR yourself. Full control over implementation, but expect 2-3 months per EHR plus ongoing maintenance.

Option B: Infrastructure provider (like Consolidate Health). Single integration point for multiple EHRs, with time to market measured in days to weeks rather than months.

For most startups, Option B is the right choice. You're optimizing for speed and focus, not control over data plumbing.

Week 1-2: Foundation

4. Set up your development environment.

If using an infrastructure provider: sign up for a developer account, access the sandbox environment, review API documentation, and obtain test credentials.

If building direct: register on each EHR developer portal, apply for sandbox access, and begin each vendor's approval process. Note that approval timelines are calendar time, not coding time.

5. Design your authorization flow.

How will patients authorize data access? You'll need an in-app consent screen that clearly explains what data you're requesting and why, a redirect to EHR authorization via OAuth, callback handling and token storage, and error states with retry logic. The authorization UX significantly affects conversion rates. Invest in making it clear and trustworthy.

6. Plan your data model.

Design your internal data schema, plan normalization logic if you're not using a normalized API, define data freshness requirements, and think through your caching strategy before you start building.

Week 3-4: Core Integration

7. Implement the authorization flow.

Build the complete OAuth sequence: authorization request generation, redirect handling, token exchange, refresh token management, and secure token storage. Test thoroughly with sandbox patients. Edge cases are everywhere.

8. Implement data retrieval.

Build API calls for each data type you need: demographics, medication lists, condition and problem lists, lab results, allergies, and any other resources your product requires. Handle pagination, missing data, and error responses gracefully.

9. Connect data to your product.

This is where your actual product value lives. Display patient information in your UI, feed data to your algorithms or AI models, and implement whatever your product does with clinical data.

Week 5-6: Testing and Refinement

10. Test with realistic scenarios.

Sandbox data is clean. Real patient data isn't. Test for missing fields, unexpected data formats, large data volumes, slow API responses, token expiration during active sessions, and patients with records at multiple locations.

11. Implement error handling.

Things will go wrong. Plan for API errors and retries, expired or invalid tokens, rate limiting, network failures, and graceful degradation when data is unavailable. How your product handles failure is as important as how it handles success.

12. Review security and privacy.

Before going live, audit token storage (encrypted and secure), verify data transmission security (TLS), review access controls, ensure audit logging is in place, and confirm your compliance posture against HIPAA and any relevant state laws.

Week 7-8: Production Preparation

13. Complete vendor requirements.

If going direct with EHRs: submit for app review, complete attestations, address review feedback, and await approvals. Build more time into this step than you think you need.

If using an infrastructure provider: complete any production access requirements and review terms and agreements.

14. Prepare for scale.

Production brings different loads than testing. Review rate limits and quotas, implement monitoring and alerting, plan for token refresh at scale, and finalize your caching strategy.

15. Build operational playbooks.

Document how to monitor integration health, debug common issues, handle patient support requests, and respond to outages or errors. Your future on-call engineer will thank you.

Week 9-12: Launch and Iteration

16. Soft launch with limited users.

Start with internal testing in production, expand to a limited beta, monitor closely for issues, and fix problems before broader release. Going from zero to full launch without this step is how avoidable problems become public ones.

17. Iterate based on real usage.

Real users reveal things sandboxes don't. Watch for authorization drop-off, confusing UX patterns, data quality issues, and feedback on whether the data you're surfacing is actually useful.

18. Expand coverage incrementally.

If you launched with limited EHR coverage, prioritize additional integrations based on actual user demand. Add EHRs incrementally and maintain consistent UX across sources as you grow.

The 90-Day Reality

Is 90 days aggressive? Yes. Achievable? Also yes, if you make smart choices early.

The biggest accelerant is using infrastructure that already exists. Building EHR integrations from scratch doesn't create product value. It creates product delay.

Consolidate Health provides the data layer that makes 90-day launches possible. One integration, multiple EHRs, clean normalized data. You focus on what makes your product valuable. We focus on getting you the data.

90 days from now, your product could be live with real patient data. The checklist is here. The infrastructure is ready.