Outlier Patent Attorneys

Protecting Digital Health Technologies: A Comprehensive Guide for Startups

Insights

Digital health is expanding at an unprecedented pace. According to a McKinsey & Company analysis, global digital health investments have surged in the past few years, with the market expected to grow exponentially as innovation accelerates.

Yet with rapid growth comes risk. In a highly competitive landscape, ideas can be copied or misappropriated if not adequately protected. Startups need a holistic approach to safeguarding intellectual property, sensitive health data, and regulatory compliance.

In this post, we’ll provide end-to-end insights specifically tailored for digital health startup founders—not just IP basics, but also real-world examples, non-obvious tips, and strategic angles for navigating global regulations.

The Digital Health Landscape and Why Protection Matters

Defining Digital Health

Digital health covers:

  • Telemedicine Platforms (remote consultations)

  • Wearable Devices (fitness and vitals tracking)

  • AI-Driven Diagnostics (machine learning in disease detection)

  • Mental Health Apps (therapy and mindfulness tools)

  • Remote Patient Monitoring (real-time patient data collection)

Each of these relies on proprietary technology and sensitive data, demanding careful IP and data protection strategies.

Opportunities vs. Challenges

  • Opportunity: The global digital health market is forecasted to reach $1 trillion by 2030, according to Grand View Research.

  • Challenge: A crowded market means competition is fierce, and compliance with evolving regulations can be resource-intensive.

Insight #1

Biggest Competitor: Your Own Partners
Sometimes hospitals or large providers you partner with might replicate your technology in-house once they see its value. Your collaboration agreements should clearly state who owns each component of the solution to avoid this “friendly fire” scenario.

Intellectual Property (IP) Fundamentals for Digital Health

1. Patents

What Is Patentable?

Technical innovations that solve real-world problems can often be patented. For example:

  • Machine learning algorithms improving medical imaging accuracy

  • Data processing methods for wearable sensors

  • Software-hardware integrations offering new diagnostic approaches

Note: Both the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) have specific rules for software and AI. You must prove a technical effect beyond a mere abstract idea or algorithm.

Challenges of Software & AI Patent Eligibility

  • Novelty and Inventive Step: Your invention must be new (no prior art) and not obvious.

  • Technical Character: In the EU, purely abstract models may be rejected unless they demonstrate a tangible, technical improvement.

Filing Strategies

  • File Early: Publicly disclosing your innovation—through pitch decks or demos—can jeopardize patent eligibility.

  • International Markets: Target growth regions (U.S., EU, Japan, China) in your filing strategy.

Insight #2

Patent “Strength” > Patent “Count”
Investors often value the quality and enforceability of patents more than sheer quantity. A single, well-drafted patent that is defensible globally can be far more valuable than a stack of weak ones.

2. Trade Secrets

When Trade Secrets Make Sense

Trade secrets can protect:

  • Proprietary algorithms or training data

  • Business processes that are innovative but hard to reverse-engineer

You must maintain strict confidentiality (NDAs, secure data handling). If a secret is publicly disclosed—even accidentally—it loses protection.

Pros and Cons

  • Pros: No public disclosure (unlike patents) and no expiration date.

  • Cons: If anyone independently discovers or reverse-engineers the tech, trade secret protection may vanish.

Insight #3

You Can Use Both Patents and Trade Secrets
Most founders think it’s either/or, but certain aspects (e.g., the “surface” invention) can be patented, while underlying data processing is kept as a trade secret.

Trademarks and Branding

Importance in Healthcare

Trust is vital in healthcare. A strong brand signals reliability to patients and providers.

Protecting Names, Logos, and Taglines

  • Register Early: Lock down trademarks in key markets.

  • International Registration: Use the Madrid Protocol for global coverage.

Insight #4

Design and Color Matter
Many startups focus on name-based trademarks, but color schemes and distinctive logos can also be trademarked, helping you stand out in a crowded digital marketplace.

Software Code

Copyright in code is automatic upon creation, but voluntary registration can provide easier enforcement evidence.

UI/UX Designs

In certain jurisdictions, you can file for design rights to protect the look and feel of your user interface—a critical differentiator in digital health tools.

5. Best Practices

  • Combine IP Protections: Patents, trademarks, trade secrets, and copyrights often overlap and reinforce each other.

  • Documentation: Maintain invention disclosure forms and version-tracking logs.

Data Protection, Ownership, and Compliance

Regulatory Frameworks

Non-compliance can lead to massive fines and brand-damaging headlines.

Data Ownership & Licensing

Digital health often involves partnerships with:

  • Hospitals or clinics (patient data)

  • Research institutions (domain expertise)

  • Device manufacturers (hardware integration)

Contracts should clarify:

  • Who owns new data?

  • How can it be commercialized?

  • What happens to improvements to AI models?

Insight #5

Your “Secret Weapon” Is Carefully Curated Data, Not Just Big Data
Many assume that huge datasets automatically yield the best AI. In reality, quality and relevance of data can matter more than quantity. Smaller, meticulously curated datasets often produce more accurate AI models—and are easier to protect as trade secrets.

Ensuring Data Security

  • Encryption & Access Controls: For preventing breaches.

  • Regular Audits: To verify compliance internally and externally.

Data Monetization

Some startups anonymize and aggregate data to sell insights to pharma or insurers. This can be lucrative but must adhere to privacy regulations—especially under GDPR, which restricts re-identification.

Common Pitfalls to Avoid

  • Ignoring Local Laws: Data rules vary widely by country.

  • Lack of Patient Consent: Particularly crucial in Europe; the default stance is to minimize data collection.

Insight #6

Encryption Without Governance Isn’t Enough
Many founders focus on technical security (e.g., encryption) but forget organizational practices like staff training and usage policies. A simple employee slip-up can breach security more easily than a hacker.

AI/ML as Software-as-a-Medical-Device (SaMD)

The FDA’s Digital Health Center of Excellence regulates certain AI-based health solutions as SaMD. Similarly, the EU Medical Device Regulation (MDR) oversees software with medical purposes.

  • Model Updates: AI evolves with new data. You must often document these changes for regulatory compliance.

Ethical & Liability Issues

  • Algorithmic Bias: Training data skewed toward certain demographics can yield discriminatory outcomes.

  • Explainability: Regulators and healthcare providers may require explanations of how AI decisions are made.

Future Regulatory Shifts

  • EU AI Act: Proposed rules could classify certain medical AI solutions as “high-risk,” imposing stricter oversight.

  • Global Harmonization: Expect more cooperation among regulators, but timelines vary.

Insight #7

Liability May Extend Beyond the Developer
Some regulations propose that both the AI developer and the deploying healthcare provider could share liability for AI errors. This nuance can shape your insurance and partnership agreements.

Strategies for Building a Robust Protection Plan

Risk Assessment and Audits

Regularly audit your IP portfolio (patents, trademarks, trade secrets). Update your strategy as your technology evolves.

Contracts and Agreements

  • NDAs for employees, contractors, and vendors

  • Collaboration Contracts for joint projects

  • Licensing Terms to govern open-source or shared software usage

Investor Considerations

Savvy investors check:

  • Ownership clarity of your IP

  • Regulatory compliance readiness

  • Ability to scale in multiple markets

Managing Global Markets

Different jurisdictions have different thresholds for:

  • Patent eligibility

  • Privacy compliance

  • Enforcement action

Tailor your IP and compliance strategies to each region.

Insight #8

Enforcement Varies Wildly by Country
IP laws might be robust on paper but weaker in enforcement in certain regions. Sometimes, establishing local partnerships or adopting alternative protections (e.g., trade secrets) can be more practical than relying on a patent alone.

Timeline and Budgeting

  • Patent Filings: Provisionals, PCTs, and national phases come with different costs and timelines.

  • Compliance Expenses: Include ongoing audits, data privacy officer salaries, etc.

Common Mistakes & How to Avoid Them

  1. Waiting Too Long to Protect IP

    • Public disclosures can invalidate patent eligibility. File early or use provisional filings.

  2. Ignoring Regulatory Changes

    • Non-compliance with AI or data laws can lead to fines and product removal.

  3. Underestimating Data Protection

    • Even accidental leaks can devastate your credibility.

  4. One-Dimensional IP Strategies

    • Relying solely on patents or trade secrets leaves gaps. Combine multiple IP layers.

  5. Poor Documentation

    • Lack of evidence or logs can derail your defense in disputes.

Insight #9

Sometimes Open-Sourcing Part of Your Tech Can Strengthen Your Position
When a portion of your platform is open source, you gain community engagement, faster iterations, and widespread adoption—while you retain proprietary control of the core or “secret sauce.” This can actually enhance your competitive edge.

Actionable Checklist for Startup Founders

  1. IP Audit

    • Catalog your patents, trade secrets, trademarks, etc.

    • Check resources from WIPO for international standards.

  2. Data Governance Framework

    • Integrate privacy by design.

    • Comply with GDPR and HIPAA.

  3. Contracts and Agreements

    • Draft robust NDAs.

    • Define IP ownership in collaboration agreements—especially regarding improvements to AI models.

  4. Continuous Monitoring

    • Track new regulations (e.g., EU AI Act).

    • Update your data usage policies regularly.

  5. Secure Adequate Funding

    • Budget for legal costs, compliance audits, and international filings.

  6. Consult Experts

    • Work with IP attorneys, data privacy consultants, and regulatory specialists early.