[Policy Alert] Federal Health It Rules Clamping Down On Information Blocking In Clinical Research Networks

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[Policy Alert] Federal Health It Rules Clamping Down On Information Blocking In Clinical Research Networks

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[Policy Alert] Federal Health IT Rules Clamping Down on Information Blocking in Clinical Research Networks

The regulatory landscape for healthcare data is undergoing a massive shift. Federal regulators are turning their attention to a critical bottleneck in medical innovation: information blocking within clinical research networks.

For years, the seamless flow of clinical data has been hindered by proprietary software, organizational silos, and overly conservative legal interpretations. Under the latest federal health IT rules, the Office of the National Coordinator for Health Information Technology (ONC) and the Office of Inspector General (OIG) are enforcing strict compliance standards. These rules ensure that Electronic Health Information (EHI) flows freely to support both patient care and clinical research.

This policy alert breaks down what these rules mean for clinical research networks, who is affected, and how organizations must adapt to avoid severe penalties.

Understanding Information Blocking in Clinical Research

What is Information Blocking?

Defined under the 21st Century Cures Act, information blocking is any practice by an "actor" that is likely to interfere with, prevent, or materially discourage the access, exchange, or use of Electronic Health Information (EHI), unless required by law or covered by a specific regulatory exception.

How Does It Apply to Clinical Research Networks?

While information blocking rules were initially viewed through the lens of patient care and treatment, their application to clinical research networks is now a primary focus.

Clinical research networks rely on the rapid aggregation of real-world data (RWD) from Electronic Health Records (EHRs) to identify trial candidates, analyze outcomes, and monitor safety. When healthcare systems or EHR developers restrict access to this data—either by charging exorbitant integration fees, delaying data exports, or citing unfounded privacy concerns—they may be guilty of information blocking.

Key Regulators and the Legislative Framework

The enforcement framework relies on two primary pillars:

The 21st Century Cures Act and the ONC

The ONC establishes the technical standards and policy definitions for information blocking. Under these rules, EHI is defined broadly using the HIPAA Designated Record Set (DRS) standard. If clinical research data is incorporated into a patient's medical or billing record, it constitutes EHI and must be shareable.

HTI-1 and HTI-2: The Latest Regulatory Updates

The HTI-1 (Health IT, Tooling, and Interoperability) Final Rule and the proposed HTI-2 rules refine these definitions. They introduce stricter transparency requirements for certified health IT developers and establish clear pathways for standardized Application Programming Interfaces (APIs). These APIs allow clinical research platforms to query and extract patient data seamlessly with proper patient consent.

Who is Affected? Identifying "Actors" in Clinical Research

The ONC categorizes regulated entities into three distinct "actors." In the context of clinical research, these actors have specific obligations:

| Actor Category | Definition in Clinical Research | Key Obligation | | :--- | :--- | :--- | | Healthcare Providers | Hospitals, academic medical centers, and clinics conducting clinical trials. | Must not withhold patient EHI from authorized clinical research networks or trial registries when requested. | | Health IT Developers | Vendors of certified EHRs and clinical trial management systems (CTMS) integrated with EHRs. | Must provide open, non-discriminatory APIs (like FHIR standards) to allow research platforms to extract clinical data. | | Health Information Networks (HINs) / Exchanges (HIEs) | Regional or national networks facilitating the exchange of clinical data. | Must allow research networks to participate in data exchange under reasonable, non-discriminatory terms. |

Permissible Exceptions to Information Blocking Rules

The ONC recognizes that data sharing is not always feasible or safe. There are eight regulatory exceptions where withholding EHI is legally permissible. These are divided into two categories:

Information Blocking Exceptions
│
├── Exceptions for Not Fulfilling Requests
│   ├── 1. Preventing Harm Exception
│   ├── 2. Privacy Exception
│   ├── 3. Security Exception
│   ├── 4. Infeasibility Exception
│   └── 5. Health IT Performance Exception
│
└── Exceptions for Procedures / Terms
    ├── 6. Content and Manner Exception
    ├── 7. Fees Exception
    └── 8. Licensing Exception

When Can Research Data Be Legally Withheld?

In clinical research, three exceptions are most frequently leveraged:

The Privacy Exception: If sharing EHI violates state or federal privacy laws (such as HIPAA or the Common Rule), or if the patient has explicitly withheld consent for research data sharing.
The Infeasibility Exception: If the requestor asks for data in a format that cannot be generated due to technological limitations or force majeure.
The Preventing Harm Exception: If a clinician determines that releasing specific clinical trial data (such as unblinded study results before the trial concludes) could cause physical harm to the patient or jeopardize the scientific integrity of the trial.

Key Challenges for Clinical Research Networks

Achieving compliance is not without its hurdles. Clinical research networks face unique operational challenges under these rules:

Informed Consent vs. Data Sharing: Balancing the patient's right to opt-out of research with the mandate to share EHI.
Proprietary Data Models: Many clinical trials utilize custom data fields that do not map cleanly to standard USCDI (United States Core Data for Interoperability) formats.
Cost Allocation: Determining what constitutes a "reasonable fee" for building custom data exports for pharmaceutical sponsors without violating the Fees Exception.
Blinded Studies: Ensuring that automated data-sharing protocols do not accidentally release blinded trial data to patients or investigators, thereby ruining trial validity.

Action Plan: How to Ensure Compliance and Avoid Penalties

Violating information blocking rules carries severe financial and operational consequences. Health IT developers and HIEs/HINs can face civil monetary penalties of up to $1 million per violation from the OIG. Healthcare providers face "disincentives" that impact Medicare/Medicaid reimbursements.

To protect your organization, implement this step-by-step compliance strategy:

1. Audit Your Data Workflows

Map out how clinical data flows from your EHRs to your clinical trial management systems (CTMS) and external research partners. Identify any manual bottlenecks, delays, or custom fees.

2. Standardize on FHIR APIs

Transition your clinical research integrations to the HL7® FHIR® (Fast Healthcare Interoperability Resources) standard. Utilizing standardized APIs minimizes the technical justification for withholding data.

3. Update Informed Consent and HIPAA Authorizations

Ensure your trial enrollment documents clearly state how patient EHI will be accessed, shared, and protected. Clear documentation supports the "Privacy Exception" if a patient chooses to restrict their data.

4. Train Clinical and IT Staff

Educate your IT department, principal investigators (PIs), and institutional review boards (IRBs) on the distinction between clinical care EHI and proprietary research data.

5. Document All Refusals

If your organization must deny a request for data sharing (e.g., to preserve a blinded study), thoroughly document the decision. Map the refusal directly to one of the eight ONC exceptions to establish a clear audit trail.

Conclusion: Embracing Open Data for Better Health Outcomes

The federal clampdown on information blocking is not just a regulatory hurdle—it is an opportunity. By dismantling the technical and bureaucratic barriers to data sharing, clinical research networks can accelerate recruitment, lower trial costs, and bring life-saving therapies to market faster.

Compliance requires a proactive approach to data governance. Organizations that invest in interoperable infrastructure today will lead the next generation of clinical innovation tomorrow.

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