Click here to open the filter panel
#
510(k) premarket notification
A
Accountability
A
Accuracy
A
Adequacy decision
A
Ad hoc services
A
Adverse event
A
AI literacy (Art. 4 EU AI Act)
A
AI Officer
A
Analysis Data Model (ADaM)
A
Anonymisation
A
Appropriate safeguards
A
Article 29 Working Party (WP29)
A
Artificial intelligence (AI)
A
Authorised representative (EU AI Act)
A
Automated individual decision-making
A
Auxiliary medicinal product
B
Best-in-class drugs
B
Binding corporate rules (BCR)
B
Biobank
B
Biometric data
B
Biotechnology
B
Broad consent
B
Business associate agreement (BAA)
C
Central imaging
C
Central laboratory
C
Chemistry, Manufacturing and Controls (CMC)
C
Clinical outcome assessment (COA)
C
Clinical research
C
Clinical study
C
Clinical trial
C
Clinical trial agreement (CTA)
C
Clinical trial phases
C
Clinical Trials Information System (CTIS)
C
Clinical trial site
C
Clinical Trials Regulation (CTR) 536/2014
C
Clinician-reported outcome (ClinRO)
C
CNIL (Commission nationale de l'informatique et des libertés)
C
Codes of conduct
C
Consent
C
Contract research organisation (CRO)
C
Controller
C
Cookies
C
Cross-border processing
D
Data Act
D
Data concerning health
D
Data Governance Act (DGA)
D
Data management plan (DMP)
D
Data minimisation
D
Data monitoring committee (DMC)
D
Data processing agreement (DPA)
D
Data protection authority (DPA)
D
Data protection by default
D
Data protection by design
D
Data Protection Impact Assessment (DPIA)
D
Data Protection Officer (DPO)
D
Data Protection Representative (DPR)
D
Data quality
D
Data retention
D
Data subject
D
Data subject access request (DSAR)
D
Decentralised clinical trial (DCT)
D
De-identification (HIPAA)
D
Differential privacy
E
Early termination of a clinical trial
E
Electronic case report form (eCRF)
E
Electronic clinical outcome assessment (eCOA)
E
Electronic data capture (EDC)
E
Electronic health record (EHR)
E
Electronic informed consent (eConsent)
E
Encryption
E
End of a clinical trial
E
Enterprise
E
Ethics committee
E
EU Artificial Intelligence Act (AI Act)
E
European Data Protection Board (EDPB)
E
European Data Protection Supervisor (EDPS)
E
European Health Data Space (EHDS)
E
European Medicines Agency (EMA)
E
EU-US Data Privacy Framework (DPF)
E
Explicit consent
F
Fairness and transparency
F
Federated learning
F
Filing system
F
First-in-class drugs
F
Food and Drug Administration (FDA)
F
Fundamental rights impact assessment (FRIA)
G
General Data Protection Regulation (GDPR)
G
General-purpose AI model (GPAI)
G
Genetically modified organism (GMO)
G
Genetic data
G
Global public health security
G
Good clinical practice (GCP)
H
Health data warehouse (HDW)
H
High-risk AI system
H
HIPAA (Health Insurance Portability and Accountability Act)
H
Human oversight (AI Act)
H
Human subjects protection review board
C
Imported item 10
S
Imported item 11
C
Imported item 12
Click a letter to view all its definitions
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Term of the Day

Natural history study

A natural history study is a preplanned observational study intended to track the course of a disease over time, identifying demographic, genetic, environmental and other variables that correlate with its development and outcomes in the absence of intervention, or under standard of care. Designs may be retrospective (chart review of existing records) or prospective (longitudinal follow-up of a cohort or registry).

Natural history data is particularly important in rare and paediatric diseases, where randomised placebo-controlled trials may be infeasible or unethical. The FDA (guidance on rare disease natural history studies, 2019) and the EMA accept well-designed natural history studies to define endpoints and biomarkers, identify patient subgroups, estimate sample sizes and, in some cases, serve as external or historical control arms for single-arm trials supporting orphan products.

Because they are non-interventional, natural history studies fall outside the CTR and are governed by national law (for example France's MR-003 or MR-004 reference methodologies) and by the GDPR. They typically involve secondary use of medical records, long-term follow-up, genetic data and small populations in which anonymisation is rarely achievable, so pseudonymisation, a DPIA and a robust research legal basis under Art. 9(2)(j) are essential. Registries maintained by patient organisations or academic consortia raise additional questions of joint controllership and data access governance.

C

Imported item 10

A covered entity under HIPAA is a health plan, a health care clearinghouse, or a health care provider that conducts specified electronic transactions. Handling health information alone does not establish this status. Life sciences organisations should assess their actual activities and relationships before describing themselves as covered entities.

Key takeaways

  • HIPAA identifies three covered-entity categories, with an electronic standard-transaction condition applying to the health care provider category.
  • A business associate performs qualifying functions or services for a covered entity involving protected health information and has separate responsibilities.
  • A biotech sponsor does not become a covered entity solely because a study involves health data or a US hospital.

The Three Categories

CategoryKey distinction
Health planProvides or pays for health care under the applicable definition
Health care clearinghouseConverts health information between standard and non-standard formats
Health care providerConducts electronic transactions for which HHS has adopted standards

HHS explains that HIPAA applies to covered entities and business associates. A business associate relationship depends on the services and data involved, not simply on whether someone receives information from a hospital.

HHS research guidance separately describes conditions for research uses and disclosures. A sponsor receiving data for its own research is not automatically acting on behalf of the hospital as a business associate. The facts and applicable disclosure route need examination.

Why It Matters for Data Protection

Operationally, document the HIPAA assessment before choosing contract wording. Identify the entity, activity, data, purpose and relationship, then determine whether a business associate agreement or another research arrangement is appropriate.

For example, consider a hypothetical biotech that both sponsors studies and provides a hospital analytics service. The two activities may require different analyses. We recommend assessing them separately rather than applying one organisation-wide label without checking the services.

Frequently Asked Questions

Is every health app a covered entity?

No. Health-related content or functionality alone does not establish covered-entity status.

Can a covered entity also be a business associate?

Yes, when it performs a qualifying service for another covered entity.

Does being outside HIPAA remove all privacy duties?

No. Other laws and contractual obligations may still apply to the processing.

Related: HIPAA; business associate agreements; HIPAA scope assessment.

Updated: 27 October 2026