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E
Explicit consent
F
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F
FDPIC (Swiss Federal Data Protection and Information Commissioner)
F
Federated learning
F
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F
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F
First-in-human (FIH) trial
F
Food and Drug Administration (FDA)
F
Fundamental rights impact assessment (FRIA)
G
General Data Protection Regulation (GDPR)
G
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G
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G
Genetic data
G
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G
Good clinical practice (GCP)
H
HDS certification (Hébergeur de Données de Santé)
H
Health data access body (HDAB)
H
Health data warehouse (HDW)
H
HHS Office for Civil Rights (OCR)
H
High-risk AI system
H
HIPAA (Health Insurance Portability and Accountability Act)
H
Homomorphic encryption
H
Human oversight (AI Act)
H
Human subjects protection review board
I
ICH E6(R3)
I
Incapacitated subject
I
Information Commissioner's Office (ICO)
I
Informed consent
I
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I
Institutional Review Board (IRB)
I
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I
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I
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I
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J
Joint controllers
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k-anonymity
K
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K
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L
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L
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L
Lay summary
L
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L
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L
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L
LGPD (Brazil's General Data Protection Law)
L
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L
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M
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M
MedDRA
M
Medical Device Regulation (MDR)
M
Membership inference attack
M
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M
MHRA (Medicines and Healthcare products Regulatory Agency)
N
Natural history study
N
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N
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O
Observational study
O
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O
One-stop-shop mechanism and lead supervisory authority
O
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P
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P
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P
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P
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P
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P
Post-market surveillance (PMS)
P
Predetermined change control plan (PCCP)
P
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P
Principles of data protection
P
Privacy
P
Privacy by design
P
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P
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P
Processing
P
Processor
P
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P
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P
Protocol
P
Provider and deployer (AI Act roles)
P
Pseudonymisation
P
Purpose limitation
Q
Qualified Person for Pharmacovigilance (QPPV)
Q
Quality management system (QMS)
Q
Quasi-identifier
Q
Query (clinical data query)
R
Randomisation and trial supply management (RTSM)
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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.

P

Post-market surveillance (PMS)

Post-market surveillance (PMS) is the systematic collection and evaluation of information about a medical device after it reaches the market. Under the EU MDR, it helps manufacturers monitor quality, performance and safety throughout the device’s lifetime and identify the need for preventive or corrective action.

Key Takeaways

  • PMS is a continuing system within the manufacturer’s quality management arrangements, not a one-off report.
  • The plan and reporting approach should match the device and applicable regulatory requirements.
  • AI Act post-market monitoring is a related obligation for relevant high-risk AI systems, not a synonym for all device PMS.

What Does a PMS Workflow Do?

ElementMeaning
CollectGather relevant experience and performance information
EvaluateIdentify patterns and implications for benefit and risk
ActImplement and follow up appropriate corrective measures

Article 83 of the MDR links the surveillance system to the manufacturer’s quality management system and requires a proportionate approach. Surveillance information supports updates to risk management and clinical evaluation, among other activities. The AI Act’s Article 72 provides for post-market monitoring by providers of high-risk AI systems. Where sectoral monitoring already exists, integration is possible under the relevant conditions. Check the system’s classification and applicable implementation timetable rather than assuming that every AI-enabled product has identical duties today.

Primary guidance: MDCG 2025-10 PMS guidance; European Commission AI Act Article 72.

Why It Matters for Data Protection

For a hypothetical connected diagnostic device, we recommend mapping information from complaints, support tickets and performance logs before combining it for surveillance. Decide which identifiers are genuinely necessary to investigate a signal and restrict access to the corresponding case information. Separate technical performance data from patient narratives where feasible, and document retention and onward sharing. Make the safety escalation route work alongside the privacy incident route: a single report may require both assessments, but the teams should not circulate identifiable records more widely than the investigation needs.

Frequently Asked Questions

Is PMS the same as vigilance?

Vigilance concerns specific safety reporting and actions within the wider post-market framework.

Is PMS only relevant after a complaint?

No. It is a systematic process, not merely a reaction to individual complaints.

Does the AI Act replace MDR surveillance?

No. Assess the applicable requirements together and any permitted integration of monitoring arrangements.

Related reading: medical device regulation mdr; pharmacovigilance.

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Updated: 27 October 2026