{"id":6940,"date":"2026-04-01T11:16:33","date_gmt":"2026-04-01T09:16:33","guid":{"rendered":"https:\/\/mediconomics.com\/?post_type=glossary&p=6940"},"modified":"2026-07-13T19:09:16","modified_gmt":"2026-07-13T17:09:16","slug":"post-market-clinical-follow-up-pmcf","status":"publish","type":"glossary","link":"https:\/\/mediconomics.com\/en\/glossar\/post-market-clinical-follow-up-pmcf\/","title":{"rendered":"Post-Market Clinical Follow-up (PMCF)"},"content":{"rendered":"

Post-Market Clinical Follow-up (PMCF) refers to the planned and proactive collection of clinical data after a medical device has been placed on the market. The aim is to keep the clinical evaluation up to date, to identify new or rare risks early, and to confirm clinical performance and clinical benefit in real-world care. PMCF is thus a central component of post-market surveillance under the EU Medical Device Regulation (EU) 2017\/745 (MDR).<\/p>\n

Role of PMCF in the MDR’s lifecycle approach<\/h2>\n

In many projects, PMCF is also used to capture “real-world” aspects that are difficult to record in pre-market studies: usage patterns, differing care pathways, comorbidities, or usage patterns close to off-label use. It is important not to tacitly broaden the intended purpose, but instead to align data collection clearly with the approved claims. This keeps PMCF regulatorily usable and strengthens the clinical evaluation instead of creating new uncertainties.<\/p>\n

The MDR does not treat clinical evidence as a one-off demonstration at the point of authorisation, but as a continuous obligation. PMCF closes the gap between pre-market data (e.g. clinical investigations) and widespread use in the market. Particularly in the case of rare events, long-term use or specific patient groups, important findings may only emerge after launch. PMCF data feed into the clinical evaluation and support the benefit-risk assessment over time.<\/p>\n

PMCF plan: content and expected structure<\/h2>\n

Manufacturers typically describe PMCF in a PMCF plan that sets out objectives, methods, data sources, endpoints and analyses. A good plan shows which clinical questions are to be answered and how data collection is implemented in practice. This also includes responsibilities, timelines, data quality measures, and criteria for assessing whether the data collected are sufficient. It is important that the plan connects with risk management and post-market surveillance, so that signals from the market phase are processed consistently.<\/p>\n

In practice, the PMCF plan is often maintained as part of an overarching PMS plan, or at least closely integrated with it. This makes clear which signals from complaints, trend analyses or incidents should lead to an adjustment of clinical data collection. Especially for software or combination products, it is also worth clearly defining which updates are considered “significant” and which clinical questions must therefore be readdressed.<\/p>\n