Beyond complication rates: Nationwide neurosurgical compensation claims in a No-fault system.

Authors

F M C Lioi, N Sunthara, M K H Wiedmann

Published in

Brain & spine. Volume 6. Pages 107470. Epub Oct 07, 2026.

Abstract

Medico-legal claims are often used as proxies for malpractice burden and health care quality. However, they reflect not only underlying clinical events but also the structure of the compensation system through which they are adjudicated. This is particularly relevant in neurosurgery, where high baseline risk and uncertainty in outcome attribution may influence both the propensity to file claims and their subsequent resolution. The objective of this study was to characterize compensation outcomes, clinical domains, decision grounds, and failure-process patterns in a nationwide no-fault neurosurgical dataset.
We retrospectively analyzed 620 neurosurgery-related compensation decisions issued in Norway between 2015 and 2024, examining clinical domains, decision grounds, and failure-process patterns.
Compensation was granted in 93 of 620 decisions (15.0%). Nontraumatic spinal disorders represented the largest domain (225/620, 36.3%) but had a low grant rate (23/225, 10.2%), whereas grant rates were higher in cerebrospinal fluid and shunt disorders (17/43, 39.5%) and trauma (9/29, 31.0%). Within nontraumatic spinal disorders, cervical degenerative disease showed particularly low compensability (8/149, 5.4%). Among granted decisions, the leading failure-process domains were preoperative or diagnostic (35/93, 37.6%), intraoperative or procedural (22/93, 23.7%), and perioperative or postoperative management (13/93, 14.0%).
In this nationwide neurosurgical series from a no-fault compensation system, compensation was granted in 15.0% of decisions and primarily reflected avoidable failures along the care pathway rather than adverse outcomes alone. Compensation decision data should therefore not be interpreted as complication rates, but as system-filtered signals of compensable and avoidable harm shaped by adjudicatory framework and system design.

PMID:
42908905
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.

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