Potential savings in the diagnosis of vestibular schwannoma

Clin Otolaryngol. 2018 Feb;43(1):285-290. doi: 10.1111/coa.12973. Epub 2017 Sep 7.


Introduction: Magnetic resonance imaging (MRI) is used to screen patients at risk for vestibular schwannoma (VS). These MRIs are costly and have an extremely low yield; only 3% of patients in the screening population has an actual VS. It might be worthwhile to develop a test to predict VS and refer only a subset of all patients for MRI.

Objective: To examine the potential savings of such a hypothetical diagnostic test before MRI.

Design: We built a decision analytical model of the diagnostic strategy of VS. Input was derived from literature and key opinion leaders. The current strategy was compared to hypothetical new strategies, assigning MRI to the following: (i) all patients with pathology, (ii) all patients with important pathology and (iii) only patients with VS. This resulted in potential cost savings for each strategy. We conducted a budget impact analysis to predict nationwide savings for the Netherlands and the United Kingdom (UK), and a probabilistic sensitivity analysis to address uncertainty.

Results: Mean savings ranged from €256 (95%CI €250 - €262) or approximately US$284 (95%CI US$277 - US$291) per patient for strategy 1 to €293 (95%CI €290 - €296) or approximately US$325 (95%CI US$322 - US$328) per patient for strategy 3. Future diagnostic strategies can cost up to these amounts per patient and still be cost saving. Annually, for the Netherlands, €2.8 to €3.2 million could be saved and €10.8 to €12.3 million for the UK.

Conclusions: The model shows that substantial savings could be generated if it is possible to further optimise the diagnosis of VS.

Publication types

  • Multicenter Study

MeSH terms

  • Cost Savings / trends*
  • Humans
  • Incidence
  • Magnetic Resonance Imaging / economics*
  • Models, Economic*
  • Netherlands / epidemiology
  • Neuroma, Acoustic / diagnosis*
  • Neuroma, Acoustic / economics
  • Neuroma, Acoustic / epidemiology
  • Population Surveillance*