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Potential savings in the diagnosis of vestibular schwannoma
Author(s) -
Scholte M.,
Hentschel M.A.,
Kunst H.P.,
Steens S.C.A.,
Rovers M.M.,
Grutters J.P.C.
Publication year - 2018
Publication title -
clinical otolaryngology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.914
H-Index - 68
eISSN - 1749-4486
pISSN - 1749-4478
DOI - 10.1111/coa.12973
Subject(s) - medicine , schwannoma , magnetic resonance imaging , population , vestibular system , test (biology) , emergency medicine , radiology , environmental health , paleontology , biology
Magnetic resonance imaging ( MRI ) is used to screen patients at risk for vestibular schwannoma ( VS ). These MRI s 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 .