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Revista Española de Salud Pública

versão On-line ISSN 2173-9110versão impressa ISSN 1135-5727

Resumo

ASENCIO EGEA, María Ángeles et al. Economic impact of the introduction of a technique for early detection of Mycobacterium tuberculosis Complex in clinical samples in a Spanish hospital. Rev. Esp. Salud Publica [online]. 2013, vol.87, n.4, pp.419-425. ISSN 2173-9110.  http://dx.doi.org/10.4321/S1135-57272013000400011.

Background: Tuberculosis (TB) remains an important public health problem worldwide. Our objective was to estimate the economic and health care impact of the introduction of an early diagnosis tecnique of TB, the Xpert MTB/RIF® assay (Xpert). Methods: The savings was estimated on the basis of reduction in the time of TB hospitalization at avoid the false-negative (FN) and false-positive (FP) TB cases diagnosed by auramine staining that could have been detected by Xpert between 2008-2012 in our hospital. The costs analysis was made by adding the cost arising from FN (hospitalization, special tests and equipment for respiratory isolation) and FP (TB treatment, successive medical consultations, analytical and microbiological controls). Results: We detected 19 FP and 22 FN during the 5-year study. Xpert would have detected 19 FP and 15 FN. It was estimated a minimum cost of 3217 euros per FP (treatment, successive medical consultations, analytical and microbiological controls), while each FN has required an extension of hospitalization from 7 days on average (62229 euros), both translated into a global cost of 62229 euros. After an initial investment of 16250 euros (50 cases with high suspicion of TB at 65 euros/test), the hospital would have saved 45979 euros overall in five years. Conclusions: The introduction of Xpert would improve the quality of health care of patients, avoiding both unnecessary hospitalizations and treatments. Also, Xpert carries a saving for our hospital.

Palavras-chave : Tuberculosis; Pulmonary diagnosis; Real-time Polymerase Chain Reaction; Sensitivity and specificity; Cost-benefit analysis.

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