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NICOLA SCICHILONE

Healthcare costs of the SATisfaction and adherence to COPD treatment (SAT)study follow-up

  • Autori: Corsico A.G.; Braido F.; Contoli M.; Di Marco F.; Rogliani P.; Scognamillo C.; Olivi I.; Santus P.; Scichilone N.; Lazzaro C.
  • Anno di pubblicazione: 2019
  • Tipologia: Articolo in rivista
  • OA Link: http://hdl.handle.net/10447/375078

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is characterised by recurring exacerbations. We estimated the costs of healthcare resources for COPD management funded by the Italian National Healthcare Service (INHS) for one year.Methods: We examined the demographic, clinical, and economic variables at enrolment and follow-up visits (at 6 and 12 months) of COPD patients participating in the SAT study and referred to 20 Italian pulmonary centres with different institutional characteristics. Costs were expressed in Euro ((sic)) 2018. A random effects log-linear panel regression model was performed to predict the average cost per patient.Results: Most of the centres were public institutions (90%; public university hospital: 30%). The total average cost of COPD was (sic)2647.38/patient and ICS/LABA/LAMA therapy contributed the most ((sic)1541.45). The average cost was (sic)6206.19/patient for severe COPD (+139.67% vs the cost/patient with mild or moderate COPD). The regression model showed that, others things being equal, increases in the predicted average logged cost per patient were due to liquid oxygen therapy (+468.31%), three COPD exacerbations during the follow-up (+254.54%), and ICS/LABA or ICS/LABA/LAMA associated therapy (+59.26%). Moreover, a 1.19% increment was observed for each additional score of the CAT questionnaire. Conversely, a 36.52% reduction in the predicted average logged cost was reported for hospitals managed by local healthcare authorities.Conclusions: The health econometric approach is innovative in the management of COPD patients in Italy. The results of the random effects log-linear panel data regression model may help clinicians estimate INHS costs when managing COPD patients.