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J Hosp Infect ; 106(2): 303-310, 2020 Oct.
Article in English | MEDLINE | ID: mdl-32693085

ABSTRACT

BACKGROUND: Little is known about the economic burden of healthcare-associated infections (HAIs) in Brazil. AIM: To analyse the costs of hospitalization by reimbursement from the Brazilian government, via the Brazilian Unified Health System (SUS) affiliation, and direct costs in the adult Intensive Care Unit (ICU). METHODS: The matched-pairs case-control study (83 patients with HAIs and 83 without HAIs) was performed at a referral tertiary-care teaching hospital in Brazil in January 2018. In order to calculate the HAI costs from the perspective of the payer, the total cost for each hospitalization was obtained through the Hospital's Billing Sector. Direct costs were calculated annually for 949 critical patients during 2018. FINDINGS: The reimbursement cost per hospitalization of patients with HAIs was 75% (US$2721) higher than patients without HAIs (US$1553). When a patient has an HAI, in addition to a longer length of stay (15 days), there was an extra increase (US$996) in the reimbursement cost per hospitalization. An HAI in the ICU was associated with a total direct cost eight times higher compared with patients who did not develop infections in this unit, US$11,776 × US$1329, respectively. The direct cost of hospitalization in the ICU without HAI was 56.5% less than the reimbursement (US$1329 × US$3052, respectively), whereas for the patient with an HAI, the direct cost was 111.5% above the reimbursement (US$11,776 × US$5569, respectively). CONCLUSION: HAIs contribute to a longer stay and an eight-fold increase in direct costs. It is necessary to reinforce programmes that prevent HAIs in Brazilian hospitals.


Subject(s)
Cross Infection/economics , Delivery of Health Care/economics , Hospital Costs/statistics & numerical data , Tertiary Care Centers/statistics & numerical data , Adult , Brazil/epidemiology , Case-Control Studies , Child , Cross Infection/epidemiology , Delivery of Health Care/statistics & numerical data , Hospitals, Teaching/statistics & numerical data , Humans , Infant, Newborn , Intensive Care Units/economics , Length of Stay/economics
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