A model for calculating costs of hospital-acquired infections: an Italian experience.
OBJECTIVE
Many approaches on the economic aspect of hospital acquired infections (HAIs) have two major limitations: first, the lack of distinction between resources attributable to the management of HAI and resources absorbed by the main clinical problem for which the patient was hospitalized, and second, the lack of an adequate method for calculating the relative costs. These assume that the resources used by HAI can be determined by measuring the extra days of length of days (LOS) of infected patients versus non-infected patients and attribute to extra-LOS a value to the mean total cost. The aim of the article is to test a cost-modelling method that could overcome these limitations by applying the appropriateness evaluation protocol to the medical charts of patients with hospital-acquired symptomatic urinary tract infection (UTI) or sepsis, and by using cost-centre accounting.


METHODS
The paper explains and tests a model for calculating costs of HAIs.


RESULTS
The data analysis showed that it is not always true that infections protract LOS: five out of 25 sepsis cases have extra-LOS and eight out of 25 UTI cases have extra-LOS, while the cases of sepsis that arose in surgery ward and intensive care units and urinary tract infections in ICU are without prolongation of LOS. The data analysis also showed that, using the mean total cost, the three cases of sepsis in the general surgery and the six in the ICU did not incur costs, nor did the two cases of UTI in ICU, so that they appear to be infections at zero cost. Moreover, the weight of the cost for the bed, or for the diagnostic services, or for the pharmacological treatment, varied widely depending on the site of the HAI and the ward where the patient was hospitalized.


CONCLUSIONS
The method can be applied in any hospital.
Gianino
M M
MM
Dipartimento di Sanità Pubblica e di Microbiologia, Università degli Studi di Torino, Turin, Italy. mariola.gianino@unito.it
Vallino
A
A
Minniti
D
D
Abbona
F
F
Mineccia
C
C
Silvaplana
P
P
Zotti
C M
CM
D001509:Bed Occupancy; D003361:Cost Allocation / Q000379:methods*; D003428:Cross Infection / Q000175:diagnosis / Q000188:drug therapy / Q000191:economics*; D016527:Drug Costs / Q000706:statistics & numerical data; D004866:Equipment Contamination / Q000191:economics; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006757:Hospital Units / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D017053:Infection Control / Q000191:economics* / Q000379:methods; D007558:Italy; D007902:Length of Stay / Q000706:statistics & numerical data; D017059:Models, Econometric; D017064:Process Assessment, Health Care / Q000191:economics / Q000379:methods*; D018805:Sepsis / Q000175:diagnosis / Q000188:drug therapy / Q000191:economics*; D014552:Urinary Tract Infections / Q000175:diagnosis / Q000188:drug therapy / Q000191:economics*