title: Three scenarios of clinical claim reimbursement for nosocomial infection: the good, the bad, and the ugly.
abstract: We studied the extent to which hospitals can expect to receive reimbursement for costs relating to nosocomial infections (NI) under the diagnosis-related groups (DRG) system of clinical claims and calculated the loss of reimbursement due to missed or incorrect registration of infective complications on hospital discharge records (HDR). We calculated clinical claim reimbursement in three scenarios: the good, in which all NI are recorded on HDR; the bad, in which a proportion of NI recorded on HDR observed at the 41 participating hospitals; the ugly, in which none of the NI are recorded on HDR. We analysed in which patients the recording of infective complications changed the DRG clinical claim and the economic consequences on reimbursements. Compared with the ugly scenario, the bad scenario, which is closest to what actually occurs, with only 55.9% of NI (180/322) properly recorded, produced an increased DRG clinical claim in 30 cases, of on average 403 for every NI. Compared with the ugly scenario, the good scenario, produced an increased DRG clinical claim in 45 cases with an average reimbursement of 618. The difference between the bad and the good scenarios shows an average loss of 215 for every case. Our calculated good scenario could cover only 3.8% of direct costs per case attributable to NI. Real, tangible benefits in health, both social and economic, will only accrue from the monitoring and control of NI in hospitals.
authors.affiliation: Department of Public Health and Policy, LSHTM, London, UK. ferdinandi.vegni@lshtm.ac.uk
authors.forename: F E
authors.initials: FE
authors.lastname: Vegni
authors.forename: M L
authors.initials: ML
authors.lastname: Panceri
authors.forename: M
authors.initials: M
authors.lastname: Biffi
authors.forename: E
authors.initials: E
authors.lastname: Banfi
authors.forename: A D
authors.initials: AD
authors.lastname: Porretta
authors.forename: G
authors.initials: G
authors.lastname: Privitera
mesh_terms: D003428:Cross Infection / Q000145:classification / Q000191:economics* / Q000453:epidemiology; D003953:Diagnosis-Related Groups; D017721:Hospital Costs; D006801:Humans; D007344:Insurance Claim Reporting; D007349:Insurance, Health, Reimbursement / Q000706:statistics & numerical data*; D007350:Insurance, Hospitalization; D007558:Italy / Q000453:epidemiology; D011446:Prospective Studies