OBJECTIVE: To model the economic costs of hospital-acquired infections (HAIs) in New Zealand, by type of HAI. DESIGN: Monte Carlo simulation model. SETTING: Auckland District Health Board Hospitals (DHBH), the largest publicly funded hospital group in New Zealand supplying secondary and tertiary services. Costs are also estimated for predicted HAIs in admissions to all hospitals in New Zealand. PATIENTS: All adults admitted to general medical and general surgical services. METHOD: Data on the number of cases of HAI were combined with data on the estimated prolongation of hospital stay due to HAI to produce an estimate of the number of bed days attributable to HAI. A cost per bed day value was applied to provide an estimate of the economic cost. Costs were estimated for predicted infections of the urinary tract, surgical wounds, the lower and upper respiratory tracts, the bloodstream, and other sites, and for cases of multiple sites of infection. Sensitivity analyses were undertaken for input variables. RESULTS: The estimated costs of predicted HAIs in medical and surgical admissions to Auckland DHBH were dollar 10.12 (US dollar 4.56) million and dollar 8.64 (US dollar 3.90) million, respectively. They were dollar 51.35 (US dollar 23.16) million and dollar 85.26 (US dollar 38.47) million, respectively, for medical and surgical admissions to all hospitals in New Zealand. CONCLUSIONS: The method used produces results that are less precise than those of a specifically designed study using primary data collection, but has been applied at a lower cost The estimated cost of HAIs is substantial but only a proportion of infections can be avoided. Further work is required to identify the most cost-effective strategies for the prevention of HAI.
OBJECTIVE: To model the economic costs of hospital-acquired infections (HAIs) in New Zealand, by type of HAI. DESIGN: Monte Carlo simulation model. SETTING: Auckland District Health Board Hospitals (DHBH), the largest publicly funded hospital group in New Zealand supplying secondary and tertiary services. Costs are also estimated for predicted HAIs in admissions to all hospitals in New Zealand. PATIENTS: All adults admitted to general medical and general surgical services. METHOD: Data on the number of cases of HAI were combined with data on the estimated prolongation of hospital stay due to HAI to produce an estimate of the number of bed days attributable to HAI. A cost per bed day value was applied to provide an estimate of the economic cost. Costs were estimated for predicted infections of the urinary tract, surgical wounds, the lower and upper respiratory tracts, the bloodstream, and other sites, and for cases of multiple sites of infection. Sensitivity analyses were undertaken for input variables. RESULTS: The estimated costs of predicted HAIs in medical and surgical admissions to Auckland DHBH were dollar 10.12 (US dollar 4.56) million and dollar 8.64 (US dollar 3.90) million, respectively. They were dollar 51.35 (US dollar 23.16) million and dollar 85.26 (US dollar 38.47) million, respectively, for medical and surgical admissions to all hospitals in New Zealand. CONCLUSIONS: The method used produces results that are less precise than those of a specifically designed study using primary data collection, but has been applied at a lower cost The estimated cost of HAIs is substantial but only a proportion of infections can be avoided. Further work is required to identify the most cost-effective strategies for the prevention of HAI.
Authors: Alan F Merry; Derryn A Gargiulo; Ian Bissett; David Cumin; Kerry English; Christopher Frampton; Richard Hamblin; Jacqueline Hannam; Matthew Moore; Papaarangi Reid; Sally Roberts; Elsa Taylor; Simon J Mitchell Journal: Trials Date: 2019-06-10 Impact factor: 2.279
Authors: Ziad W Jaradat; Qutaiba O Ababneh; Sherin T Sha'aban; Ayesha A Alkofahi; Duaa Assaleh; Anan Al Shara Journal: Pathog Glob Health Date: 2020-10-28 Impact factor: 2.894
Authors: Nicole Mittmann; Marika Koo; Nick Daneman; Andrew McDonald; Michael Baker; Anne Matlow; Murray Krahn; Kaveh G Shojania; Edward Etchells Journal: Drug Healthc Patient Saf Date: 2012-10-05