Stephen E. Brossette

The costs of nosocomial infections.

Background:Although nosocomial infections (NIs) are widely regarded as expensive complications of healthcare delivery, their costs have not been rigorously quantified in large-scale studies. Additionally, problems that can bias cost estimates have often gone unaddressed. For example, are NIs more likely to cause significant extra length of stay (LOS) and costs, or are they more likely to be relatively inexpensive and inevitable consequences of long and expensive hospitalizations? This study is the largest of its kind to provide a rigorous analysis of the costs of NIs. Objective:To precisely bound the attributable costs of a NI using large-scale data and to determine the effects of endogeneity between NIs and LOS on cost estimates. Design, Setting and Patients:Discharge diagnoses, cost, LOS, and NI data were collected for 1,355,347 admissions from March 30, 2001 to January 31, 2006 in 55 hospitals. Main Outcome Measures:The cost effects of NIs (in 2007

Cost of bloodstream infections

) were estimated using multivariable regression models. Restricted models were applied to determine how cost estimates are confounded by disease severity and LOS. Results:NIs are associated with

The effects of laparoscopic cholecystectomy, hysterectomy, and appendectomy on nosocomial infection risks.

12,197 (95% CI,

System and method of pill identification

4862–

Method for measuring the incidence of hospital acquired infections

19,533, P < 0.001) in incremental cost. A lower bound estimate of infection cost, controlling for LOS, is

SYSTEM AND METHOD OF ADAPTIVE COLOR CORRECTION FOR PILL RECOGNITION IN DIGITAL IMAGES

4644 (95% CI,

System and method of using imprint analysis in pill identification

1266–

Tray set for supporting a marker-based target for identifying solid medicines

7391). Conclusions:NIs are associated with substantial increases in the costs of inpatient care, even when estimates are corrected for potential endogenous confounding.

Système et procédé d'utilisation d'une analyse d'empreinte dans l'identification d'une pilule

BACKGROUND Hospital-acquired bloodstream infections (BSIs) are relatively rare but do not occur randomly. This suggests that unobserved confounding factors can bias estimates of BSI-associated incremental costs of care. Compared with previous studies, this analysis used a large sample size for greater precision, actual cost-accounting data, and case matching combined with bounding estimates to correct for bias. METHODS Data from 1,355,647 admissions during 69 months in 55 hospitals were collected from a large population database. BSIs were identified by the Nosocomial Infection Marker, a well-validated, electronic, laboratory-based marker used for automatic infection surveillance. Costs were obtained by matching laboratory data with hospital accounting system calculations and converted to 2006 US dollars. RESULTS Of 58,376 presumed nosocomial infections, 12,578 (21.6%) were identified as BSIs. More than 50% of BSIs occurred within the first week of hospitalization and 80% during the first 2 weeks. Various analyses resulted in the following estimates of BSI-associated incremental costs: basic regression analysis,

ADAPTIVE COLOR CORRECTION FOR PILL RECOGNITION IN DIGITAL IMAGES

19,643 (P < .0001; 95% confidence interval [CI]: