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Arch Intern Med. 2002 Nov 25;162(21):2437-42.

Interhospital differences in nosocomial infection rates: importance of case-mix adjustment.

Author information

1
Infection Control Program, Department of Internal Medicine, University of Geneva Hospitals, 1211 Geneva 14, Switzerland.

Abstract

BACKGROUND:

Nosocomial infection rates are used to assess patient safety and the effectiveness of health care systems, but adjustment for case-mix, a key factor for benchmarking, is often overlooked.

OBJECTIVES:

To perform a nationwide prevalence study of nosocomial infection and evaluate the impact of hospital size on infection rates.

METHODS:

One-week-period prevalence study in 18 acute care hospitals ranging from small primary to large tertiary care institutions. All adult inpatients in medical, surgical, and intensive care units hospitalized at time of study were included. Infection prevalence and case-mix determinants were calculated according to hospital size. After each factor was tested for its significance on the occurrence of nosocomial infection, all factors were introduced in a multivariate model with hospital size as the main explanatory variable and nosocomial infection as the dependent variable.

RESULTS:

Among 4252 patients, 429 developed 470 nosocomial infections, for an overall prevalence of 10.1% (intensive care units, 29.7%; medical, 9.3%; surgical, 9.2%; and mixed wards, 14.1%). Unadjusted prevalence rates were 6.1% in small, 10.0% in intermediate, and 10.9% in large hospitals (P =.007). Increased comorbidity (odds ratio, 1.80), cancer (1.68), trauma (1.75), neutropenia (4.66), antibiotic exposure (6.64), history of intensive care unit stay (2.14), referral from another hospital (1.87), intubation for 24 hours or more (2.09), and prolonged stay (3.35) were independently associated with nosocomial infection (all P<.05), but hospital size was not.

CONCLUSIONS:

Higher infection rates observed in larger hospitals were partly associated with unfavorable case mix. Unadjusted rates may lead to erroneous assumptions for health care prioritization.

PMID:
12437402
[Indexed for MEDLINE]

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