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Estimating incidence and attributable length of stay of healthcare-associated infections-Modeling the Swiss point-prevalence survey


Doerken, Sam; Metsini, Aliki; Buyet, Sabina; Wolfensberger, Aline; Zingg, Walter; Wolkewitz, Martin (2022). Estimating incidence and attributable length of stay of healthcare-associated infections-Modeling the Swiss point-prevalence survey. Infection Control and Hospital Epidemiology, 43(8):1022-1031.

Abstract

OBJECTIVES

In 2017, a point-prevalence survey was conducted with 12,931 patients in 96 hospitals across Switzerland as part of the national strategy to prevent healthcare-associated infections (HAIs). We present novel statistical methods to assess incidence proportions of HAI and attributable length-of-stay (LOS) in point-prevalence surveys.

METHODS

Follow-up data were collected for a subsample of patients and were used to impute follow-up data for all remaining patients. We used weights to correct length bias in logistic regression and multistate analyses. Methods were also tested in simulation studies.

RESULTS

The estimated incidence proportion of HAIs during hospital stay and not present at admission was 2.3% (95% confidence intervals [CI], 2.1-2.6), the most common type being lower respiratory tract infections (0.8%; 95% CI, 0.6-1.0). Incidence proportion was highest in patients with a rapidly fatal McCabe score (7.8%; 95% CI, 5.7-10.4). The attributable LOS for all HAI was 6.4 days (95% CI, 5.6-7.3) and highest for surgical site infections (7.1 days, 95% CI, 5.2-9.0). It was longest in the age group of 18-44 years (9.0 days; 95% CI, 5.4-12.6). Risk-factor analysis revealed that McCabe score had no effect on the discharge hazard after infection (hazard ratio [HR], 1.21; 95% CI, 0.89-1.63). Instead, it only influenced the infection hazard (HR, 1.84; 95% CI, 1.39-2.43) and the discharge hazard prior to infection (HR, 0.73; 95% CI, 0.66-0.82).

CONCLUSIONS

In point-prevalence surveys with limited follow-up data, imputation and weighting can be used to estimate incidence proportions and attributable LOS that would otherwise require complete follow-up data.

Abstract

OBJECTIVES

In 2017, a point-prevalence survey was conducted with 12,931 patients in 96 hospitals across Switzerland as part of the national strategy to prevent healthcare-associated infections (HAIs). We present novel statistical methods to assess incidence proportions of HAI and attributable length-of-stay (LOS) in point-prevalence surveys.

METHODS

Follow-up data were collected for a subsample of patients and were used to impute follow-up data for all remaining patients. We used weights to correct length bias in logistic regression and multistate analyses. Methods were also tested in simulation studies.

RESULTS

The estimated incidence proportion of HAIs during hospital stay and not present at admission was 2.3% (95% confidence intervals [CI], 2.1-2.6), the most common type being lower respiratory tract infections (0.8%; 95% CI, 0.6-1.0). Incidence proportion was highest in patients with a rapidly fatal McCabe score (7.8%; 95% CI, 5.7-10.4). The attributable LOS for all HAI was 6.4 days (95% CI, 5.6-7.3) and highest for surgical site infections (7.1 days, 95% CI, 5.2-9.0). It was longest in the age group of 18-44 years (9.0 days; 95% CI, 5.4-12.6). Risk-factor analysis revealed that McCabe score had no effect on the discharge hazard after infection (hazard ratio [HR], 1.21; 95% CI, 0.89-1.63). Instead, it only influenced the infection hazard (HR, 1.84; 95% CI, 1.39-2.43) and the discharge hazard prior to infection (HR, 0.73; 95% CI, 0.66-0.82).

CONCLUSIONS

In point-prevalence surveys with limited follow-up data, imputation and weighting can be used to estimate incidence proportions and attributable LOS that would otherwise require complete follow-up data.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Infectious Diseases
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Epidemiology
Health Sciences > Microbiology (medical)
Health Sciences > Infectious Diseases
Language:English
Date:August 2022
Deposited On:11 Nov 2021 11:34
Last Modified:26 Jun 2024 01:43
Publisher:Cambridge University Press
ISSN:0899-823X
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1017/ice.2021.295
PubMed ID:34348807