Unknown

Dataset Information

0

Healthcare-associated infections (HAIs) during the coronavirus disease 2019 (COVID-19) pandemic: A time-series analysis.


ABSTRACT:

Objective

To use interrupted time-series analyses to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare-associated infections (HAIs). We hypothesized that the pandemic would be associated with higher rates of HAIs after adjustment for confounders.

Design

We conducted a cross-sectional study of HAIs in 3 hospitals in Missouri from January 1, 2017, through August 31, 2020, using interrupted time-series analysis with 2 counterfactual scenarios.

Setting

The study was conducted at 1 large quaternary-care referral hospital and 2 community hospitals.

Participants

All adults ≥18 years of age hospitalized at a study hospital for ≥48 hours were included in the study.

Results

In total, 254,792 admissions for ≥48 hours occurred during the study period. The average age of these patients was 57.6 (±19.0) years, and 141,107 (55.6%) were female. At hospital 1, 78 CLABSIs, 33 CAUTIs, and 88 VAEs were documented during the pandemic period. Hospital 2 had 13 CLABSIs, 6 CAUTIs, and 17 VAEs. Hospital 3 recorded 11 CLABSIs, 8 CAUTIs, and 11 VAEs. Point estimates for hypothetical excess HAIs suggested an increase in all infection types across facilities, except for CLABSIs and CAUTIs at hospital 1 under the "no pandemic" scenario.

Conclusions

The COVID-19 era was associated with increases in CLABSIs, CAUTIs, and VAEs at 3 hospitals in Missouri, with variations in significance by hospital and infection type. Continued vigilance in maintaining optimal infection prevention practices to minimize HAIs is warranted.

SUBMITTER: Sahrmann JM 

PROVIDER: S-EPMC9879893 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

altmetric image

Publications

Healthcare-associated infections (HAIs) during the coronavirus disease 2019 (COVID-19) pandemic: A time-series analysis.

Sahrmann John M JM   Nickel Katelin B KB   Stwalley Dustin D   Dubberke Erik R ER   Lyons Patrick G PG   Michelson Andrew P AP   McMullen Kathleen M KM   Gandra Sumanth S   Olsen Margaret A MA   Kwon Jennie H JH   Burnham Jason P JP  

Antimicrobial stewardship & healthcare epidemiology : ASHE 20230117 1


<h4>Objective</h4>To use interrupted time-series analyses to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare-associated infections (HAIs). We hypothesized that the pandemic would be associated with higher rates of HAIs after adjustment for confounders.<h4>Design</h4>We conducted a cross-sectional study of HAIs in 3 hospitals in Missouri from January 1, 2017, through August 31, 2020, using interrupted time-series analysis with 2 counterfactual scenarios.<h  ...[more]

Similar Datasets

| 2346925 | ecrin-mdr-crc
| S-EPMC7953962 | biostudies-literature
| S-EPMC9349967 | biostudies-literature
| S-EPMC7508518 | biostudies-literature