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. 2021 Aug:114:32-42.
doi: 10.1016/j.jhin.2021.03.032.

Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection

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Free article

Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection

S Stewart et al. J Hosp Infect. 2021 Aug.
Free article

Abstract

Background: Few healthcare-associated infection (HAI) studies focus on risk of HAI at the point of admission. Understanding this will enable planning and management of care with infection prevention at the heart of the patient journey from the point of admission.

Aim: To determine intrinsic characteristics of patients at hospital admission and extrinsic events, during the two years preceding admission, that increase risk of developing HAI.

Methods: An incidence survey of adults within two hospitals in NHS Scotland was undertaken for one year in 2018/19 as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. The primary outcome measure was developing any HAI using recognized case definitions. The cohort was derived from routine hospital episode data and linkage to community dispensed prescribing data.

Findings: The risk factors present on admission observed as being the most significant for the acquisition of HAI were: being treated in a teaching hospital, increasing age, comorbidities of cancer, cardiovascular disease, chronic renal failure and diabetes; and emergency admission. Relative risk of developing HAI increased with intensive care unit, high-dependency unit, and surgical specialties, and surgery <30 days before admission and a total length of stay of >30 days in the two years to admission.

Conclusion: Targeting patients at risk of HAI from the point of admission maximizes the potential for prevention, especially when extrinsic risk factors are known and managed. This study proposes a new approach to infection prevention and control (IPC), identifying those patients at greatest risk of developing a particular type of HAI who might be potential candidates for personalized IPC interventions.

Keywords: Adjustment; Epidemiology; Hospital-acquired infection; Logistic regression; Multivariate analysis; Risk; Risk factors.

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