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

S. Stewart, C. Robertson, S. Kennedy, K. Kavanagh, L. Haahr, S. Manoukian, H. Mason, S. Dancer, B. Cook, J. Reilly

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
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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.
Original languageEnglish
Pages (from-to)32-42
Number of pages11
JournalJournal of Hospital Infection
Volume114
Early online date21 Jul 2021
DOIs
Publication statusPublished - 31 Aug 2021

Keywords

  • epidemiology
  • hospital-acquired infection
  • multivariate analysis
  • adjustment
  • risk
  • risk factors
  • logistic regression

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