Abstract

BackgroundNosocomial, or healthcare-associated infections (HAI), exact a high medical and financial toll on patients, healthcare workers, caretakers, and the health system. Interpersonal contact patterns play a large role in infectious disease spread, but little is known about the relationship between health care workers’ (HCW) movements and contact patterns within a heath care facility and HAI. Quantitatively capturing these patterns will aid in understanding the dynamics of HAI and may lead to more targeted and effective control strategies in the hospital setting.MethodsStaff at 3 urban university-based tertiary care hospitals in Canada completed a detailed questionnaire on demographics, interpersonal contacts, in-hospital movement, and infection prevention and control practices. Staff were divided into categories of administrative/support, nurses, physicians, and “Other HCWs” - a fourth distinct category, which excludes physicians and nurses. Using quantitative network modeling tools, we constructed the resulting HCW “co-location network” to illustrate contacts among different occupations and with locations in hospital settings.ResultsAmong 3048 respondents (response rate 38%) an average of 3.79, 3.69 and 3.88 floors were visited by each HCW each week in the 3 hospitals, with a standard deviation of 2.63, 1.74 and 2.08, respectively. Physicians reported the highest rate of direct patient contacts (> 20 patients/day) but the lowest rate of contacts with other HCWs; nurses had the most extended (> 20 min) periods of direct patient contact. “Other HCWs” had the most direct daily contact with all other HCWs. Physicians also reported significantly more locations visited per week than nurses, other HCW, or administrators; nurses visited the fewest. Public spaces such as the cafeteria had the most staff visits per week, but the least mean hours spent per visit. Inpatient settings had significantly more HCW interactions per week than outpatient settings.ConclusionsHCW contact patterns and spatial movement demonstrate significant heterogeneity by occupation. Control strategies that address this diversity among health care workers may be more effective than “one-strategy-fits-all” HAI prevention and control programs.

Highlights

  • Nosocomial, or healthcare-associated infections (HAI), exact a high medical and financial toll on patients, healthcare workers, caretakers, and the health system

  • Current infection prevention and control (IPC) measures focus on proper performance of both routine practices and additional precautions by all health care workers’ (HCW) [4, 5]

  • Preliminary attempts to quantify mixing patterns and contact rates have been conducted among the general population on a large scale [6,7,8,9], or in non-healthcare settings [10,11,12], but rates of HCW contacts within healthcare settings are postulated to be significantly higher and more heterogeneous than those within the general population [13]

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Summary

Introduction

Nosocomial, or healthcare-associated infections (HAI), exact a high medical and financial toll on patients, healthcare workers, caretakers, and the health system. Interpersonal contact patterns play a large role in infectious disease spread, but little is known about the relationship between health care workers’ (HCW) movements and contact patterns within a heath care facility and HAI. Capturing these patterns will aid in understanding the dynamics of HAI and may lead to more targeted and effective control strategies in the hospital setting. Close contact between patients and/or healthcare workers (HCWs), and high concentrations of medicallyvulnerable populations, combined with physical movement between treatment areas, are factors that may facilitate HAI spread within health care institutions and the community. Preliminary attempts to quantify mixing patterns and contact rates have been conducted among the general population on a large scale [6,7,8,9], or in non-healthcare settings [10,11,12], but rates of HCW contacts within healthcare settings are postulated to be significantly higher and more heterogeneous than those within the general population [13]

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