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Reorganization of nurse scheduling reduces the risk of healthcare associated infections

Eugenio Valdano, Chiara Poletto, Pierre‐Yves Boëlle, Vittoria Colizza

2021Scientific Reports18 citationsDOIOpen Access PDF

Abstract

Efficient prevention and control of healthcare associated infections (HAIs) is still an open problem. Using contact data from wearable sensors at a short-stay geriatric ward, we propose a proof-of-concept modeling study that reorganizes nurse schedules for efficient infection control. This strategy switches and reassigns nurses' tasks through the optimization of shift timelines, while respecting feasibility constraints and satisfying patient-care requirements. Through a Susceptible-Colonized-Susceptible transmission model, we found that schedules reorganization reduced HAI risk by 27% (95% confidence interval [24, 29]%) while preserving timeliness, number, and duration of contacts. More than 30% nurse-nurse contacts should be avoided to achieve an equivalent reduction through simple contact removal. Nurse scheduling can be reorganized to break potential chains of transmission and substantially limit HAI risk, while ensuring the timeliness and quality of healthcare services. This calls for including optimization of nurse scheduling practices in programs for infection control in hospitals.

Topics & Concepts

TimelineInfection controlScheduling (production processes)Health careComputer scienceNurse scheduling problemMedicineNursingMedical emergencyJob shop schedulingOperations managementIntensive care medicineComputer networkEconomicsEconomic growthHistoryArchaeologyRouting (electronic design automation)Flow shop schedulingHealthcare Operations and Scheduling OptimizationInfection Control in HealthcareGeriatric Care and Nursing Homes
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