Accounting for patient heterogeneity in nurse staffing using a queueing-theory approach
Eimanzadeh, Parisa Gloede, Heather Soule, Joyce Salari, Ehsan
Eimanzadeh, Parisa
Gloede, Heather
Soule, Joyce
Salari, Ehsan
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2018-06-30
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Article
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Keywords
Multi-class finite-source queues,Nurse staffing,Patient acuity,Queueing theory
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Parisa Eimanzadeh, Heather Gloede, Joyce Soule & Ehsan Salari (2018) Accounting for patient heterogeneity in nurse staffing using a queueing-theory approach, Health Systems
Abstract
Evidence from observational studies suggests that inadequate nurse staffing in hospitals and heavy nurse workload may compromise patient safety and quality of care. There are recommended minimum nurse-to-patient ratios for different types of inpatient care settings. However, nursing-care intensity may vary across different patients within an inpatient unit depending on the severity of their medical condition, potentially rendering fixed nurse-to-patient ratios ineffective. This study aims at developing nurse-staffing strategies that explicitly account for patient heterogeneity. Using queueing theory, we develop a stochastic framework to model direct nursing care provided in inpatient-care units. The stochastic model is then used to measure different performance metrics that evaluate the efficiency and timeliness of inpatient-care delivery. The trade-off between those performance metrics and the nursing staff level is quantified, which can assist clinicians with determining minimum nursing staff levels that ensure timely delivery of nursing care to a given patient mix.
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Taylor & Francis
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Health Systems;2018
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2047-6965