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Adaptive staff scheduling at Outpatient Department of Ntaja Health Center in Malawi - A queuing theory application

Accurate staff scheduling is crucial in overcoming the problem of mismatch between staffing ratios and demand for health services which can impede smooth patient flow. Patient flow is an important process towards provision of improved quality of service and also improved utilization of hospital reso...

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Detalles Bibliográficos
Autores principales: Mtonga, Kambombo, Gatera, Antoine, Jayavel, Kayalvizhi, Nyirenda, Mwawi, Kumaran, Santhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PAGEPress Publications, Pavia, Italy 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8941316/
https://www.ncbi.nlm.nih.gov/pubmed/34781628
http://dx.doi.org/10.4081/jphr.2021.2347
Descripción
Sumario:Accurate staff scheduling is crucial in overcoming the problem of mismatch between staffing ratios and demand for health services which can impede smooth patient flow. Patient flow is an important process towards provision of improved quality of service and also improved utilization of hospital resources. However, extensive waiting times remains a key source of dissatisfaction with the quality of health care service among patients. With rarely scheduled hospital visits, the in-balance between hospital staffing and health service demand remains a constant challenge in Sub-Saharan Africa. Accurate workload predictions help anticipate financial needs and also aids in strategic planning for the health facility. Using a local health facility for a case study, we investigate problems faced by hospital management in staff scheduling. We apply queuing theory techniques to assess and evaluate the relationship between staffing ratios and waiting times at the facility. Specifically, using patient flow data for a rural clinic in Malawi, we model queue parameters and also approximate recommended staffing ratios to achieve steady state leading to reduced waiting times and consequently, improved service delivery at the clinic.