Queuing management study at the Multidisciplinary Anesthesia and Intensive Care Clinic of CNHU-HKM in April 2022
Abstract
Objective: Constant availability of inpatient beds in an intensive care unit (ICU) is part of the resilience of health systems, especially in an emergency context, namely in public health. This study aims to appraise the management of inpatient waiting lines in the ICU of Hubert Koutoukou Maga National Hospital and University Center (CNHU-HKM) in Benin, in March-April 2022.
Methods: This was an analytic cross-sectional study of inpatients or their relatives and staff, selected by convenience and reasoned choice, respectively, carried out from March 21 to April 15, 2022. Logistic regression was used to identify associated factors with queues management.
Results: Altogether 55 patients were surveyed. On a daily basis, 13 ± 1 patients were hospitalized in 18 functional beds for 3 ± 1 admissions and 3 ± 1 discharges. The average bed occupancy rate was 89.8% ± 3.8%; the average waiting time before patient care was 3.6 ± 1.2 minutes and the traffic intensity were 0.03. Per hour, the odds of having a patient were 33.29%, with a 97% chance of a bed being occupied. The probability that an admitted patient would spend a whole week there was 37%. Only patient arrival flow was significantly associated with insufficient queuing management. There was also a lack of inpatient beds and technical boards. The construction of two wards and the installation of seven additional beds could improve queues management.
Conclusions: The management of AF in our study site depends mainly on the daily flow of arriving patients, but also on the number of available hospital beds, the working organization and the existing technical and structural measures. Addressing these parameters will significantly improve the situation.
Methods: This was an analytic cross-sectional study of inpatients or their relatives and staff, selected by convenience and reasoned choice, respectively, carried out from March 21 to April 15, 2022. Logistic regression was used to identify associated factors with queues management.
Results: Altogether 55 patients were surveyed. On a daily basis, 13 ± 1 patients were hospitalized in 18 functional beds for 3 ± 1 admissions and 3 ± 1 discharges. The average bed occupancy rate was 89.8% ± 3.8%; the average waiting time before patient care was 3.6 ± 1.2 minutes and the traffic intensity were 0.03. Per hour, the odds of having a patient were 33.29%, with a 97% chance of a bed being occupied. The probability that an admitted patient would spend a whole week there was 37%. Only patient arrival flow was significantly associated with insufficient queuing management. There was also a lack of inpatient beds and technical boards. The construction of two wards and the installation of seven additional beds could improve queues management.
Conclusions: The management of AF in our study site depends mainly on the daily flow of arriving patients, but also on the number of available hospital beds, the working organization and the existing technical and structural measures. Addressing these parameters will significantly improve the situation.
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PDFDOI: https://doi.org/10.5430/jha.v11n2p25
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Journal of Hospital Administration
ISSN 1927-6990(Print) ISSN 1927-7008(Online)
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