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1.
Med J Armed Forces India ; 79(3): 300-308, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37193519

RESUMO

Background: Hospital administrators are often challenged with overcrowding at hospitals. The study hospital receives referred patients; however, they have to wait in long queues even for getting registered. This was a cause of concern for hospital administrators. The study was undertaken to find an amicable solution to the queues at registration using Queuing Theory. Method: This observational and interventional study was carried out in a tertiary care ophthalmic hospital. In the first phase, data of service time and arrival rate was collected. The queuing model was built using the coefficient of variation (CoV) of the observed times. Server utilization for new patient registration was found to be 1.21 and was 0.63 for revisit patients. Scenario-based simulation carried out using free software for optimal utilization of both types of servers. Recommendations made to combine the registration process and to increase one server were implemented.In the second phase, after one year, patient registration data were collected and compared for the number of patients registered using SPSS 17. Results: Number of patients registered within the registration timings increased whereas the number of patients registered after the registration timings decreased significantly at 95% CI with a p-value of less than 0.001. Queues finished early and more number of patients were registered in the same time. Conclusion: Using queuing theory, the bottleneck of the systems can be identified. Scenario and software-based simulations provide solutions to the problem of queues. The study is an application of Queuing Theory with a focus on efficient resource utilization. It can be replicated in an organization with limited resources facing the challenge of queues.

2.
Med J Armed Forces India ; 78(Suppl 1): S163-S171, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-36147384

RESUMO

Background: Cancellation of surgeries is a regular phenomenon in any hospital, and reasons may vary from clinical to managerial ones. The aim of the study is to suggest scheduling to address the problem of time over run related cancellations. This is an observational and descriptive study conducted in a tertiary care hospital with ophthalmology facilities. The sample size is calculated with 95% confidence interval using Epi Info 6 from the total surgeries performed in the last 5 years (n = 380). Simple random sampling technique was used. Methods: Surgical time for all types of ophthalmic surgeries (n = 582) was observed. Allocation of listed cases to the available operating rooms (ORs) was carried out using the observed time using LEKIN software. Results: The time over-run of 2 h and 6 h was noted for two units, whereas idle OR time was observed in other units. An average idle time of 19% was noted on each day. Reallocation of the cases to the ORs was carried out taking all the planned cases (of both the operating units of the day) as the number of jobs and all the available ORs as parallel machines using LEKIN software. All the planned cases could be accommodated; still, an average of 17% of the total available operation theater (OT) time was found idle on each day. Conclusions: Planning of cases using procedure time and scheduling on a daily basis using allocation models with simple algorithms can provide optimal utilization of OTs and can address the time over-run and related cancellations.

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