Covenant Hospital operates a main hospital and three outlying clinics in a medium-size city. All four locations perform similar outpatient services, and patients typically visit the location nearest them. The hospital has recently had more congestion—longer waiting lines—than it (or its patients) would like. As part of a study to learn the causes of these long lines and to suggest possible solutions, all locations have kept track of customer arrivals during 1-hour intervals for the past 10 weeks. All locations are open Monday through Friday from 9 a.m. until 5 p.m. and on Saturday from 9 a.m. until noon.
For each location, the hospital and clinics collected data that contains the number of customer arrivals during each hour of a 10-week period. The manager of Covenant has hired you to make some sense of these data. Specifically, your task is to present charts and/or tables that indicate how customer traffic into the hospital locations varies by day of week and hour of day. There is also interest in whether any daily or hourly patterns you observe are stable across weeks. Although you don't have full information about the way the hospital currently runs its operations—you know only its customer arrival pattern and the fact that it is currently experiencing long lines—you are encouraged to append any suggestions for improving operations based on your analysis of the data.
In this assignment we analyse the operations of Covenant Hospital. Covent Hospital has four hospitals in the city. Out of the four hospitals one of the hospitals is the main hospital while other three are outlying clinics. According to the given situation, the hospital is facing a staffing problem. The hospital is open from Monday to Saturday. From Monday to Friday the hospital is open from 9am to 5pm. On Saturday the hospital is open from 9 am to noon.
The analysis of the data shows that the average number of patients from Monday to Thursday in a particular clinic is approximately similar. Thus, the average number of patients visiting Clinic 1 from Monday to Thursday is roughly similar. Similarly, for Clinic 2,3 and4. However, the average number of patients in the particular clinic increases on Friday’s and Saturdays. The average number of patients visiting the clinic is highest on Saturdays (sheet 1).
The analysis of average number of patients visiting a clinic at a particular time shows that irrespective of days the number of patients visiting a clinic is low during the start of the clinic i.e., at 9:00 am. However, the average number of patients visiting a clinic peaks during the period of 1:00 am to 1:00 pm. From 1:00 pm to 4:00 pm the average number of patients visiting the clinic slowly falls. Further, the number of patients again increases during 4:00 pm to 5:00 pm. The least number of patients visit the clinic during 3 to 4 pm (sheet 1).
Analysis of the number of patients visiting any of the four clinics from Monday to Saturday shows that the number of patients visiting the clinic on Fridays at any particular time is the highest of the particular time. Moreover, the number of patients visiting the clinic on Saturdays is the highest throughout the time 9:00 am to noon. Furthermore, the data shows that the total number of patients visiting the clinic is highest during the time 11:00 am to 1:00 pm on all working days. The analysis also shows that the least number of patients visited the clinic during the time 3:00 pm to 4:00 pm (sheet 2)
The data presents only information regarding the number of patients visiting the clinic. On the basis of the data it can be visualised that the longest line would be formed during the period 11:00 am to 1:00 pm on all working days. Similarly, the longest line may be formed on Fridays and Saturdays as compared to other working days. More data is required to further analyse the problem.
This problem has been solved.
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