The main activity of the diagnostic centre is to take blood samples from patients, analyze them and report the results back to the physician or patient. Sometimes they advise the patient with respect to the medicine they take, for example in the case of diabetes. Some of the patients come to the hospital to have a blood sample taken. Many of the blood samples however are taken at service locations of the diagnostic centre in the area around the location of the hospital. In this case there are about 30 different service locations where a patient can go, to have their blood sample taken.
The employees of the diagnostic center work at the service locations and take the blood samples from the service location to a laboratory to have them analyzed. As an extra service the employees also visits patients at home to take a blood sample. Currently the employees visit the patient at home before and after they work at the service location. This takes careful planning because patients at the service location must not be kept waiting. As you may guess an important condition in the collection process is to have the blood at the laboratory in time. Blood can not be kept indefinitely; it must be delivered on time to the laboratory, otherwise no analyses can be performed.
As you can see this is a rather complex logistic process. Many questions arise, such as
- Are there enough locations available for the patients to go to, or should the number be changed?
- What should be the opening times and the geographic position of each of these locations?
- Should all the blood samples be taken directly to the laboratory, or should they be collected first at specific places in the network. In other words should hubs be used?
- Should from an employees point of view the samples taken at the patient’s home be combined with the blood samples taken on the service locations of the diagnostic centre?
This is where Operations Research comes in. We analyzed the blood sample logistics with a model that we developed to analyze and optimize supply chains. With this model we can answer questions like where facilities should be situated, how large they should be and which customers should they serve. With this model we found that introducing a few hubs where blood samples are collected from the service locations before taking them to the laboratory saves about 25% of travel time of the employees. This saves time but also the distance traveled, which reduces the costs for the diagnostic center. This time saved can be used to take more blood samples boosting the workforce effectiveness as well.
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