**5. Illustration**

This section focuses on two hospitals studies for defining their existing system finding inconsistencies and points to improving by applying the previous methodology and using adapted new technologies tools for increasing the hospitals performance. The first hospital had just integrated a new building and would like to use this opportunity for transforming digitally its logistics flow organization. The second hospital already started working with lean manufacturing for structuring its storage area and needs to reduce products dispatching and to optimize all logistics flows. The focus was made on six flows for the improvement: meals, patients, medicines, cloths, consumables, and wastes.

After the use of the methodology for defining the existing system, and finding non-added values and added values, a detailed digital transformation process has been applied on each hospital. New technologies and tools were defined for increasing the hospital flow performance. For instance, Automated Intelligent Vehicles have been chosen for transporting products and reducing waste time for nurses and caregivers. The Automated Intelligent Vehicles (AIVs) solution exemplifies how logistics applications 4.0 and lean manufacturing can contribute to help fighting against the pandemic through the personal health reduction of exposure to the virus. The **Figure 8** presents the result of the transport time optimization in the first hospital. This data concerns the dispatching flows and human non-values were identified. The integration of the AIV allows to reduce the duration of tasks but also serves as a gain of time for nurses and caregivers.

In the two hospitals studied in this paper for validating concepts elaborated, nurses and caregivers spent their times by managing the logistics and transportation of food, medicines, and materials. This situation contributes to the increase of contact between professionals, patients, and different departments, thus influencing the increase of exposure to the virus. Besides, with the need for more health


#### **Figure 8.**

*Non-added transport time optimization.*

professionals, to support the flow of Covid patients, the more time they must contribute to the quality of care and not to the logistics, will increase their capacity to give people the right and well-done treatment.

The study in these two hospitals even before the pandemic showed that the number of patients was increasing in the hospitals, but no increase of nurses. The results of one hospital were about 2700 additional hours to be paid to the nurses. This situation has to be suppressed probably been increased by the covid pandemic. Then, the implementation of AIVs within hospital logistics will contribute to the following aspects:


The **Figure 9** shows the model of AIVs studied in a second hospital located in the south of the Ile de France region. The referring hospital elaborated by exploiting data acquired in these two hospitals had 4 AIVs and delivered medicines and meals on 5 floors. These tools according to the digital twin developed were sufficient for ensuring all the products dispatching in each of these hospitals.

Applying the hospital logistics optimization system presented in this paper to the medicine distribution process presented in **Figure 4**, it was possible to find several possibilities of improvement. The most impacting was the application of the AIV system presented in this chapter since the process had 16 transport operators in which at least 8 could be replaced by AIVs and affected to more important tasks. Thus, it was possible to reduce 50% of the transport actions performed by nurses and caregivers, giving more energy and time for activities related to patient care.

In both hospital cases the desire to integrate new technologies and tools for optimizing all their flows and making their health personnel available for other tasks was high. These hospitals give data and information for defining reference models for healthcare logistics flow. The management of all these data and the diversity of

*How to Improve Hospital Flows in the Context of the COVID Pandemic DOI: http://dx.doi.org/10.5772/intechopen.98672*

decision to take, validate the need of a decision-aided tool for driving the digital transformation process in hospitals. The digital twins are being developed for each hospital and will participate to the improvement of the reference model for healthcare 4.0. The digital transformation of these hospital is growing up.
