Multi-institutional compounding units: evaluation of a new model of production

Introduction

In 2014, we centralized the chemotherapy compounding units of two institutions, i.e. 100, 000 preparations / year (35,000 for site A and 65,000 for B) instead of leaving 1 unit in each. We question the choice of this economic model.

Objectives

The aim is to compare the operating costs of two separate units, one on Site A and the other on Site B with our current unit.

Materials and methods

We revised the preparations’ history of our software (Chimio® - Computer engineering) and determined:

• The cost related to the destruction of the leftovers of unstable expensive drugs in 2 separate units compared to a single unit.
• The staff and equipment needed to ensure the production if it had been carried out on two separate units in comparison with those of the current unit.

Results

€ 80,000 is saved per year by reusing 20% more leftovers compared to a system with two separate units

To ensure a similar level of service, ie a continuous opening on weekdays from 7am to 6pm, 9.6 technicians would be needed for site A and 14.4 for site B while this activity is carried out by 19.6 technicians on our unit. This allows a saving of €185 000 / year.

The number of pharmacists would also be superior since 2 would be needed for Site A and 2 for Site B, 1 more than at present. This represents an additional cost of 77 000 € / year.

It also allows the mutualization of equipments with the gain of an isolator and a spectrophotometer for a saving of €55 000 / year for 7 years (amortization period of equipments)

Conclusion

This production model saves 397 000 € / year while allowing a greater specialization of the teams. It would be necessary to adjust the pharmaceutical time of the site A according to possible mutualizations of activities.

The economy made by the diminution of leftovers’ destruction is minimal because of the regrouping of activity by medical specialties on a single site. The main area of improvement now lies in optimizing the management of anticipated treatments: dose banding and reallocation.