A System Dynamics Approach to Workload Management of Hospital Pharmacy Staff: Modeling the Tradeoff between Dispensing Backlog and Dispensing Errors

OCCUPATIONAL APPLICATIONS

We adopted a system dynamics approach to simulate dynamic factors affecting dispensing backlog and dispensing errors in a hospital pharmacy system. This approach allowed us to simulate diverse scenarios (hospital winter pressures and differing staffing arrangements) and to understand the potential unintended impact of rework due to dispensing errors, which is often missing from model-based approaches. The results revealed the impacts of key factors (high workload, staff capacity, backlog, incoming prescriptions, errors, and delay) on system performance and safety within hospital pharmacies. Use of a system dynamics model can provide pharmacy management with practical tools to understand the unintended adverse effects of dynamic factors that contribute to dispensing backlog and errors.

TECHNICAL ABSTRACT

Background (or Rationale): The traditional hospital pharmacy staffing management model does not account for the complex interactions of social, technical, and environmental factors that can affect performance and safety. Conventionally, workload and dispensing errors within the hospital pharmacy system have been analyzed on a factor-by-factor level, using linear and static approaches that ignore feedback mechanisms.

Purpose: We aimed to explore the potential of a system dynamics approach to modeling staffing level management in a hospital pharmacy.

Methods: Qualitative and quantitative system dynamics models were created to simulate dynamic aspects contributing to dispensing backlog and errors in a hospital pharmacy. A baseline scenario was tested in a “normal” condition, and three different staffing level scenarios (fixed, flexible, and equivalent-fixed) were tested in an extreme condition (hospital winter pressures).

Results: During hospital winter pressures, the unintended negative effect on rework due to dispensing errors made it more challenging to deal with demand variability. Findings from the scenario-based simulations revealed that a flexible staffing level arrangement, which dynamically adjusts the number of staff to demand variability during winter pressure, is less effective in reducing the amount of rework than maintaining an equivalent-fixed staffing level. Dispensing backlog during winter pressure can be averted or substantially diminished by proactively employing an equivalent-fixed staffing level that accounts for total staff capacity needed vis-à-vis the current workload. Premature release of extra staff and delayed calling of additional staff from wards can have significant impacts on backlog.

Conclusions: Our results demonstrate that system dynamics can provide practical insights into staffing level management in a hospital pharmacy, by accounting for dynamic factors causing dispensing backlog and errors and presenting decision-makers with a holistic understanding of elements affecting system safety and performance.

Keywords:

• Systems analysis
• computer simulation
• pharmacy dispensary

Acknowledgments

Authors would like to thank the staff at University Hospitals of Leicester (UHL) for their support throughout this study.