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Incremental changes in the workforce to accommodate changes in demand.

Jonathan F Bard¹, Hadi W Purnomo

¹Graduate Program in Operations Research & Industrial Engineering, I University Station C2200, The University of Texas, Austin, Texas 78712-0292, USA. jbard@mail.utexas.edu

Health Care Management Science

|April 15, 2006

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This study presents two models to solve the nurse addition problem, aiming to minimize uncovered nursing shifts by hiring and scheduling new nurses. The models ensure schedules meet all hard and soft constraints for optimal staffing.

Area of Science:

Operations Research
Healthcare Management

Background:

Service organizations face challenges in dynamic staffing due to fluctuating demand and fixed workforces.
Hiring contract labor, such as agency nurses or travelers, is often a costly solution for staffing shortages.

Purpose of the Study:

To address the nurse addition problem by developing models for hiring and scheduling temporary nursing staff.
To minimize the maximum number of daily uncovered shifts within a planning horizon.

Main Methods:

Developed two mathematical models for the nurse addition problem.
The first model uses a pattern-view formulation, adapted from midterm preference scheduling.
The second model employs a shift-view formulation solved via a branch-and-price algorithm.

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Main Results:

Both models aim to hire nurses and assign midterm schedules to minimize uncovered shifts.
Rosters must adhere to hard constraints (working hours, stretches, breaks, weekends) and soft constraints.

Conclusions:

The presented models offer a structured approach to optimizing the addition of nursing staff.
These methods can help reduce reliance on expensive contract labor by improving midterm scheduling efficiency.