title: Using linear programming to minimize the cost of nurse personnel.
abstract: Nursing personnel costs make up a major portion of most hospital budgets. This report evaluates and optimizes the utility of the nurse personnel at the Internal Medicine Outpatient Clinic of Wake Forest University Baptist Medical Center. Linear programming (LP) was employed to determine the effective combination of nurses that would allow for all weekly clinic tasks to be covered while providing the lowest possible cost to the department. Linear programming is a standard application of standard spreadsheet software that allows the operator to establish the variables to be optimized and then requires the operator to enter a series of constraints that will each have an impact on the ultimate outcome. The application is therefore able to quantify and stratify the nurses necessary to execute the tasks. With the report, a specific sensitivity analysis can be performed to assess just how sensitive the outcome is to the stress of adding or deleting a nurse to or from the payroll. The nurse employee cost structure in this study consisted of five certified nurse assistants (CNA), three licensed practicing nurses (LPN), and five registered nurses (RN). The LP revealed that the outpatient clinic should staff four RNs, three LPNs, and four CNAs with 95 percent confidence of covering nurse demand on the floor. This combination of nurses would enable the clinic to: 1. Reduce annual staffing costs by 16 percent; 2. Force each level of nurse to be optimally productive by focusing on tasks specific to their expertise; 3. Assign accountability more efficiently as the nurses adhere to their specific duties; and 4. Ultimately provide a competitive advantage to the clinic as it relates to nurse employee and patient satisfaction. Linear programming can be used to solve capacity problems for just about any staffing situation, provided the model is indeed linear.
authors.affiliation: Wake Forest University School of Medicine, USA.
authors.forename: Charles H
authors.initials: CH
authors.lastname: Matthews
mesh_terms: D016519:Hospitals, Religious; D009741:Nursing Staff, Hospital / Q000191:economics*; D019982:Organizational Case Studies; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration*