Animated Simulation: Determining Cost Effective Nurse Staffing for an Acute Care Unit

Abstract

The purpose of this research project was to determine the appropriate mix of nursing personnel on the day shift for a given workload. The top management team at the Milwaukee Veterans Affairs Medical Center (VAMC) has questioned nursing staffing methodologies for several years. Nurse executives have been unable to educate the top management team on nurse staffing methodologies because they lacked quantifiable data to support the nurse staffing methodologies. Recently, the Department of Veteran Affairs Central Nursing Office instituted a new staffing methodology, called the Expert Panel-Based Methodology. Since this methodology once again utilized subjective data and individual judgments, the top management team was uncertain of its validity. Empirical data was collected for the time studies and retrospective data was analyzed in order to obtain a historical perspective on admissions, discharges, transfers onto the unit, transfers off the unit, average census, and cardiac catheterizations. This data was placed into a statistical package, Stat: :Fit, and the appropriate distributions were assigned to each measurement. The flow of the nursing unit's day shift was modeled in the computer simulation program, MedModel 3.01. A separate program was developed for each day of the week. The researcher then varied the staffing and determined the appropriate nurse staffing mix for the average daily census at the beginning of the shift and the workload for each day of the week.

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Document Details

Document Type
Technical Report
Publication Date
Jun 19, 1997
Accession Number
ADA372426

Entities

People

  • Joan M. Richard

Organizations

  • Academy of Health Sciences

Tags

DTIC Thesaurus Topics

  • Catheterization
  • Computer Programs
  • Computer Simulations
  • Computers
  • Health Care
  • Health Services
  • Intensive Care Units
  • Measurement
  • Medical Personnel
  • Patient Care
  • Personnel Management
  • Simulations
  • Therapy
  • Time Studies
  • Wound Infections

Readers

  • Computational Modeling and Simulation
  • Medical or Health Care Field.