The Science Journal of the American Association for Respiratory Care

2008 OPEN FORUM Abstracts


Harry Morris1

Background: Meeting the clinical demands of a large tertiary hospital is demanding in and of itself. Staffing within the earned labor budget adds another dimension. Respiratory Care departments earn their labor in a number of ways; billable procedures, case mix adjusted-adjusted patient days and the daily patient census, to name a few. Our department earns its labor from the daily patient census. Our staffing model was causing us to use labor in excess of our budget. We were given a forecasting tool from the department of Operations Performance Improvement to assist us in staffing our shifts within the budget. Clinical shift supervisors use this tool to forecast the number of allowed staff based on the patient census. The purpose of this study is to demonstrate that through the application of available concepts and data, staffing a complex department can be accomplished within budget.

Methods: Using historical labor data, we were able to see how we were performing under previous assumptions. Implementing a grid that allows the user to input daily staffing data along with the census and the WHPUOS, the supervisors could easily see if they were staffed within budget or were overstaffed. By diligently applying this method of staffing on a daily basis the supervisors are able to bank labor early in the month and save labor for days when the acuity is excessively high.

Results: Initially, our staffing model appeared to be too robust and we were not going to be successful. By making adjustments to our staffing model we were able to bring our labor usage from 16.7 FTEs over budget to being on budget within 4 months without experiencing quality issues.

Conclusion: The previous staffing model of staffing based on perceived, anecdotal perceptions would not allow us to meet our labor goals. By applying the forecasting tool, we were able to demonstrate that we could staff ourselves safely and still remain within budget. The tool works. The clinical shift supervisors understand how to apply this tool to accurately meet the clinical demands of our institution. By banking labor on higher census days, they can still meet the needs of lower census days that may have a high acuity.