The Science Journal of the American Association for Respiratory Care

2010 OPEN FORUM Abstracts


Clarence Finch, Hollie Lampton, Christine Carbaugh, Kristen J. Price; Respiratory Care, MD Anderson Cancer Center, Houston, TX

Introduction: Measuring employee productivity is one method of justifying staffing levels in respiratory care departments. But how do these levels of productivity relate to the revenue generated by each respiratory therapist? This study explores that question. We hypothesize that a correlation exists between an employeeÂ’s monthly productivity and the billing units he/she generates. Methods: For this study, we collected data on a population of 38 respiratory therapists in an 8 month period. A simple regression analysis was performed to determine if employee average monthly productivity, as measured by the ratio of total treatment time to total time worked (minutes), could be used to predict average monthly billing units (dollars). The employees were then divided into one of three groups based on primary work location: Floor (inpatient units), ICU (intensive care unit), or Both (a combination of both areas). A simple regression analysis was performed for each group using the same variables as the previous model. The division and analysis process was repeated with the groups Day Shift (employees working 7:00am to 7:00pm) and Night Shift (employees working 7:00pm to 7:00am). Finally, a multiple regression test was performed on the 15 ICU respiratory therapists. The independent variables were productivity and average monthly ventilator hours; the dependent variable remained billing units. Results: The overall regression test of the correlation between productivity and billing units showed no statistical significance (p > .010). When the employees were divided by work area, the group working on the floor exhibited statistical correlation with billing units (p < 0.001), while the groups working in the ICU (p > 0.500) and both areas (p > 0.500) did not. Day shift employee productivity showed statistical correlation with billing units (p < 0.001), but night shift productivity showed no correlation (p > 0.500). Further analysis of the ICU respiratory therapists showed no correlation (p > .050) between productivity, ventilator hours, and billing units. Conclusion: In this analysis, we found that employee productivity can be used to predict potential billing units generated by respiratory therapists who treat patients on inpatient floors or who work on the day shift, but not for respiratory therapists working in the ICU or on the night shift. Further research is needed to find prediction factors for ICU and night shift employees. Sponsored Research - None