The key to predicting laboratory workload - University of South Alabama Medical Center case study - 1984 MLO Article Awards Contest prize winner

Medical Laboratory Observer, Nov, 1984 by Shannon S. Harper

To calculate a work index, each patient category is given a weighted factor. The factor for type 1 is 0.5; type 2, 1.0; type 3, 2.5; and type 4, 5.0. The work index is a simple total of all patients' weighted factors. It isn't the number of FTEs that will be needed in a nursing unit, but it leads to a staffing estimate. Acuity equals the work index divided by census or patient days.

Each nursing unit does these calculations. A total work index and average acuity for the hospital are computed monthly. I decided to perform correlation and regression studies using the monthly nursing work index and acuity levels as the independent variables. Nineteen months of data were available for the study, from September 1982 to April 1984 (data for June 1983 were unobtainable).

The results were exciting. The monthly work indexes correlated 0.796 with laboratory billings. Acuity levels correlated 0.734. Again using the Statpak program on the hospital computer, I applied stepwise regression with the index and acuity in combination. The adjusted multiple regression coefficient was 0.805. Wonderful! This meant that more than 64 per cent (0.805 squared) of the variance from perfect correlation could be explained.

Since the nursing work index and acuity variables correlate well with the number of billed procedures, they are much better predictors of laboratory workload than is the patient census. Census is bound to affect the laboratory to some extent, of course.

Figure II shows the regression model used by the computer to compare the work index and acuity level with the number of billed lab procedures. From this model, we get the numerical constants in the following formula for predicting our laboratory workload: Y = 944 37(X.sub.1.) 7437(X.sub.2.)

Y is the total number of laboratory procedures. The constants correlate work index and acuity with known laboratory billings. X.sub.1 is the work index and X.sub.2 is the acuity level, supplied to us by the nursing service. As you can see in Figure III, the equation estimates laboratory volumes for May, June, and July 1984 that are very close to actual billed procedures.

I believe this approach could easily be adapted to laboratories in other institutions as well as to other departments in a hospital. Our hospital's administration, looking at the data in Figure III, no understands why the lab has remained busy despite a decline in patient census. As a result, I have been asked to apply the work index and acuity system to the pharmacy and respiratory therapy departments. Both departments have experienced a revenue decrease this past year without a corresponding decrease in workload.

Work index and acuity data, along with such other yardsticks as the CAP workload recording method, are helping us to monitor the impact of health care changes and to manage our workload. Sometimes you have to develop your own tools.