Management applications of workload recording; analyzing the sources of workload can improve laboratory activity forecasts and staffing plans.
Laboratory managers often base staffing and scheduling decisions on "experience.' The College of American Pathologists' workload recording method gives managers a powerful tool for improving these decisions and optimizing efficiency.
Optimal laboratory staffing may be defined as the smallest number of full-time equivalents required to perform all necessary workloaded and non-workloaded tasks while maintaining quality, acceptable turnaround time, and staff morale. An FTE reflects the hours for which an employee is paid, not just the time at work. In most institutions, this amounts to 2,080 hours annually: 8 hours per day 5 days per week 52 weeks. Employees are generally paid for vacation time, holidays, sick days, and other times when they are away from the lab.1
Although there will be some variation due to differences in employment contracts and a laboratory's turnover rate, it takes about 1.2 FTEs on the average to staff a single position on one shift five days a week for 52 weeks. This rises to about 1.6 FTEs for positions requiring seven-day coverage. Figure I shows how comparable figures can be derived for your laboratory, given your average hours per FTE.
The first task in using the CAP workload recording method to optimize staffing is to determine your workload. Workload as defined by the WLR method provides a solid basis for determining personnel requirements. To calculate total workload, add up all raw counts for timed procedures multiplied by their unit values. Accuracy is vital, for your subsequent steps depend upon these data.
Laboratorians perform many tasks that are non-workloaded (have no assigned unit value). Such tasks can be taken into account by comparing your productivity with that of similiar laboratories. Paid productivity is the total workload, in workload units, divided by the number of paid hours. Worked productivity is this same workload divided by the number of worked hours. By contrast, workloaded productivity (previously termed "specified' productivity) considers only those hours available to perform the workload after time spent on non-workloaded activities has been subtracted.
By comparing your paid and/or worked productivity to that of similar laboratories, it is possible to select a target productivity that is most appropriate for your setting. This will not necessarily be the average for all labs nor even for your type of lab as defined by the 10 categories currently separated out in the CAP Computer Assisted Program. There are often good reasons why a laboratory may have a productivity higher or lower than average.
Select your target productivity with care and an understanding of the factors that make your laboratory unique. For example, if your laboratory maintains its own staff for billing and collections, or for some other non-workloaded activities, this will decrease your productivity.
To take another example, consider the reference laboratory that handles work collected and processed in physicians' offices and does few Stat tests. The unit value in workload recording includes time for initial processing, which in this case is being done by personnel on someone else's payroll. The unit value is also assigned by averaging time studies, which include different-size batches of routine and Stat work. This reference laboratory should have a higher-than-average target productivity.
Because you choose your target paid productivity through comparison with laboratories in similar situations, such as at teaching hospitals, you in effect make allowance for the time needed to perform non-workloaded activities. Where you can identify differences from your reference group, you make further allowances. (A forthcoming article in this series will elaborate on non-workloaded activities.)
Figure II demonstrates how the paid productivity equation is rearranged to calculate the number of FTEs needed to achieve target productivity. If your laboratory produced 2,688,343 WLU in 1986 with 39 FTEs, its productivity was 33.1 WLU per hour. Suppose you now select the median hourly productivity of 38 WLU/ hour for community hospitals as your target. Multiply the target productivity by 2,080 hours and divide the result into the 1986 workload. This will give you the number of FTEs required for the target productivity: 34 or 5 fewer than you had in 1986.
Of course, workload is no longer a given for most laboratories. The major changes may once have occurred as variations within the year--by day of the week and from month to month.2 Most laboratories now see significant variations from one year to the next. Changes in hospital reimbursement mechanisms have led to significant decreases in the average length of stay and, at many hospitals, a declining census as well. More elaborate physicians' office labs can be expected to cut into some hospital laboratories' outpatient work, and competition from HMOs, PPOs, and ambulatory care centers is further dividing up the marketplace.
While the future is not cast in concrete, certain data are available to help us forecast trends. For example, your workload probably changed from 1985 to 1986. Suppose it dropped by 6 per cent. Will that decrease continue in 1987" If so, how would that affect your productivity? Let's find out:
If your laboratory produced 2,688,343 WLU in 1986, 94 per cent of that as a workload estimate for 1987 would be 2,527,042 WLU. If the staff holds at 39 FTEs, productivity would drop to 31.2 WLU per hour. To achieve the target productivity of 38 WLU per hour that you established earlier, you would have to reduce your staff to 32 FTEs.
Naturally, you hesitate to budget 7 fewer FTEs just because last year's slide in workload may be repeated. Indeed, there are better ways to project future workload than merely extending the most recent trend line.
Before we go further, it should be emphasized that workload reports must be accurate and complete. If there happen to be 300,000 unrecorded WLUs, you will compound your problems by expecting the staff to operate at what in reality is a paid productivity of 42.5 WLU per hour. However, assuming that your current workload estimate is accurate and the target productivity appropriate, you need to develop the best-possible projections for the coming fiscal year.
It is important to know the sources of your workload and as much as possible about the forces affecting them. If 60 per cent of the workload comes from Medicare-sponsored patients, how is this segment of your population most likely to change? For one thing, hospital length of stay has decreased nationally since DRGs were introduced. If your hospital's average length of stay dropped from 8.8 days in 1985 to 8.5 days in 1986, this no doubt played a part in the laboratory's 6 per cent workload decline, though probably not more than 3.4 per cent: (8.8 - 8.5) 8.8.
Nevertheless, discussions with hospital administrators may indicate that they expect a further decrease to the neighborhood of 8.1 days. This could cause another drop in workload, by as much as 4.7 per cent: (8.5 - 8.1) 8.5.
At the same time, you might learn that the hospital's average occupancy fell 7.9 per cent, from 342 beds per day in 1985 to 315 in 1986. This comes much closer to explaining the 6 per cent drop in workload. But again, there is not an exact match. Still other factors are at work.
While workload is partially dependent on length of stay, more tests are typically ordered in the first few days following admission than at any other time. For that reason, the number of admissions usually influences laboratory workload more than either length of stay or hospital census alone. You can obtain projections for next year's admissions, discharges, and average length of stay from your hospital administration.
Because numerous forces are at work--often in opposite directions --your predictions may become quite complicated. The national laboratory experience appears to be mixed. Some hospitals report increased testing on "sicker' patients; others report reduced testing, perhaps in an attempt to become more cost-conscious.3 Don't be discouraged. The goal is not a perfect prognostication, but rather an understanding of your environment that will allow you to make approximations, which can be fine-tuned later.
You need to work out projections based on a variety of possible futures, combining the various sources of workload and the changes that may occur. If you offer outpatient services that depend on clinic visits, you can determine the average number of WLUs per visit. Try multiplying that figure by the number of clinic visits projected for next year. If the laboratory is marketing a new toxicology screening program to business firms in your area, project the expected workload from that endeavor as well.
Don't hesitate to try several degrees of change for each factor--a "worst case,' "best case,' and "most likely case.' Combine each degree of change with the appropriate source of workload and add the results to predict your total projected workload. A microcomputer spreadsheet makes it easy to develop and alter predictions (Figure III).
Once you have predicted your workload, use the figure to calculate productivity with the current number of FTEs. Then use your target productivity to determine the number of FTEs you should have.
Now that you have a handle on the projected workload and know how many FTEs are available, you are ready to tackle scheduling. It's obviously not enough to know that you need 14.9 FTEs in chemistry to generate 1,178,439 WLU with an hourly productivity of 38 WLU. Workload is not evenly distributed over 24 hours a day, seven days a week. Staffing must be sufficient to handle different levels of workload at different periods within a medically acceptable time frame.
Ideally, you would like to know what the workload was last year for each shift on each day of the week during each month--then you could adjust that workload based on projections for next year. Although laboratory computer systems have become increasingly sophisticated in tracking workload, most of us do not have data accurate to that level. Nevertheless, we can approach the ideal by using approximations.
To illustrate how, we will examine some considerations involved in scheduling three chemistry shifts on Saturday. Even though most laboratory computers still have some deficiencies in dealing with nonbilled procedures, it should be relatively easy to determine the number of billed procedures requested for each of the Saturday shifts. Extrapolating with reasonable assumptions can then yield an estimate of the total workload performed that day.
Suppose the computer's record of chemistry workload for the month averages 73 per cent of the total number of WLUs tallied (excluding, for example, repeats and standards). Divide the computer's number of WLUs generated in chemistry on each of the three Saturday shifts by .73, and you will have approximations of the actual chemistry workload that must be accomplished during the day, evening, and night shifts, Laboratories lacking an information system can ferret out the same data manually by counting request slips.
The next assumptions concern the Saturday staff's productivity. It should be higher than the monthly average since there will probably be fewer non-workloaded activities, such as in-services, training, and meetings. Allow a minimum 8 per cent for personal, fatigue, and delay time. This calculates to about five minutes per hour, making 55 WLU per hour the maximum productivity one can expect. If employees take two 15-minute breaks, available work time in each shift is 7.5 hours.
Thus each FTE would be able to accomplish a maximum of 412 WLU per shift (55 WLU 7.5 hours). If there are 3,500 WLU to be done in chemistry, 8.5 FTEs will be required. If the bulk of the work--say 2,000 WLU--is concentrated on the day shift, then 4.9 FTEs are needed. The evening shift requires 2.4 FTEs for its 1,000 WLU, and the midnight shift, with 500 WLU, requires 1.2 FTEs.
These calculations are all very well and good, but laboratorians don't come in 0.4 or 0.2 size. One answer is to use part-time employees; another, for the 1.2 FTEs needed on the midnight shift, may be to get cross-coverage from the technologist in hematology, which requires only 0.6 FTE to handle 250 WLU late at night.
In addition, although last Saturday was relatively quiet, next Saturday may bring multiple injuries, bleeding ulcers, and other traumas for a much heavier workload. Variations on the order of 30 per cent are not uncommon, and only some of them--such as the slowdown in elective surgery around Christmas--can easily be forecast. (Such seasonal variations do have a predictive value and should be built into the schedule whenever possible. Vacations may be encouraged during traditionally slow periods.)
Obviously, some slack must still be built into the schedule. However, it's best not to assume the worst by adding 30 per cent to the average staffing you have calculated. Generally speaking, larger-volume labs experience smaller workload variations. If you can determine what variations really do occur--and plot a histogram-- you can get a better idea of the scope of the problem.
There are other, less complicated ways to deal with workload variations. If it is only an occasional problem, overtime may be the best means of coping with an unusually high workload. In other intances, some routine work can be postponed until a slack period on a later shift. For example, screening trichromes for ova and parasites might be saved to fill in the slack time of extra FTEs who are scheduled to be on hand for Stat tests. The workload figures for ova and parasites will give you an insight into the potential fit.
Suppose you learn that the 500 chemistry WLU on the midnight shift may include 400 Stat WLU, all coming into the lab in a single hour. At an hourly productivity of 55 WLU per FTE, you would need 7.2 FTEs if the Stats came in all at once, or 3.6 FTEs if they were evenly spaced throughout the hour. How does one ever resolve this kind of problem? (Bear in mind that a midnight staff of 7 FTEs would have an effective paid productivity of less than 9 WLU per hour for the entire shift!)
Determine the shift's workload pattern. Perhaps the shift change is inappropriately timed: The ICU morning draw starts at 6 a.m., yet day staff employees don't arrive in the laboratory until 7 or 8 a.m. Bring in more of them to run the Stat ICU specimens, and the job will get done without seriously overstaffing or overtaxing the midnight crew.
These same principles apply to scheduling any and all sections or shifts. Once you know the workload to be accomplished, you can determine the number of FTEs required. As noted earlier, it takes 1.6 FTEs of paid hours to cover a shift seven days a week. Non-workloaded activities must be scheduled into appropriate times, so one cannot make the same maximal assumptions concerning productivity for each shift that we have just allowed for a Saturday.
I hope these ideas will encourage you to think of other ways to manage staffing and scheduling more effectively. The primary concepts are that 1) when CAP workload is used with appropriate target productivity, it provides a solid basis for budgeting and staffing, and not only for the laboratory as a whole, and 2) if you can determine the workload, you can plan staffing coverage for any section over any period of time.
1. Conn, R., and Koch, J. Management applications of workload recording--Part I. MLO 19(4): 39-42, April 1987.
2. Barletta, J.M. Using projectional analysis to reach your staffing goals. MLO 16(3): 81-90, March 1984.
3. Test ordering trends mixed. Clin. Chem. News 13: 1, January 1987.
Photo: Figure I How many FTEs are needed to cover one position?
Photo: Figure II Past productivity and FTEs needed for target productivity
Photo: Figure III A spreadsheet for different workload forecast assumptions
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|Title Annotation:||Part 2|
|Author:||Grove, William E.|
|Publication:||Medical Laboratory Observer|
|Date:||May 1, 1987|
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