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Integrated software: a quick way to audit turnaround time or paid hours.

Integrated software: A quick way to audit turnaround time or paid hours Artists and scientists alike appreciate how a visual display of information can enhance understanding. One clinical laboratory example is in the area of quality control. The purpose of control charts, as originally described by Levey and Jennings, is to enable us "to determine at a glance" whether analytical errors are beyond statistically defined limits of variation.

Today, graphs are common tools of our profession. They are used not only to evaluate analytical performance by controls but also to monitor such function checks as reagent absorbances and refrigerator temperatures, and to present lab results to clinicians in a more meaningful way.

A number of multifunctional or integrated software packages for microcomputers combine the use of data bases, spreadsheets, graphic capabilities, and word processors. Applying these integrated programs to data gleaned from management reports, audits, mainframe information systems, and other sources can produce much more useful information than one would obtain by merely collecting and inspecting the data.

We use Valdocs + software (Rising Star, Torrance, Calif.), which is only available with the Epson QX-10 micromcomputer. But such integrated software as Symphony (Lotus, Cambridge, Mass.) and Framework (Ashton-Tate, Culver City, Calif.) will work on a variety of microcomputers. We'll illustrate what they can do by discussing our separate audits of Stat turnaround time and paid hours.

In our lab, Stat turnaround time starts when the test request is received by telephone. Also available for audit are the collection time, the time the specimen is received in the technical section of the lab, and the time the results are telephoned to the requesting physician or nursing station.

A randomly selected sample of Stat results is regularly audited, and the times are recorded for further evaluation. This information is conveniently maintained in a spreadsheet. It is not only arranged there in neat tabular form but can also be further manipulated.

Figure I shows representative data from our Stat turnaround time audit arranged by increments of time elapsed between each step from test request to result reporting. The spreadsheet calculates the aggregate elapsed time (i.e., turnaround time) as well as the average time for each increment and for the entire sample set of data.

In addition, the data can be readily moved around within the spreadsheet for evaluation of specific subsets, such as the average turnaround time by shift, or for a period like 6 a.m. to 10 a.m., or by day of the week or type of test.

The chart in Figure II was put together simply by instructing the graphics program to pull the appropriate data from the spreadsheet (the information can also be automatically incorporated into reports via the word processing application of the software). Our goal is Stat turnaround time of less than 60 minutes, and the graph clearly shows which of the audited Stats go over that mark.

As a system monitor, the Stat turnaround time audit is analogous to quality control in its two dimensions of usefulness. First, we can decide whether or not the absolute value of the data set requires corrective action: Is the average turnaround time for this period within acceptable limits? Second, we can look for trends by comparing the information to performance in previous periods; another of our graphs is a bar chart of monthly elapsed time averages.

Graphic display of turnaround time information has effectively communicated our performance and our expectations to employees. Turnaround time has improved as a result.

Another illustration of the uses of integrated software in laboratory management is paid hours. Most institutions have a system for monitoring paid hours and/or the number of full-time equivalents per pay period, typial as part of a departmental responsibility or financial report. I tracked such information for a number of years by manually transcribing the total number of paid FTEs, sick/vacation/holiday time, and overtime hours into a log.

In recent years, as our hospital information system improved, so did the quantity, frequency, and timeliness of payroll data. In an attempt to keep up with the bi-weekly reports and enhance our ability to use them, I began loading the data into a spreadsheet.

On a spreadsheet the information can be readily manipulated to provide updated totals and averages; to focus on specific time periods; to evaluate patterns in sick time, vacation and holiday coverage, and overtime; and even to look at trends by job class.

When the spreadsheet data are moved to the graphics software, FTEs can be portrayed by section or, as in Figure III, for the laboratory as a whole. The graph in Figure III also breaks down FTEs by type of paid time. You can quickly discern what proportion of paid time is accounted for by sick, vacation, and holiday hours, and you can evaluate the breakdown of current hours with that of previous periods.

Two caveats: First, any data base compiled by a manager must be accurate and clearly referenced as to its source in order to be respected and accepted by administration. We might request more FTEs, for example, on the basis of our paid-hour analyses. But administration would want to know where the information came from in the first place (the hospital information system's payroll data), and it would want to be sure the lab correctly transcribed the data.

These microcomputer applications are tools, not the final product. We must be careful not to become so involved in assembling and displaying information that we forget to look at it and use it appropriately.
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Title Annotation:Computer Dialog
Author:Lollich, Michael C.
Publication:Medical Laboratory Observer
Date:Jun 1, 1986
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