DoE to Improve Clinical Processes - 1993

8/6/2019 DoE to Improve Clinical Processes - 1993

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USING EXPERIMENTAL DESIGNS TO IMPROVE CLINICAL PROCESSESColletta H. (K.K.) MooreQualPro, Knoxville, TN

ABSTRACTMost hospitals now use simple quality tools suchas flowcharting, brainstorming, fishbone charts,etc. in their process improvement efforts. Whilethese tools are effective, they are limited in theiruse-potential. This session will use a case studyto demonstrate how one hospital used experimental design techniques to improve quality.

INTRODUCTIONMost health care organizations recognize the needfor continuous quality improvement (CQI) and,therefore, are using many of the basic CQI techniques such as flowcharting, brainstorming,fishbone charts, etc. While these tools are effective, they are limited in their use-potential. Although initial success can be obtained using thesetechniques, often the process is still not capableofmeeting customers' needs. As a result, teammembers are left frustrated and feeling as if CQIimplementation is a futile effort. This paper willillustrate how design of experiments (DOE) candramatically improve process capability onceobvious changes have already been implemented,and the improved process is predictable.

Quest for Quality and Productivity in Health Services 1993Conference Proceedings. Institute of Industrial Engineers.1993 QualPro. Printed with pennission from QualPro.

THE STRATEGYIn a typical CQI team setting, team membersmight hold a brainstorming session to identifypossible solutions to a problem. Afterward, aconsensus is often reached on which one possiblesolution, also called a!actor, to test. This type ofexperimentation, known as one-factor-at-a-timeexperimentation (OFAT), is very common inindustry. Unfortunately, OFAT is problematic:(1) it's inefficient and (2) it often provides invalidresults. In contrast, DOE tests factors simultaneously as opposed to sequentially. In addition,DOE provides information on which combinations of factors are significant. Statisticians callthese combinations interactions. Interactionsoften hold the key to true breakthroughs inprocess improvement [1].

CASE STUDY; RADIOLOGYTURNAROUND TIME

A hospital in the Southeastern U.S. used DOE inits CQI effort to significantly reduce turnaroundtime for radiology reports. After nine months, theturnaround time decreased from approximatelytwelve hours to four hours. A team used thefollowing procedure for improving the process:

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Determine key measure(s) and establish themeasurement system Achieve stability Experiment with the process

Determine Key Measure(s) and Establish theMeasurement SystemA key measure is a quantifiable outcome thatprovides information on howwell the process isbehaving from the external customers' viewpoint.The key measure for radiology reports wastimeliness, which was operationally defined to bethe time from patient arrival until the time thetranscription was sent.A measurement system was developed to trackthe time throughout the process. Each day, tenfolders (which had the data collection tool at-tached) were randomly selected, and the keymeasure was recorded. The data were analyzedthrough the use ofX, R charts. As expected, theprocess was unstable, or not predictable, asshown in Figure 1.

Achieye StabilitySince stability is an important prerequisite toDOE, eliminating special cause variation, orvariation which is not inherent in the system, is acritical step in process improvement. Afterinvestigation, the cause of this variation pointedto reports which had been requested on thenursing units before the film had been interpreted.The return of the folders to the Radiology Depart-ment was untimely; therefore, a process measureof film on floor time was analyzed to improve thekey measure, total turnaround time.The team identified potential solutions whichwould decrease film on floor time. After learningthat the nursing units were not completely awarethat the film had not been interpreted, one mem-ber suggested the presence of stickers on the frontof the folder for easy identification. A stickerwould indicate the need to return the folder asquickly as possible to the Radiology Departmentso the process could be completed. In addition,the team learned that each nursing unit did nothave a standard location for radiology folders.

LCL =1.65

UCL=22.97CL =12.31

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2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32Date

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Figure 1. Turnaround Time for Radiology Reports; Initial X Chart (Simulated Data)

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Once the factors in an experiment are determined,the settings, also known as levels, of each factorneed to be defined. The "low level" is typicallythe current condition, whereas the "high level" isthe proposed change in current condition. Conventional codes for the low level and high levelare - and +, respectively. The factors and levelsfor the design are found in Table 1.

Some units even used the regular, internal mail!courier process which also contributed to thedelay. Therefore, one member suggested theprovision of in-out boxes on each unit. Instead ofreaching consensus on which one, or perhapsboth, of these ideas should be implemented, theteam used a more valid, scientific approach in itsdecision making: DOE. Ironically, however, thisfirst DOE was used to achieve stability. MostDOEs are used after stability is achieved.

Table 2. 22 full factorial.

B AB Y R+ 12.48 14.007.44 5.72

+ 11.89 9.19+ + 7.89 7.09

Run A12 +34 +

The results are also provided in Table 2.Yrepresents the average film on floor time in hours foreach treatment combination, or week. R represents the range of film on floor time in hours foreach treatment combination. The DOE concludedthat stickers significantly reduced film on floortime by 4.52 hours. In-out boxes, as well as thecombination of stickers and in-out boxes, provedto be insignificant. This information preventedthe wasted expense of in-out boxes throughoutthe hospital.Levelactor

Table 1. Factors and levels for initial DOE.A 22 full factorial, a type of experimental designshown in Table 2 , was used to assess the effectof stickers (A) and in-out boxes (B) on film onfloor time [2]. Once the design is selected, thesymbols (-,+) can then be decoded. For example,Run 1 specifies A- and B- . Therefore, for oneweek, stickers will not be used, nor in-out boxeson the units. Run 2 specifies A+ and B- . Therefore, for a different week, stickers will be used,but in-out boxes on the units will not be used.The other runs are decoded similarly. Each week,film on floor times are recorded.

A: Stickers

B: In-out boxes

-Not used+Used-Not used+ Used

After this initial DOE, the stickers eliminatedspecial causes in the key measure. Surprisingly,however, a pattern became obvious: weekendswere different than weekdays. By analyzing themseparately, i t became clear that the stickers notonly eliminated special causes, but it also shiftedcommon cause variation in weekday turnaroundtime. The average turnaround time was reducedby 53%. Ordinarily, many CQI efforts stop atinitial success. However, team members still feltmore gains could be realized through otherpossible process changes. Since the process wasstable, DOE was used again to improve processcapability.Experiment with the ProcessPractical, feasible, cost-efficient factors wereidentified during a brainstorming session. Thesefactors and their levels are found in Table 3 [3].For this experiment, a Plackett-Burman [4]screening design was selected to provide an

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Should use each week's daily averages asreplicates within treatment to estimate exptl("random") error. Also, depending on howmany cases within each day, may use box-and-whisker plots to further examinevariation and check for outliers.


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efficient way to reduce a large number of factors A 16-run Plackett-Burman screening design isto a smaller set of important factors for subse- given in Table 4. This design allowed estimationquent experimentation [5]. of each main effect as well as each two-factorinteraction. Similar to the smaller 22 full factorialpreviously mentioned, the design symbols are

A. Short-Term Printer decoded. For example, Run 1 specifies A+, B-,(-) Orders were not reprinted to short-term C-, D-, and E+. Therefore, for a four-day timefile area. Folders were searched for after period, the short-term printer was used, thethe current procedure was performed. schedule board was not utilized, separate areas(+) A short-term printer was simulated which were utilized for ftlm sorting and short-termprovided a process for obtaining the filing, a runner was not used, and the QC functionradiology folder before the current proce- was discontinued. As before, the other treatmentdure was completed. combinations are decoded similarly. For eachtreatment combination, the average turnaroundB. Schedule Board time was recorded for each of the four days.(-) Schedule board was not utilized.

(+) A schedule board was used to provide anorganized method for tracking patients, Run A B C D Estaff, workload, etc.1 + +C. Sorting/Combo 2 + +(-) Separate areas were utilized for film 3 + + + +sorting and short-term filing. 4 + + + +(+) Combined film sorting and short-term file 5 + + + +areas. 6 + + + +7 + +D. Runner 8 + +(-) File room was staffed as usual. 9 + + + +(+) An additional person was employed on a 10 + +temporary basis to transport films to and 11 + +from various areas. 12 + +13 + +E. Quality Control (QC) 14 + +(-) All routine films were routed through QC 15 + +where a technologist rechecked all films 16for quality.(+) QC was discontinued. Technologists Table4. 16-run Plackett-Burman design.

assumed full responsibility and account-ability for film quality.Table 3. Factors and levels for screening design.

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This is not a Plackett-Burmbut rather a "jumbled" 2**(5fractional factorial whosedefining contrast is E = -(ABCD). That is why 2fi's cbe estimated.

See note onprevious page.


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A Pareto chart of main effects and interactioneffects is shown in Figure 2. Without going intodetail of the calculations, theDOE showed thatthe schedule board/runner (BD) interaction wasthe only significant effect on total turnaroundtime.Figure 3 shows a quasi-interaction plot whichhelps illustrate the BD interaction. Although thistechnique provides a crude estimate of the AEinteraction, it works well in practice. As shown,the combination of the schedule board with norunner significantly reduced turnaround time.This new knowledge prevented an unnecessaryadded position in the department. As a result ofthe implemented changes, average turnaroundtime decreased to approximately four hours.

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B: Schedule Board +

Figure 3. Quasi-interaction plot of BDinteraction.

4.034

"Control Limits" =2.42

B CD DE E AC BE AD AB D AE CE A BCFactor

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

BD C

Figure 2. Pareto chart ofmain effects and interaction effects.134


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DoE to Improve Clinical Processes - 1993