CME/SAM. Value Stream Mapping of the Pap Test Processing Procedure. A Lean Approach to Improve Quality and Efficiency

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CME/SAM

Value Stream Mapping of the Pap Test Processing

Procedure

A Lean Approach to Improve Quality and Efficiency

Claire W. Michael, MD,

1

_{Kalyani Naik, SCT (ASCP), MS,}

2

_{and Michael McVicker}

3

Key Words: Pap test; Lean management; Toyota production system; Laboratory management; Quality assurance DOI: 10.1309/AJCPIWKS7DJXEEQQ

A b s t r a c t

We developed a value stream map (VSM) of the Papanicolaou test procedure to identify opportunities to reduce waste and errors, created a new VSM, and implemented a new process emphasizing Lean tools. Preimplementation data revealed the following: (1) processing time (PT) for 1,140 samples averaged 54 hours; (2) 27 accessioning errors were detected on review of 357 random requisitions (7.6%); (3) 5 of the 20,060 tests had labeling errors that had gone undetected in the processing stage. Four were detected later during specimen processing but 1 reached the reporting stage. Postimplementation data were as follows: (1) PT for 1,355 samples averaged 31 hours; (2) 17 accessioning errors were detected on review of 385 random requisitions (4.4%); and (3) no labeling errors were undetected. Our results demonstrate that implementation of Lean methods, such as first-in first-out processes and minimizing batch size by staff actively participating in the improvement process, allows for higher quality, greater patient safety, and improved efficiency.

The value of a rapid Papanicolaou (Pap) test turnaround time (TAT) has been an issue of debate for some years. It has been argued that maintaining a steady-state TAT for routine Pap tests is more important than a rapid TAT, given the long natural history of progression of cervical disease that the Pap test is designed to detect and the potential for a rapid TAT to actually result in decreased quality testing.1,2_However, from the perspective of the patient who may be anxiously awaiting her test results, whether normal or abnormal, or the clinician seeking to provide efficient service to the patient by reporting all test results at the same time within the shortest timeframe possible, a rapid TAT is as significant as the qual-ity of the results.

These customer expectations of high-quality results and high-quality service, coupled with the enormous economic pressures facing the laboratory, makes maintaining cost-effectiveness, while at the same time continuously improv-ing service and patient safety, critical to its success. Process improvement methods, such as the Lean and Six Sigma approaches, which have been successful in the industrial set-ting and have recently been introduced into the health care arena, present an opportunity to achieve efficiency while improving the quality of operational performance of the labo-ratory. Although a growing number of pathology laboratories have integrated these methods into their continuous improve-ment programs,3,4_{a small number of previously published} articles have focused on improving the TAT of the Pap test.5,6 We used Lean methods to examine our ThinPrep (Hologic, Marlborough, MA) Pap test processing procedure with the goal of improving processing time (PT) and reducing acces-sioning and/or labeling errors.

Upon completion of this activity you will be able to:

• outline the potential application of value stream mapping in the laboratory and how it contributes to process improvement. • identify the sources of waste in the laboratory and learn how to

minimize them.

• perform a value stream map of a laboratory process.

The ASCP is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The ASCP designates this journal-based CME activity for a maximum of 1

AMA PRA Category 1 Credit ™ per article. Physicians should claim only the

credit commensurate with the extent of their participation in the activity. This activity qualifies as an American Board of Pathology Maintenance of Certification Part II Self-Assessment Module.

The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose.

Questions appear on p 690. Exam is located at www.ascp.org/ajcpcme.

by guest on May 18, 2016

http://ajcp.oxfordjournals.org/

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Materials and Methods

As part of an anatomic pathology department-wide initia-tive to implement Lean, all cytology staff and faculty partici-pated in a division-wide “Introduction to Lean” session, dur-ing which basic principles and tools were introduced. Before beginning our Pap test processing procedure value stream project, we presented the project to our staff, focusing on its purpose and scope, and solicited volunteers to participate in all its aspects, from creating the current value stream map (VSM) to collecting and analyzing data, identifying improve-ment opportunities, selecting opportunities that should be tar-geted for the future state VSM, creating and implementing the future state, and reviewing results to determine outcomes of the new map. As the owners of this process, it was critical to obtain not only their feedback to achieve a successful outcome but also their active participation in all aspects of the project, particularly in designing the future state.

A team composed of 2 members of the cytopreparatory staff, 1 cytotechnologist, laboratory supervisor, medical direc-tor, and a Lean coach was charged with evaluating our Thin-Prep Pap test processing procedure. The scope of the project included receipt of the specimen in the laboratory as the start point and production of the labeled slide ready for cytotech-nologist evaluation as the end point. The entire process was videotaped by the team coach and subsequently reviewed in detail by the team. A video VSM was created, first of the specimen flow and then of the staff as they processed the specimen (traditionally 2 staff members are involved in the Pap process while a third is involved in nongynecologic

specimen processing). Each step taken by the specimen and the staff, along with the length of time for each step in sec-onds, was entered into an Excel (Microsoft, Redmond, WA)– based VSM tool and designated as processing vs waiting time. The VSM was then reviewed in detail by the team to identify waste (ie, non–value-added activities) that could be eliminat-ed and identify opportunities to minimize potential for errors. A new process was then designed based on the follow-ing identified opportunities: (1) batchfollow-ing durfollow-ing openfollow-ing and racking of vials into ThinPrep 3000 (T3000) processor racks

❚Image 1❚; (2) unnecessary highlighting of information

per-ceived to be critical on requisitions ❚Image 2❚; (3) batching of

accessioned and bar code–labeled samples for T3000 process-ing ❚Image 3❚; (4) specimens waiting in queues at multiple

points for subsequent steps in the process; (5) handling of the same sample at multiple points (at opening, racking, and labeling with the bar code label); (6) writing the accession number on the requisition during accessioning, then affixing a bar code label with the same accession number to the requisi-tion during a subsequent labeling step; (7) matching patient identity at multiple points (at opening and then again match-ing the bar code label to the vial and requisition); (8) loadmatch-ing variable batch sizes (ranging from 40 to 80) into the T3000 instrument; and (9) interruptions to staff during accessioning to load/unload the T3000, autostainer, and coverslipper.

Changes introduced to the process included the follow-ing: (1) first-in first-out during opening of specimen bags and accessioning, labeling, and racking of the specimens ❚Image 4❚, ❚Image 5❚, and ❚Image 6❚; (2) minimizing the batch size

❚Image 1❚ Specimens in yellow bins are waiting to be opened

and accessioned. Vials in ThinPrep 3000 racks and corresponding requisitions await bar code labeling after accessioning.

❚Image 2❚ Unnecessary highlighting of information perceived to be critical on requisitions is shown.

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in the T3000, autostainer, and coverslipper to 40 Pap test specimens at a time; (3) elimination of redundant steps; and (4) when staffing made it feasible, assigning 1 staff member to perform “in-cycle” work (ie, opening and accessioning, label-ing, and racking of the specimens) and another to perform “out-of-cycle” work (ie, loading/unloading the equipment).

Overall staffing varied equally during the 2 periods based on staff work schedules and leaves. However, in the new process, when staffing levels were sufficient, we made a point of assigning 2 staff members to Pap test processing (with 1

assigned to perform “in-cycle work” and the other to perform “out-of-cycle work”). The third staff member was assigned to nongynecologic specimen processing.

The effect of the changes was evaluated by measuring the following monitors before and after implementation: (1) total PT (determined by following ThinPrep Pap test specimens from specimen receipt to slide labeling); (2) number of acces-sioning errors (defined as discrepancies between the requisi-tion and informarequisi-tion entered into the laboratory informarequisi-tion system) that were encountered during the normal workflow

❚Image 6❚ Single case handling involves affixing the bar code label to the vial and then racking.

❚Image 3❚ Batching of accessioned and printed bar code labels that wait to be matched and affixed to a vial in a separate batched step is shown.

❚Image 4❚ Single case handling involves opening the specimen bag and accessioning 1 case at a time. No other specimens are in the accessioning space until the current specimen is processed.

❚Image 5❚ Single case handling involves affixing the bar code label to the requisition before the next specimen is handled.

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as well as via random audits for a period of 4 weeks; and (3) number of labeling errors (unlabeled vial, inadequately labeled with only 1 identifier, or mismatched vial/requisition) at the clinical site that were missed up front but subsequently identified downstream (determined by reviewing the laborato-ry problem log for the 6 months immediately before and after the pilot project). Z test statistical analysis was conducted to determine the level of significance.

Results

Preimplementation data review revealed the following: (1) PT for 1,140 samples ranged from 1 to 3 days, with an average of 54 hours; (2) 27 accessioning errors were detected on a random review of 357 requisitions (7.6% of requisitions); (3) 5 (17.24%) of 29 total labeling errors (out of approxi-mately 20,060 Pap tests that were processed during the 6

months) had gone undetected during the specimen opening and accessioning stage. Four were detected later during speci-men processing, but 1 reached the reporting stage.

❚Figure 1❚ is a sample of the tool that was generated as

a result of the analysis of the video VSM, with each step of the process detailed in the map. ❚Figure 2❚ illustrates the

then-current state map process flow. During analysis of the tool, the team focused on steps that were categorized as waste, par-ticularly those steps that took long periods (highlighted in the tool). From these raw data, our Lean coach developed visual graphs that demonstrated to the team how much time was spent in non–value-added activities (ie, waste) such as storage (ie, waiting for the next step), transportation, inspection, and certain processing steps

Review of the process flow chart and time spent in each process demonstrated that each specimen spent 98.7% of laboratory time in storage or waiting in several stages desig-nated as raw material before processing, between processing,

❚Figure 1❚ A tool generated as a result of the analysis of the video value stream map. Individual steps are shown along with their designation and time track. Individual steps categorized as waste, which involve long periods, are highlighted.

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at the end of a process, or as a finished good as illustrated in the time line chart. ❚Figure 3❚ illustrates the actual time

spent at each major point in the process (receiving, racking/ finishing, accessioning, processing, and staining/coverslip-ping). ❚Figure 4❚ is a pie chart that shows value-added and

non–value-added time as a percentage of overall PT. Both of these graphs clearly demonstrate that most of the PT in the current state was spent in non–value-added activities, and these should be the potential targets for the process.

❚Figure 5❚ shows the current workflow with the specific

steps that were believed to be wasted activities highlighted in green. Most of the steps that were removed required the same specimen to be handled multiple times and by multiple individuals. Each time a specimen is handled represents an additional opportunity for errors and involves unnecessary repetitious work because the specimen must be picked up, the labeling analyzed to confirm patient identity, and the specimen set aside again once the activity is completed.

In addition, this multiple handling encouraged batching of specimens at multiple points throughout the process—first at receiving when the specimen container labels were matched against the requisition, and then again after accessioning was completed and accession labels were affixed to the contain-ers. The new process allowed one staff member to open, confirm patient identity, accession, label both the requisition and the container, and set the specimen aside as single piece handling during that step of the process. In addition, the team eliminated the step of marking the requisition intended to focus attention on certain items such as human papilloma-virus (HPV) request, missing clinical history, and diagnostic Pap test; the initial purpose was to alert staff and/or faculty downstream of this information. The team removed this step to determine whether this step truly affected errors that may occur downstream.

Review of postimplementation data revealed the fol-lowing: (1) PT for 1,355 Pap test samples ranged from 1

Repeat until batch (all specimens received) is complete

Repeat until batch (80) is complete

Repeat until batch (80) is complete Repeat until batch (80) is complete

Repeat until batch (variable size) is complete 1. Specimens received 2. Unbag specimen vial/ requisition 3. Verify patient ID 4. Write “dummy” # on vial/ requisition 5. Fix “hanging” labels on vial, align cap 6. Set vial in T3 rack 7. Mark up requisition (eg, HPV request, missing clinical history, diagnostic Pap smear) 8. Set requisition aside 16. Place vial into rack/set requisition aside 15. Place one bar code label on vial/one on requisition 14. Match bar code label to vial/requisition 13. Remove vial from rack

12. Place requisitions with corresponding rack 11. Set requisition aside 10. Write accession # on requisition 9. Accession specimen/ bar code label prints 17. Load vial racks and supplies into T3 18. Run T3 19. Unload T3 20. Transfer vials from racks to storage bins 21. Transfer slides from T3 slide rack to stain rack 22. Load stain rack into stainer 23. Run stainer 24. Unload slide rack from stainer 32. Set requisitions with slides 33. Deliver requisitions/ slides to CTs 31. Match slides to requisitions 30. Place slide label on slide 29. Match slide label to slide 28. Transfer slides to slide trays 27. Unload

slide racks coverslipper26. Run

25. Load slide rack into coverslipper

❚Figure 2❚ Preimplementation current state map process flow with specific steps that were considered to be wasted activities are highlighted in green. CT, cytotechnologist; HPV, human papillomavirus; Pap, Papanicolaou; T3, ThinPrep 3000.

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to 2 days, with an average of 31 hours; (2) 17 accessioning errors were detected during a random review of 385 requi-sitions (4.4% of requirequi-sitions); and (3) 0 of 30 total labeling errors (out of approximately 20,000 specimens processed during 6 months post-pilot) went undetected at the front end. ❚Table 1❚ summarizes the pre- and

postimplementa-tion data.

A Z test of the average time from receipt to result revealed a score of –40, indicating that the 13-hour difference in the populations was of high statistical significance (P < .001). The 2.2% difference in error rates revealed a Z score of –2.33 and a P value of .00099, another highly significant result (errors discovered outside the random sample were not included in the statistical analysis).

ST PR AC RK RE ST PR AC RK B E FG I NV RM T VA

Storage: Between process Storage: End of process Storage: Finished good Inspection

Non–value-added Storage: Raw material Transportation Value-added RE 0:39:28 0:00:00 Dept Time 1:01:57 20:50:02 0:32:25 12:33:22 0:00 4:48 9:36 14:24 19:12 0:00 4:48 9:36 14:24

❚Figure 3❚ Time line of product activity shows the actual time spent at each major point in the process. AC, accessioning; PR,

processing; RE, receiving; RK, racking/finishing; ST, staining/coverslipping.

Storage 98.7% Value-added processing 1.2% Inspection 0.0% Transportation 0.1% Non–value-added processing 0.0% Storage Transportation Inspection Non–value-added processing Value-added processing Total time 126,505 120 19 31 1,559 128,234 38:08:25 0:02:00 0:00:19 0:00:31 0:25:59 35:37:14 98.7% 0.1% 0.0% 0.0% 1.2% 100.0% Seconds Hour:Min:Sec % of Total Time

❚Figure 4❚ Time line analysis pie chart of process steps shows value-added time (red) and non–value-added time (green) as percentage of overall process time.

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Discussion

In 1999, the Institute of Medicine published its report To Err Is Human: Building a Safer Health System, citing medi-cal errors as the eighth leading cause of death and exceeding those attributed to motor vehicle incidents, breast cancer, and AIDS. The report indicated that between 44,000 and 98,000 people die annually as a result of preventable medical errors.7 Error was defined as failure of a planned action to be com-pleted as intended or the use of a wrong plan to achieve an aim. The report also described the effect of errors on patients and health care providers as a costly one because it erodes the patient’s trust and diminishes the satisfaction obtained by both patients and providers. One of the causes of errors identified by the report was the decentralized and fragmented nature of the health care delivery system. Frequently, errors were attrib-uted to faulty systems or processes that lead people to make

Repeat until batch (40) is complete

Eliminated steps

Repeat until batch (40) is complete Repeat until batch (40) is complete Repeat until batch (40) is complete 1. Specimens

received patient ID3. Verify

4. Write “dummy” # on vial/ requisition 5. Fix “hanging” labels on vial, align cap 16. Place vial into rack/set requisition aside 15. Place one

bar code label on vial/one on requisition 9. Accession specimen/ bar code label prints 17. Load vial racks and supplies into T3 18. Run T3 19. Unload T3 20. Transfer vials from racks to storage bins 21. Transfer slides from T3 slide rack to stain rack 22. Load stain rack into stainer 23. Run stainer 24. Unload slide rack from stainer 32. Set requisitions with slides 33. Deliver requisitions/ slides to CTs 31. Match slides to requisitions 30. Place slide label on slide 29. Match slide label to slide 28. Transfer slides to slide trays 27. Unload slide racks 26. Run coverslipper 25. Load slide rack into coverslipper 6. Set vial in T3 rack 8. Set requisition aside 14. Match bar code label to vial/requisition 13. Remove

vial from rack 12. Place requisitions with corresponding rack 11. Set requisition aside 2. Unbag specimen vial/ requisition 7. Mark up requisition (eg, HPV request, missing clinical history, diagnostic Pap smear) 10. Write accession # on requisition

❚Figure 5❚ Postimplementation process flow after eliminating the non–value-added steps is shown. CT, cytotechnologist; HPV, human papillomavirus; Pap, Papanicolaou; T3, ThinPrep 3000.

❚Table 1❚

Summary Data of Preimplementation and Postimplementation Monitors

Monitor Preimplementation Postimplementation

No. of specimens 1,140 1,355

Total processing time, d

Average 2 1 Range 1-3 1-2 Accessioning errors No. of requisitions 384 391 No. (%) of errors 29 (7.6) 23 (5.9) Labeling errors

No. of specimens processed 20,060 20,000

Total No. of labeling 29 30

errors received

No. (%) of labeling 5 (17.24)a ₀

errors missed

a_{Four detected during processing, and 1 reached reporting step.}

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A record of the flow steps is developed either by video-taping or meticulously penciling the steps either manually or using specially designed software. The time of each step is measured in seconds. Throughout the process, although the viewer (project coach) is a silent observer and may not inter-fere in the process, he or she could ask questions later, such as why a particular action is performed. A team is formed that should have representation from every level. In our project, the team consisted of 2 members of cytopreparatory staff, 1 cytotechnologist, the laboratory supervisor, medical director, and a Lean coach. Next, the scope of the project should be decided by defining the following factors traditionally abbre-viated as SIPOC: (1) supplier, defined in our project as our central specimen processing department; (2) inputs, or the raw materials in the process, defined as arrival of the sample to the laboratory, including the requisition, billing, and registration information and the sample vial; (3) process, defined as pro-cessing the Pap test samples, including accessioning, prepar-ing slides, stainprepar-ing, and labelprepar-ing; (4) outputs, defined as the point when a slide was ready on the shelf for screening; and (5) customers who receive or benefit from the output, defined in this project as the cytotechnologist.

Once the process is closely observed, the visual rep-resentation—in this project a videotape—is reviewed and every step is recorded in an Excel-based chart measuring the following metrics: PT, which records the time to conduct a single step; waiting time, which records the time an item waits between 2 steps or interruption before 1 step is completed; and lead time, which is the addition of PT and wait time and rep-resents the total time from the customer’s perspective (Figure 1). Each time is designated as either value-added, defined as a step that contributes to the flow of the specimen in the process such as accessioning a sample, or non–value-added, defined as the time that does not contribute to the specimen flow, such as the time the first sample in a batch waits until the last sample is accessioned before processing starts. Non–value-added time can also include steps, such as quality control measures, that are essential from the laboratory perspective yet do not contribute to the flow of the specimen. ❚Table 2❚

lists examples of steps, their descriptions, and how to code them. In addition, data are collected to measure first-time quality or the percentage of steps completed without an error on the first attempt. In our study, we monitored accessioning and labeling errors by means of a random auditing for 4 weeks and also by reviewing the error logs for 6 months before and after implementation of process improvements. Additional metrics can be identified according to the project at hand.

In pathology, the implementation of Lean production methods has been explored in the last few years. Condel et al4_{published their experience in the application of Lean tools} in the anatomic pathology laboratory. They described how they strived to create an environment with zero errors and the error or fail to prevent it. The report suggested that

mis-takes can be eliminated if the health care system is designed at all levels to be safer and makes it difficult for people to make mistakes. In other words: the goal is error prevention rather than correction. Consequently, awareness of public safety, the need to establish better quality assurance measures, and pre-vention of medical errors have been the subject of discussion and debate in the health care system for more than a decade. In addition to the many improved quality assurance measures that have been introduced since then, the health care industry has turned to the Lean management or Toyota production system used successfully for decades by other industries for its well-known error evaluation tools.3-6,8

Lean management generally focuses on improving effi-ciency by eliminating waste and error-proofing the process. In The Toyota Way,9_{Liker lists 8 types of waste: (1)} overproduc-tion, in which an item is produced in a quantity greater than is needed or before it is needed; (2) waiting, in which a worker may spend time waiting for the next step or when the item is not flowing through a value-added operation; (3) unnec-essary transport, in which material is transported long dis-tances or between processes; (4) overprocessing or incorrect processing, in which unessential or inefficient steps may be performed during processing; (5) excess inventory, in which excess supplies are preordered, space utilization is inefficient, or the presence of clutter may hide problems; 6) unnecessary movements, which involve motion of workers that does not add value, such as looking for supplies or stacking shelves; (7) defects, in which the product is flawed and needs correction and therefore additional rework; and (8) unused employee creativity and disuse of their ideas.

VSM is one of the Lean tools that help the examiner see and understand the flow of material and information in a process.10,11_{This tool allows the reviewer to develop a} visu-al representation of the current state of the process, identify non–value-added steps resulting in waste, and consequently identify areas of improvement. VSM tracks the flow of the item and information and follows their path throughout the process step by step. VSM helps the observer identify not only the waste but also its contributing factors and forms the foundation to design a process improvement implementa-tion plan.

Developing a VSM with both an outside coach and the workers observed in the process helps both parties to understand why the process is performed the way it is and consequently helps workers to understand how many of the steps they take add no value. Without this understanding, any improvement tactics will fail when the process stalls because of a lack of buy-in. The best and lasting solutions are found by staff members who become aware of the waste in their activities. Our staff members created the solutions that they enacted, thus making them meaningful and lasting.

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and through trial and testing, however, we determined that the most efficient number was 40 specimens. Thus the first 40 specimens are ready for coverslipping and labeling by the second cytopreparatory staff while the remaining specimens are accessioned by the first staff. Although in this situation, batching cannot be completely eliminated, we implemented single case handling within the smaller batch. This means that rather than opening the entire batch, sorting the vials and requisitions, accessioning the entire batch, and then labeling the batch, we now open 1 specimen bag at a time, review the requisition, accession the specimen, label the requisition and vial, put the vial in the T3000 rack, and then proceed to the second bag and repeat the entire process. Such a minor change in the process flow resulted in a more continuous flow of the specimen, a decrease in non–value-added time, and elimina-tion of the system risk for errors. Another interesting area of improvement that surfaced in our review was the time spent marking the requisition for request of HPV testing, if the last menstrual period was missing or if the specimen is retrieved as annual routine follow-up or for diagnostic purposes. These markings were previously introduced as quality assurance methods to circumvent previously encountered problems, such continuous flow by identifying waste in areas and reorganizing

their laboratory space and consequently their work flow. Zarbo and d’Angelo3_{also published their experience and success in} decreasing the rate of errors in the surgical pathology labora-tory after they introduced a cultural transformation and imple-mented the Toyota production system/Lean management tools. In this report, we share our experience in developing a VSM to further our understanding of our processing method of the Pap test and identify opportunities for improvement. As illustrated in the preimplementation map (Figure 2), several opportunities were identified. A major problem was the pro-cessing of specimens in large batches. Although historically batching was considered more efficient, further scrutiny of the process shows that batching contributes to many of the errors such as misidentification, mislabeling, and specimen mix-ups. Also, batching contributes to non–value-added time when the first accessioned specimen is kept waiting until the last speci-men in the batch is accessioned before it is labeled and stained. Indeed, batching is necessary for certain laboratory processes such as the Pap test. Because the T3000 can accommodate up to 80 vials in 1 run, we traditionally processed 80 specimens per batch, particularly in the first batch. Based on our data

❚Table 2❚

Summary and Examples of Step Descriptions and Codes Definitions of Terms for the

Description Code Operator Analysis Typical examples as seen in the laboratory environment Processing time

Value-added VA The time required to process a Cell block section being cut in histology laboratory product or service that actually Performing actual test

changes the size, shape, form, Slide being stained but only the time that staining is occurring fit, or function for the first time Time the T3000 is processing the specimen but not while

sitting in the processor waiting

Preparing conventional smear but not while sitting in fixative Interpretation of a result but not inspection

Non–value-added NV The time required to process a Paperwork, filing results, or phone calls regarding specimen product or service that does not Specimen being labeled

change the size, shape, form, fit, Specimen coverslipped on slide

or function for the first time and Uncapping or recapping a specimen container is not associated with inspection; Packaging a specimen for send-out

eg, packaging

Inspection time I The time required to determine whether Inspecting specimen for clots, mucus, etc

the product or service is being Inspecting label or requisition for proper information accomplished per specification Reviewing results before verifying them

Transportation time T The distance (expressed in feet ) the Moving specimen from one process to the next product travels as it moves from Moving specimen from counter to centrifuge place to place Carrying processed vials to storage

Raw material storage RM Material awaiting the first process step Specimen sitting in laboratory before accessioning Requisitions waiting for input into LIS

Between-process storage B Any storage time that is not considered Specimens sitting in T3000 waiting for processing RM, E, or FG Processed slides waiting for staining

End-of-process storage E When the product is waiting immediately Packaged samples waiting for courier to transport (send-out) after a defined process step Results waiting for verification steps to occur

Results waiting for input into LIS

Finished goods storage FG When the product or service is complete Completed printed results waiting to be sent to customer and waiting as a finished good Results waiting within interface and not yet delivered for use

Reading instructions

LIS, laboratory information system; T3000, ThinPrep 3000.

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Acknowledgments: The authors would like to acknowledge Susan Clozza, CT(ASCP), Doug Mullen, and Kimberly Meekins from the Department of Cytopathology, University of Michigan Hospital, Ann Arbor, for their contribution to this project.

References

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applying Lean production methods to anatomic pathology.

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6. Dark RL. Using Lean to cut Pap test TAT pays off at Baystate Medical Center. Dark Report. 2009;16:10-15. Available at http://www.darkreport.com/dark/index.htm. Accessed February 27, 2013.

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Is Human: Building a Safer Health System. Washington, DC:

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World’s Greatest Manufacturer. New York, NY: McGraw-Hill

Publishing; 2004.

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as forgetting to order the HPV test. Condel et al4_{describe this} process as an example of a “work-around” practice that has been adopted in general by the medical community. In this process, we attempt to fix the problems ourselves by creating new quality checks to prevent the error rather than fixing the problem from its roots. In doing so, we create additional steps in the process that have a temporary effect, much like a Band-Aid. We eliminated these marking and highlighting steps in the postimplementation map and instead focused on standardizing the process of handling the Pap test, rendering such markings unnecessary in the future. Our data confirmed that the error rates were improved despite the elimination of these steps.

In summary, implementation of single piece flow and minimizing batch size allowed for higher quality, efficiency, and greater patient safety by maximizing up-front detection of specimen labeling errors and eliminating rework associ-ated with passing these defects downstream. Single piece flow further improved efficiency by reducing the number of times each specimen is handled and reducing the processing TAT by eliminating redundant steps and wait times that were inherent in the batch processing method.

Lean tools, such as VSM, offer the opportunity to improve quality, operational performance, and patient safety in the cytopathology laboratory. The tools were critical to the suc-cess. However, equally critical were staff empowerment and engagement, some of the key principles central to Lean philos-ophy.5_{The tools are powerful in achieving short-term process} improvements, but it is the Lean philosophy and principles that sustain continuous improvement in overall performance.

From the 1_{Department of Pathology, Case Western Reserve}

University, Cleveland, OH; and Departments of 2_{Pathology and}

3_{Surgery, University of Michigan, Ann Arbor.}

Address reprint requests to Dr Michael: Dept of Pathology, Case Western Reserve University, 11100 Euclid Ave, Room 212B, Cleveland, OH 44106; [email protected].