Lean Thinking - Unlocking the Mysteries to Simplify Work and Improve Quality
Have fun as you learn why laboratories, factories, or any group of people working together operate the way they do and how the application of lean concepts can reduce stress, improve operations, and mitigate error potential in the highly complex environment of Histology and Anatomic Pathology Services. The presentation will highlight real-life use of Lean Six Sigma principles and how these principles and tools will help the participant to affect change in their lab in order to improve their overall lab performance and enhance patient safety efforts.
- Understand the origins of Lean and Six Sigma and the fundamentals of each.
- Learn basic tool sets of Lean Six Sigma utilized in healthcare.
- Gain understanding of how these principles and tool sets can be applied to the histology laboratory to improve workflow and efficiencies while improving the work environment.
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MS. LINNETTE GROVE: [SLIDE 1 00:00:01] Hello, everyone, and welcome to the 27th presentation of the Leica Pathology Leaders Webinar Series.
My name is Linnette Grove. I'm the IHC specialist for western PA, Western New York, and northern West Virginia for Leica Biosystems. I will be your host today.
Our discussion today is entitled "Lean Thinking: Unlocking the Mysteries to Simplify Work and Improve Quality, presented by Debra Schofield, West Regional Lean Histology Consulting Services Manager for Leica Biosystems.
This presentation will take about 45 minutes. Immediately afterward, we will have 15 minutes to answer questions. If you have any questions during the presentation, please select Q&A from the menu bar at the top of your screen or send us a chat message. We will answer all questions at the end of the presentation for everyone to hear.
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This webinar is being recorded and will be available for viewing or downloading on our website, PathologyLeaders.com, in about two days.
If you are viewing this webinar as a group, please have your group administrator distribute the post-event survey URL to everyone in attendance. The survey will open in your browser after the event and must be completed to receive the PACE credit.
Once you have completed the survey, you will be automatically redirected to a certificate generation page. Please take note that this link will also be emailed to you later this week. You will have the survey link within two to three business days, just in case you do not take the survey right after the presentation.
Also, the CPD credit for UK attendees will be available with the archive.
At this time, I would like to present our speaker. Debra Schofield has been involved in the field of clinical laboratory medicine since 1975 and in the diagnostics industry since 1987. Her current responsibility involves utilization of Lean and Six Sigma tools to support AP laboratories in their efforts to design more effective and efficient work spaces, as well as develop cost-effective processes which streamline workflow, improve employee satisfaction in their work environment, and mitigate the potential for error. Debra has degrees in biology, chemistry, and medical technology from Pacific Lutheran University. It is with my pleasure to hand the presentation over to Debra.
DEBRA SCHOFIELD, MT (ASCP): [SLIDE 2 00:02:59] Thank you, Linnette. Hello, everyone, and thank you again for your attendance and interest in this topic. We're going to do a bit of exploring into the concept of Lean and how it can unlock the path to more simplified and higher-quality work in the anatomical pathology laboratory.
[SLIDE 3 00:03:21] We're going to be discussing three major topics, which include why we're involved in Lean in health care in the first place, what are the fundamentals of Lean, and how do we adapt those fundamental principles to the AP lab?
[SLIDE 4 00:03:41] I think that you're probably all familiar with the issues that we face in the AP lab today. We recognize that these issues exist and the broad effects that they can have on the organization, as well as patients that we serve.
Our traditional approaches to fixing these issues in the past has been either through acquiring new technology or cutting budget. But those approaches are not netting the same benefit they once did. We need to find a better way.
[SLIDE 5 00:04:21] Each day we come into work wanting to do our best possible work. We don't intentionally make mistakes, and we in the scientific community are always introspective in studying how or why things happen, in an effort to improve and drive decreased error. So we acknowledge that in AP, there are a significant number of labeling errors that do occur.
[SLIDE 6 00:04:45] At the service-line level, great attention has been paid to the issue of errors in labeling specimens, and studies have been conducted in an effort to identify the root cause as well as the means of mitigating the potential for these errors to occur.
Control of a specimen begins outside the boundaries of the laboratory. And when errors occur in the surgical suite, they may or may not be caught during the laboratory accessioning or specimen data entry process.
[SLIDE 7 00:05:19] And the focus of attention has been raised at higher levels beyond the individual health care facility. The Institutes of Medicine have initiated several studies in the last decade, creating a correlation between medical mistakes, resulting deaths, and the financial impact to the health care system. The cost of medical mistakes, both from an economic and a human perspective, are significant and are no longer being ignored.
[SLIDE 8 00:05:50] And as these studies are conducted, the government weighs in with its own conclusions, which typically come in the form of reduced or denied reimbursement. Since the early eighties, with government spotlight on healthcare--originating, as some of you may recall, with cytology Pap smears and the evolution of DRGs--the tolerance for health care has narrowed. And the government has set ever-increasing financial restrictions which, in their view, are employed to drive up quality.
[SLIDE 9 00:06:23] And as regulations change, the lawyers follow. Not only are health care institutions liable, but there has evolved an increasing focus on individual accountability as well. In this case, mislabeling a sample constituted willful misconduct because the health care worker did not follow the procedure established by their department. It kind of makes you stop and think.
[SLIDE 10 00:06:51] And of course, there is, most importantly, the patient. That could be your brother. It could be your son or your nephew. It could be you. So this drives us to continually strive to find ways to be better, to find the next higher level of quality.
[SLIDE 11 00:07:11] It all begins and ends with quality. If the quality of laboratory results is questionable, how valuable are they to the patient's diagnosis? And from a business perspective, any company's survival is dependent, in large part, on their ability to deliver a certain sustained level of quality.
[SLIDE 12 00:07:35] So why Lean? Why now? If we didn't already have sufficient reason to accelerate process improvement initiatives, we can always look to the trending in reimbursement, or overall the cost of delivering services versus the rate at which we are paid as providers. There is no question that we have to find new ways to adapt.
Consider this: reagent and capital costs only represent approximately 8% to 17% of the total operating budget for your laboratory. Even if you reduce these costs by 70%--let's say you took them even further. Let's say you reduced them to zero--you would not significantly close the ever-widening gap that is developing.
This is where Lean comes in. Some of you may already be aware of Lean initiatives which are taking place throughout other departments in your organization. Often, some of the early adopters for this discipline are admitting--the emergency department, radiology, and even dietary.
[SLIDE 13 00:08:43] So first, let's explore before we talk specifically about Lean. We'll talk about what is process improvement. What is a process, period? It is simply a series of tasks performed to achieve a given output. The more steps and/or people that are involved in the series of tasks, the more opportunities for error. And therefore, given throughput for a process will have an inherent error rate associated with it.
Process improvement seeks to streamline processes by eliminating unnecessary steps and error-proofing as many of the remaining steps as possible. Therefore, process improvement allows us to increase the throughput, while keeping the errors at a minimal level.
[SLIDE 14 00:09:34] And Lean is fundamentally a form of process improvement. [SLIDE 15 00:09:37] However, it is much more than that. Lean Six Sigma is a blend of two separate disciplines, and it's defined as a "methodical, systematic approach to addressing quality improvement through minimizing defects and costs by controlling waste and variance in a production process."
Both seek to remove defects and decrease costs. Six Sigma looks at variations in a process, thereby creating consistency in the output. Lean, however, is focused on removing wasteful steps out of the process. Both are highly disciplined methodologies, with focus on quality.
[SLIDE 16 00:10:24] In its most simplistic terms, Lean can be defined this way. We look at work that should be done, and we look at ways that should not be done.
[SLIDE 17 00:10:38] And as you examine your process, and you determine into which two buckets each of the steps in your process fall, you strive to eliminate the waste out of the process and streamline it, simplify it, and get work done more quickly, more efficiently, and more error-free.
[SLIDE 18 00:11:01] So what are these wastes that we're talking about? Well, the slide says seven wastes, but there is actually a total of eight. Talent was added probably in the last ten years into this list, and it was added because the talent pool, especially in healthcare disciplines, especially in histology, is declining. And as that available resource becomes less and less available, it becomes more important--more critical that we focus on utilizing those talented people in the way in which they can be best utilized and not spent doing things that could be either automated or done more effectively in another fashion.
[SLIDE 19 00:11:54] So let's look at how these wastes in Lean translate into a laboratory setting. Transportation speaks to waste that develops as specimens or product, as Lean defines them, move throughout the work process. So typical examples would be moving samples from room to room, having a workspace layout that requires that multiple transport steps take place in order to get the specimen through all the steps of the process. Moving equipment, tables, or carts to supplement inadequate workspace--this happens quite often in histology, where you will have a cart on wheels that you pull up next to the embedding bench so that you have that extra additional space that you need, either to provide you storage for supplies that you use, or additional countertop space that's required as you do your work.
But all of that additional little table that you're moving around constitutes a waste in terms of transportation and moving it into position and out of the way as you have to move back and forth between your work space and other work that you're doing.
Inventory waste in a laboratory shows itself as overstocking of reagents or gloves or Kimwipes or, most notably, slides--stacks and stacks of slides--that may actually represent more like several weeks' inventory, rather than just a week's worth of inventory or a day.
Orders build up in accessioning that need to be entered into the computer system. That's a type of inventory as well. And access in standing orders--standing orders may have been set a year ago. Volumes may have changed. They may have declined. And without adjustment to the standing order, now all of a sudden, you're creating waste in inventory, because you've got more than you need on hand to do the work that's presenting itself.
Motion, like transportation, is also movement. But in this case, motion refers to the movement of the operator themselves. So having to get up and down from your workbench in order to retrieve supplies or samples from another area of the laboratory will constitute a wasteful motion.
If you have a large breach or walk distance in order to complete a process step--let's say between embedding and sectioning is actually another bench where you may do the special staining--it's out of sequence in terms of the work that has to be done, and so you have to move through that space in order to get back and forth between the two parts of the process, which are actually logically connected to one another.
Sneakernetting is a little bit of affectionate term I have for anything where you have to get up and run to create a communication link between you and a pathologist, you and someone in accessioning, for instance--anywhere where you're having to communicate because there is a void, either technologically, because there is not a computer, the computer connection, et cetera.
Waiting waste represents itself as idle equipment or people. In other words, work is not sufficiently level-loaded so that everyone who is in different sections of the department have work to do at the same time. So they're waiting for things to occur. If there are 124 specimens sitting in accessioning, there is nothing for the people who may be working in the grossing area to do at that point in time, creating idle time for those individuals.
Specimens that are sitting waiting for external courier transport also represents a wait time waste, as well as any kind of internal transport between departments.
Overproduction is represented as multiple signatures that may be required, accessioning department making multiple copies of forms before they get moved on into grossing or transcription, duplicate or multiple information system entries, and printing a hard copy of a report when a digital copy is really sufficient.
Overprocessing, which is closely related but different, may look like batch printing of patient labels or advanced batch printing of slides before they're needed--printing of cassettes, which may or may not get used during grossing; also, in the sectioning area, cutting additional slides, which may or may not get used later on for extra stains that get ordered by the pathologist.
All of this has to be evaluated individually, of course--not to say that all of this should be excluded; just areas for consideration.
And defect waste is simply that. It is an error, an omission, or some other mistake that's made--incorrect specimen slide or cassette labeling, rehydrating embedded specimens because they've been processed or overprocessed in the tissue processor, a lost sample, and tissue that gets lost from the slide during staining.
And then we've talked already a bit about talent and skill waste.
[SLIDE 20 00:18:33] So this is--I like this chart because this actually comes from Toyota and how they think about Lean. And I think it represents very well pulling together all the principles of Lean and understanding what it's built upon. So the foundation of the pillars of Lean is the structural framework on which you use all of the Lean tools. So this creates stability and standardization in the organization.
And the primary tools used in this foundation are 5S, which we're going to talk about, TPM, which is actually Total Productive Maintenance--a little bit different meaning for that acronym, but TPM emphasizes proactive and preventative maintenance to maximize the operational efficiency of equipment. And that's probably used a little bit more in production--other types of production industry. But it can also be applied in the laboratory in terms of predictive maintenance on equipment, understanding when an instrument may need maintenance before the need actually arises or a condition presents itself, where the instrument fails and creates work stoppage.
Standard work or standard operations is the third component of the foundation. And kaizen, or rapid improvement, is the fourth.
Then central to all of this model is actually respect for people, both within and externally to the organization. It's very important in a Lean environment, for Lean to succeed, that people be central to every consideration that's made, every change that's made. It's very important that everyone in the organization who has hands on the work is part of a team that helps build that change, builds that environment for how the work is going to be done in the future. So there is a great deal of empowerment of individuals. And most of the best ideas for change in the laboratory come from the people who do the work each and every day.
Cross-training is central to Lean as well, so that there can be a flexible movement of workforce resources that are needed, depending upon the volume of work and where they need to be at a particular moment in time to keep work flowing.
The concept of hoshin is very important when we're talking about respect for people. Hoshin is actually what I call policy deployment. And it captures the strategic goals of the organization. It strives to get every employee pulling in the same direction at the same time. It achieves this by aligning the goals of the company, which is the strategy, with the plans of middle management or the tactics and the work that gets performed by all of the employees, which is operations.
So as people are doing the work, there is an understanding of the strategy and the reason behind why things are being done. And as it makes more sense, it's done more effectively.
Now, to the left on our pillars here are some of the most common resources or tools that we use in Lean. And they are known as just-in-time resources. So this is where the concepts of pull and flow come from--task time, which is the heartbeat of your process, heijunka, which is level-loading. And we're going to be talking quite a bit about that when we get into applying Lean to the AP lab. But level-loading is critical to smoothing production.
And then cell design and a couple of other things--single-minute exchange of die, which is really another production term. We don't use that too much in the laboratory. It really deals with change over time, so it has more to do with equipment, potentially equipment in your tissue processing area. But it's not too often used in AP.
Then on the right-hand side of this diagram, we have jidoka. And jidoka is the concept of automation with a human touch, or I prefer to call it human-centered automation. And there's a lot involved in this category, but I would probably say--and we'll get into just a little bit of how that applies to the future of technology in the next slide.
But the most commonly used concepts out of this side of pillar are puka yoke, which is error-proofing systems. An example of error-proofing would be the fact that when you get into your vehicle in the morning, and you the key in the ignition, a couple of error-proofing concepts are that you have to step on the brake, and the car has to be in neutral, or it will not start. Those two factors are actually a way of error-proofing, to make sure that you can't just turn on the vehicle, and if it were in gear, it would just immediately race forward or backward, potentially causing an accident. That is a form of error-proofing. 5 Whys and built-in quality are another couple of concepts that we use.
And all of these Lean concepts and pillars build up to the ultimate output, which is customer satisfaction. And in the laboratory, a customer can be several. You can have the pathologist is your customer, the patient, of course, is your customer, and you can also have other internal and external customers and forms of clinicians and clients that you serve. And ultimately, business success comes out of this model if well-applied.
[SLIDE 21 00:25:42] So let's talk about jidoka for just one moment, because this is an important concept that frequently gets forgotten in the whole concept of Lean. But it isn't something that your vendor partners have forgotten, because this concept of automation with a human touch is evolving equipment. You're seeing it come out in terms of automation for IHC, where the instrument is doing more and more of things that used to have to be manually done by the operator are now fully automated. Tissue processors that have the ability to tell you when alcohols need to be exchanged out, because they keep track of it instead of you having to manually keep track of it.
So this is really the concept--this and automation, which is a concept of jidoka, are in the works behind the scenes with your vendor partners and developing the future of automation, where more and more, you're going to see AP equipment come out with less human interventions necessary to make it do its basic functionality. So it's thinking machines.
[SLIDE 22 00:27:04] So let's talk about the five key Six Sigma--Lean Six Sigma principles. First, understanding Lean, we go all the way back to the origin, which is really the patient. And we understand that value is created. The only way value is recognized, let me say, is from the customer's perspective. If the customer was able to biopsy that spot on their arm themselves, put it onto a slide, and hand it to a pathologist and ask him, do I have cancer, and get an answer, that's exactly what they would do.
But since they're not able to do that, we're all employed. And in light of that, we need to understand that everything that we do with that tissue specimen once it's taken from a patient has to be something that they would be willing to pay for because they can't do it themselves. So fundamentally, value is created when the product is--the fit, form, and function of that tissue product or tissue specimen is changed.
So when we think about everything that happens in histology, from the time it hits the doorway until it's in the hands of the pathologist, the steps that really change the form or function are grossing, tissue processing, embedding, sectioning, and staining. Everything else that transpires may be absolutely necessary, but it is a form of waste. It may be necessary waste, but it is a form of waste. And it doesn't add value that the customer would be willing to pay for.
Second key principle in Lean Six Sigma is pull. And this is the concept that work is synchronized and designed to match demand. And most things in the AP lab are very much a pull system. There isn't any way to create work before there's a demand for it. Tissue specimens are presented and actually work through the system in a pull environment.
However, inventory, on the other hand, is most often very much a push. If you look at most labs, we're overstocked with supplies. And that is kind of a push inventory system, where we think we're going to need it, but it may be way over the volume that's actually required.
Flow is so critical, it's mentioned three times here. This is where level loading comes in. It's all about the concept of continuous, and ultimately single-piece, flow. So it's getting to your lowest possible inventory of product and supplies and having those at point of use and just in time, eliminating large batches, getting to your smallest batch size.
And Lean is not a one-time thing that we do. Lean really is a culture that we develop in the organization for continuous improvement. It's about systematic change and renewal. And it's about bringing about innovation to continuously drive out costs and reduce the cycle time.
And fifth and final is something that's a little bit foreign to us. We all know that, as we get a job, we have a job description. And from the perspective of Lean, job descriptions come at the very end of designing the process. So in other words, even though I may be a histotech, and I'm assigned to this particular bench, and this is what I know, and this is what I do, in Lean, the roles actually are defined by how the best possible process works and then what do people need to do to complement that process and make it work most effectively.
So it's a little bit different approach to understand roles and responsibility in the laboratory, because it does flow out of whatever process you have designed.
[SLIDE 23 00:31:47] Lean tools that we use--level-loading, for one--we're going to be talking about this with regards to tissue processors and also embedding and sectioning. It's about getting away from badging and having a consistent, even flow of work through the department.
Standard work is not just about standard operating procedures in your procedure manual, because those are important. But standard goes deeper than that. It actually defines what the work space looks like, what's contained in it, and how people do that particular work.
Standard work is well-represented, and if you've ever been to a Kinko's or what are now called FedEx Office stores, if you walk in, and you go to use one of their copiers, you'll see that, at the work space, they have taped off everything in terms of where a stapler goes, where paper clips reside, where extra paper is located. Everything is labeled. And that is a standard workbench. Every single copier that you walk up to in a FedEx Office store is going to have that very same presentation. And that is a model of standard work.
Layout analysis is understanding how your laboratory is set up in relationship to the process steps. And is that layout consistent with the sequence of steps that you have to go through to get the work done each day. Is there anything that could consolidate the footprint of the work that has to be done, so that you have less transportation, less motion. So it's very much, I would say, key to making sure that you have the most efficient laboratory process possible.
Layout is, as I said, critical to both transportation and motion, which can equate to an impact of 25% in terms of productivity--so very critical Lean tool.
5S, which we'll go into some detail in in a moment, visual management, which was the Kinko's example--those are some types of visual management, and we'll be talking about that in a moment; and then error-proofing.
[SLIDE 24 00:34:25] [SLIDE 25 00:34:27] So where do we start? And Dr. Harry from the Six Sigma Management Institute says we have a bit of homework that we have to do first to first understand our entire process before we embark on ways to fix it. And it's okay that we don't know everything about our process. We're buried in it every day in so much detail and so much work that we barely have time to come up for air and really examine what we're doing from a more analytical perspective.
But this is an important thing to understand. We really don't know what we don't know. We can't act on what we don't know. And we won't know until we search, and we won't search if we don't question, and we won't question what we don't measure. And unfortunately, in the laboratory, we can be very data-poor. AP systems,