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Variation Kills

In the state of Colorado, there are efforts underway to reduce the number of accidents occurring on the I-70 mountain corridor.  If you have driven this route in the last ten years, it was probably during the tourist season, and you saw the sources of the problem first-hand.  Specifically, there are major mountain ascents, long tunnels burrowing under mountains, “merge zones” (lanes changing from 3 to 2 before entering tunnels), posted speed changes, too many cars, and too much snow (and many people not used to driving on it).  This is a bad mix of conditions and result in one of the most congested stretches in the U.S. interstate highway system.

Civil and traffic engineers have known for years that the major problem to congestion and accidents is the traffic speed differential.  The American Association of Surface Highway Transportation Officials points out that crashes are not related so much to speed as they are to “the range in speeds”.  Also, more studies have shown that when the speed varies, there is a greater chance of a crash.  To fight this, Colorado is engaged in a program called “active traffic management”.  This involves (in part) putting out pace cars on the highway to regulate the speed of all the vehicles, thereby improving the average speed.  Though some (actually many) might complain about this, the fact is that it does work: the average time per car over the entire population of cars is improved.

In the business of process engineering, we are fond of saying that variation “kills” (the example above makes a more literal case).  In the lab environment, when we say variation kills we mean that this is the thing to concentrate on more than any other.  For example, it’s not so much the average turnaround time of a cardiac marker that is the problem: it’s the fact that most of the tests are completed in 30 minutes and some are taking 2 hours!  The problem is the variation, or more specifically, the unreliable processes that are creating variable outcomes.  Although the data range might be 1 ½ hours, the average will look artificially good at under one hour.  This is why many labs (and other organizations) rely on a compliance number instead of an average number (i.e., turnaround times are under one hour, 80 percent of the time).  This provides a more accurate picture of what is going on in the lab.  With this in mind, our quick approach to dealing with variation includes the following:

  1. Understand and accept that variation is a natural outcome of a process
  2. Perform root cause analysis to identify the source of variation
  3. Improve the poor processes through Lean and other continuous improvement methods
  4. Watch for exceptions (signals) that indicate the process is breaking down
  5. Start again at 1

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When Automation Goes Bad

Main newsletter article, September 2011

the summer of 1997 I was touring a reference lab facility in the Denver area.  They had recently installed a total lab automation (TLA) system which was all the rage at the time.  With the new system, the medical technologists were concerned about quality while management was excited about becoming “cutting-edge” (the supervisors were caught in the middle and were looking forward to the weekends).  The system, which essentially linked the major analyzers together with a conveyer belt (“track system”) cost in the range of 1 million dollars.  For that cost, the lab was able to save the time involved in transporting specimens, which was about 1% of the overall labor time involved in lab testing.  So, for 1 million bucks, they saved 1% of the labor.  This didn’t seem to make sense to me, but the news was actually worse than that:  the new track was prone to jams, disconnects and random incidents of failure.  As a result, the lab had to hire 4 FTE to maintain the track.

A bad investment?  Probably.  There are different sides to the argument.  One might say that the goal wasn’t to save labor time, or improve on turnaround times (with which the track didn’t help), but rather to create consistency.  If there is one thing that automation can accomplish it is this:  creating a standardized process.  It sounds obvious, but automation does have a funny way of doing the same thing, the same way, every time (except when it breaks-down).

In the fifteen years since, we at Nexus have seen all kinds of automation in the clinical and pathology laboratory, from “islands” of automation, to automated processing systems, to assisted slide screening devices and even slide makers that also stain.  We also have seen little boxes resembling a Nintendo that actually perform STAT testing at the bedside.  Some of these systems have gone bad, and some have provided a payoff like a lottery winning ticket.  Making the right bet does involve some luck (i.e., not buying a lemon), but at Nexus we have found that your chances are better with the following in mind:

  1. Improve the process first –automation is only one part of the value chain: the process must support the automation
  2. Don’t be an early adapter – it is fun to be the first on your street to get the iPhone or Android, but in the lab, a bad decision has serious ramifications
  3. Research – find impartial, data driven comparisons on the automation class (Nexus and others provide this information)
  4. Purchase a Lean-enabling device over one that isn’t (more information at http://leanhci.com/wp/the-lhi-lab/)
  5. Provide a detailed RFP that requires the vendor to prove its products value and provides integration services to your lab’s workflow
  6. After buying, control the process through continuous improvement – always remember that automation isn’t the answer, only one step toward an improved operation

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The Lean-enabled Device

August 2011 Main Article

Nexus is a management consulting company that works with laboratories and healthcare IVD companies to help create a more effective laboratory operational environment.  In this capacity, we are frequently asked to identify the analyzer, instrument, automation or other device that will help make the laboratory more efficient.   Sometimes this is not a simple answer, and depending on the situation and operational characteristics of the laboratory, there could be many correct answers.  However, the industry is in general agreement that the Lean philosophy toward lab operations will ultimately create a more streamlined and effective lab that will reduce waste (to include testing errors) and more frequently meet the expectations of the customer(s).

The outcome of Lean in the clinical and pathology laboratory usually takes the form of Lean Lab initiatives.  Generally, Lean Lab initiatives accomplish the following:

  1. Compress the chain of events leading to the test result by eliminating the steps that are not of value to the customer
  2. Organize the work area through an ongoing process of cleaning and sorting
  3. Ensuring the physical environment is streamlined
  4. Creating a flexible operational environment
  5. Installing items and features that will dramatically decrease the opportunity for human error

A Lean-enabling device (such as a clinical laboratory analyzer) is one that makes it easier to accomplish the above initiatives.  Characteristics of Lean-enabled instruments might include:

  • Continuous, random access devices that can be operated in small batches, or even handle a single patient at a time
  • Instrument requires little labor input relative to output (human interfacing)
  • Instrument requires little labor input relative to output (electronic interfacing)
  • Instrument generates test results faster than other options
  • Instrument has the flexibility to prioritize certain work (i.e., STAT tubes) without affecting the main work processes
  • Flexible modes that allow for quick change over when needed or walk away ability
  • Relatively small instrument and functional footprint
  • Flexibility to be moved or integrated with other devices or informatics as needed
  • Poke-yoke features that minimize human error
  • Instrument uses relatively few consumables and generates relatively little waste compared to the output

So, when answering the question of which device is more effective, we usually revert back to the criteria above.  If a device meets many, if not all, of these characteristics they will help the lab manager to accomplish Lean goals.  It is important to point out that no device will create a Lean environment for you.  Rather, the some devices are more suited to better enabling Lean initiatives.

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Lean and Green: Lab Automation Design

July 2011 Main Article

For many years the major clinical and pathology automation vendors have understood the lean concepts of minimizing waste and optimal piece-flow.  Design engineers have looked at workflow in the laboratory and asked customers questions (usually via marketing channels) as to how the instrument can be designed to help the lab achieve their goals.  More often than not, lab goals in recent years have centered on work and product efficiency.

Early in the diagnostic instrument life-cycle an instrument is usually as good as the quality of the test.  As time progresses, the designers must compete by providing better instrument features.  An example of this evolution is the instrument rack size.  Early instruments are typically designed to work with batches of samples (sometimes up to 96 samples – the size of a micro plate).  Over time the assay quality is assumed and the customer demands more flexibility and better throughput from lab automation.  An outcome of this is usually better batch size: instead of running 96 samples (and having to wait for all 96 to complete) the customer demands single piece flow so that the cycle time per sample is improved.  Although the best solution would be single-piece flow with batch sizes of 1, the compromise is usually somewhere in-between.  This is why many instrument racks have a capacity of 5. 

Additionally, many vendors have done good work with visual cues: having identification and color codes to help the operator to avoid mistakes.  Poke-yoke techniques (fail safe features) are also used (i.e., designing a reagent bottle to fit only in the exact spot on the instrument where it is designed to rest).

The next phase of instrument design has been in motion for some time and involves the “green” aspect of “lean and green”.  This isn’t just a socially conscience need.  Many labs spend tens of thousands of dollars per year in solid and liquid disposable costs.  The labs that try to minimize these costs (such as pathology labs that perform xylene recycling) are still spending thousands of dollars in labor and capital.  Lab suppliers are working on these issues, from the aggressive (xylene substitutes) to the moderate (more efficient reagent packaging).

The “Lean and Green” evolution has fully arrived.  The suppliers that don’t address these issues will be hard pressed to compete in the lab space.

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Tools of the Trade: Mapping 

July 2011

Every quality management approach begins with Understanding the Customer’s need.  This phase, also called Voice of the Customer, is important to determining what is of value to the customer and what is not.  The next phase to any quality management approach is Understanding the Current Situation.  This step, like all of phases of a process, is critical to accomplish the steps that follow.  Some ways to capture the current situation are through time studies, flow charting, interviews and metrics monitoring.  A Lean method, the Value Stream Map (or VSM), is a visual tool used to broadly understand the workflow of an operation.  Like all management tools, there are slight variances in how they are constructed, but generally they show the inputs to a system, the outputs and the major steps involved in converting the inputs to outputs.  VSMs also depict the flow of information as it is used to support the operation.  Finally, the VSM will also track the (cycle) time of how long it takes an item, like a specimen tube, to journey through the system.

The scope of a VSM will depend on the goals of the project.  In the clinical laboratory the scope is typically the specimen tube from the arrival time in accessioning to the end point at specimen archive and test result release.  A VSM could be used to track a nursing position or the path of the patient record (this is becoming important in the age of electronic patient records).  If a hospital administrator is interested in improving patient satisfaction, then the VSM might focus on the “patient journey” from admitting to discharge, with the patient being the product.

Training for VSM can be performed by Nexus in your operation.  If you have a need for many studies Nexus can also train your personnel to be VSM experts.

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Transfusion: The Lean Approach and Activity Based Costing in Operational Decisions

June 30, 2011

Clinical transfusion laboratories worldwide are facing a time of uncertainty.   Whether it is healthcare reform, austerity measures, an aging population, or simply the challenge of an increasing demand, there are operational hurdles to meet in transfusion markets around the world.  These pressures, however recent they may seem, are not new, and methods and tools are available to help the transfusion manager to navigate through the uncertainty.  Two such methodologies are Quality Management Methods and Total Cost of Operation.

Quality Management Methods have been used for years and evolved in each industry in such a way as needed.  In the clinical diagnostics world, the Lean Methodology has taken hold for good reason:  it has a common sense approach, requires little training, and can be implemented quickly with good results.  Methods like these are critical as our lab processes will break down over time and methods like Lean ensure that they are constantly reviewed for effectiveness.  Once changes are made, it is then important to monitor the operation regularly to ensure that performance doesn’t slip.  Benchmarking and other metrics are commonly used to this end; however, total cost of operation (TCO), an Activity Based Costing tool, is being used to fully understand the financial impact on the operation.  Gauging progress through benchmarking and other methods is important for understanding if we are making progress or slipping in the operation.

These methods are proven and have been tested through time.  They should be considered as one of the many tools in the transfusion manager’s arsenal, because in this economic climate the more tools the manager has available, the better chance for success.

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Labs Face Macroeconomic Challenges

March 27, 2011

A recent industry article summarized the future of in vitro diagnostics as one “buffeted by uncertainty and unstable economic forces”[1].  In the article, a broad survey indicated that administrators and managers from the U.S. lab market are concerned about a variety of things, but especially about healthcare reform legislation.  Whether reform leads to an increase in costs, additional regulatory oversight, or general economic hardship, the overall feeling is that the status quo will not work in the future.  As we at Nexus travel around the world working with laboratories, we hear the same concerns, and the challenges facing countries like the UK are just as, if not more, pressing than what we see in U.S. labs.

Another article stated that the uncertainty of legislative changes would force managers to develop a “deeper and more detailed knowledge of the laboratory’s economic structure” and “maintaining the status quo will be a losing battle”[2].

These articles have the same tone, essentially saying that administrators and managers must think progressively to keep up with the macroeconomic changes that are coming down the pike.  The first article was written in 2011.  The second article was written in 1983.

Reading these articles reminds us that the more things change, the more they stay the same.  In 1983 the dreaded acronyms were DRG, HMO and PPO.  Today it is ACO, EHR and LDT (regulation).  The solutions in 1983 were shared services, manpower cross-training, test consolidation, lab marketing, decreasing fixed costs, the outsourcing of unprofitable tests, and generally the “development of a good accounting system to accurately classify and measure the lab resources consumed by each type of test”.

In 2011 we have yet to see what the solutions are, though we at Nexus believe that they are similar to the solutions in 1983: continuous operational improvement and using the right measuring instruments and accounting tools to gauge progress.  If you have read or worked with Nexus before, you see this in the total cost of operation programs we have developed and the CI methods to include Lean and other methods.  The challenges are here, some old and some new.  They are not all understood, but regardless they will require progressive thinking, and like in 1983, the proactive labs will survive.

[1],[2] see newletter archives for references