KataCon 2017 Keynote: Joe Ross

Joseph P. RossLast year I nominated Joe Ross, the CEO of Meritus Health in Hagerstown, MD to be a keynote speaker at the 2017 KataCon. I did so because I think Meritus has a compelling story.

Like many organizations, Meritus had engaged in several years of staff-led improvement focused on events and things like “A3 Training.” And like many organizations, while the individual events seemed successful, the actual long-term traction was limited.

A little over a year ago Meritus started exploring Toyota Kata as a possible way to change the cultural dynamic. The 2017 KataCon will be on the anniversary of our first training session.

In the meantime, Meritus also applied the same thinking to how they did their senior leader rounding, as well as applying the thinking shifting the way the staff interacts with patients and each other.

Joe’s talk will cover these key points and the lessons they have learned along the way.

I hope you will be there to hear his message and meet him as well some of his key people.


NPR: Hospitals New Face Pressure to Reduce Infection Rates

This article on NPR is chiefly about the dilemma that hospital administrators are facing as escalating government reporting requirements are being tied to their Medicare payments. (For my non-US readers, Medicare is the U.S. government medical insurance program for seniors and retirees. It pays a huge portion of hospital’s revenue, and thus, its policies carry a lot of weight).

The article’s lead does a good job of summing up the issue:

Under laws in more than two dozen states and new Medicare rules that went into effect earlier this year, hospitals are required to report infections — risking their reputations as sterile sanctuaries — or pay a penalty. That’s left hospital administrators weighing the cost of ‘fessing up against the cost of fines.

So, in effect, the administrators are faced with weighing the financial impact of lost Medicare payments vs. the financial impact of telling the truth about their infection rates. This is, in my mind, yet another symptom of the General Motors style of management that is taught by every MBA program in the world.

It also suggests that there is a viable alternative of continuing to maintain the illusion that it is not a problem.

Is it a problem? Hospital infections kill about 90,000 people a year in the USA. Compare that with the 40,000 or so that are killed in traffic accidents, and you get the idea.

Add to that the fact that the patient ends up getting billed (and usually insurance pays the bulk) for the treatment of these infections.

Fundamentally this is about quality, and the problem is certainly not limited to health care. (it is just that lives are at stake)

How does your company respond when there is a known issue that is impacting quality?

If you deliver a defective product or service, do you charge your customers for the rework? This is not a facetious question. Some companies do.

Do you avoid collecting information for fear of revealing the true magnitude of a problem?

Do your workers fear bringing it up when they are directed to carry out inappropriate actions, or actions which violate the company’s written policies and procedures?

Is it OK to improvise outside of your known process in order to get the part out the door?

Back to the hospital – we know how to tackle this problem. It is merely extremely difficult. That doesn’t make it impossible. I am glad it is getting attention. I am disappointed that it takes government generated threats of visibility to get action.

Some Healthcare Observations

A couple of weeks ago I had the opportunity to return and see my friends in the Netherlands, and I’d like to share some observations from the Lean Thinking in Healthcare Symposium I attended over there.

But that conference was on Friday. I arrived in-country on Monday morning at 7:30am. By 10:30 am I was in sterile scrubs in an operating room observing a knee replacement operation. (I was told of this agenda while on the way there, at about 9:30.) I’ve got to say it was quite an interesting experience, and here is my public, if belated, thanks to Dr. Jacob Caron, who graciously brought me into his domain. Thanks, also, to his patient for allowing me into this bit of her life as well.

The experience was fascinating, and enlightening. Here is the core value-add of a long and complex process as the patient is moved through the various stages of treatment. And at that core, things are organized, quiet, efficient. Of course it is nothing like an O.R. on television. Drama is the last thing a real-life surgeon (or patient, for that matter) wants in the O.R.

The work flow of instruments caught my eye. We all know that the surgeon asks for the instrument he needs, and the O.R. nurse hands it to him, usually anticipating his request.

But there is a return flow as well. As the surgeon is done with an instrument, he puts it down as he asks for the next one. The O.R. nurse then quickly picks it up, wipes it (if necessary), and re-orients it so she can pick it up quickly when it is needed again.

None of this is really surprising with a little thought. I imagine the tight circle around the patient is organized pretty much the same way in every operating room in technologically advanced countries. In manufacturing, we use the “like a surgeon” analogy to describe how team members who directly add value should be supported.

Later that afternoon, I was touring the ward where the orthopedic surgery ward with the supervisor.

They are working on kaizen, they have an Problem – Improvement board and do a decent job keeping track of things that disrupt work.

“No time” seemed to come up a lot as a reason for the nurses. And, from what I know of the workload of hospital nurses, this is not a surprise either.

But where does their time go?

Let’s consider that nurses are the front line. Yes, the physicians get the attention, but aside from cases like surgery, it is the nurses who actually deliver the care to the patient. In other words, though the physicians design the care, it is the nurses who actually carry it out.

So here was my question / challenge to the audience at the conference:

No operating room in the developed world would ever tolerate a situation where the surgeon had to go look for what he needed to deliver care to the patient. The surgeon’s world is fully optimized so she can devote 100% of her attention to the patient.

Yet, in those very same hospitals, all over the world, we tolerate – every day – conditions where nurses, who are also primary care providers, spend too much of their time fighting entropy, looking for what they need, improvising, dealing with interruptions – all of the things we would never tolerate in the O.R.

Why the disparity?

British NHS Executive Talks About Lean

Lesley Doherty, the Chief Executive at NHS Bolton in the U.K. was recently interviewed by IQPC as a precursor for her being a keynote speaker at a conference IQPC is sponsoring in December (Zurich). In the spirit of full disclosure, IQPC had invited me to participate in a “blogger’s panel discussion” (along with Karen Wilhelm, author of Lean Reflections) earlier this year in Chicago.

The Chicago conference turned out to be very Six Sigma centric – in spite of having Mike Rother as a keynote. But that is history.

I want to reflect a bit about this podcast. I invite you to listen yourself- it is an interesting perspective from a senior executive who discusses her own learning and discovery. I will warn you that you may have to “register” on the web site – though you can uncheck the “send marketing stuff” box. I will also say that the interview’s sound is pretty bad, so it is hard to hear the questions, but I was able to reconstruct most of it from context.

What is interesting, to me a least, is that the methods and experiences are pretty standard stuff – common to nearly all organization undertaking this kind of transformation.

A summary of the notes I took:

They have to deliver hard budget level savings on the order of 5% a year for the next several years. That is new to them as a government organization.

They started out with an education campaign across the organization.

Initial efforts were on increasing capacity, but those efforts didn’t result in budget savings. In one case, costs actually increased. They don’t need more capacity, they need to deliver the same with less.

They have identified process streams (value streams), and run “rapid improvement events.”

Senior people have been on benchmarking or study trips to other organizations, both within and outside of the health care arena.

They are struggling to sustain the momentum after the few months after an “event” and seeing the “standard” erode a bit – interpreting this as needing to increase accountability and saying “This is how we do things here.”

“Sustaining, getting accountability at the lowest level is the biggest challenge.”

In addition, now that they are under budget pressure, they are starting to look at how to link their improvements to the bottom line, but there isn’t a standardized way to do this.

They believe they are at a “tipping point” now.

There is more, having do to with Ms. Doherty’s personal journey and learning, and knowledge sharing across organizations who are working on the same things, but the key points I want to address are above.

Please don’t think that this interview is as cold as I have depicted it. It is about 20 minutes long, and Ms. Doherty is very open and candid about what is working and what is not. It is not a “rah-rah see what we have done?” session.

As I listened, I was intently trying to parse and pull out a few key points. I would have really liked it if these kinds of questions had been asked.

What is their overall long term vision? Other than meeting budgetary pressure and “radically reviewing” processes, and “transformation.” What is the “true north” or the guide point on the horizon you are steering for?

What is the leadership doing to set focus the improvement effort on the things that are important to the organization? What does the process have to look like to deliver the same level and quality of care at 5% lower costs? What kinds of things are, today, in the way of doing that? Which of those problems are you focused on right now? How is that going? What are you learning?

What did they try that didn’t work, and what did they learn from that experience?

When you say “local accountability” to prevent process erosion, what would that look like? What are you learning about the process when it begins to erode?

The “tipping point” is a great analogy. What behaviors are you looking for to tell you that a fundamental shift is taking place?

As you listen, see if you can parse out what NHS Bolton is actually doing.

Is their approach going to sustain, or are they about to hit the “lean plateau?”

What would the “tipping point” look like to you in this organization?

What advice would you give them, based on what you hear in this interview?

Information Transfer Fail

While the dentist was looking over my x-rays, he saw something he would like checked out by a specialist. He used words like “sometimes they..” and “might be…” when describing the issue he saw.

I get a referral. The information on the referral slip is the name of the referring dentist (which I can’t read), no boxes checked, and “#31” in the comments.

I call the specialist and start getting technical questions about what my dentist wants them to look at / look for, etc.

So the process is to use the patient as a conduit for vaguely expressed (in layman’s terms) technical information between highly trained specialists.

Sadly, I think this happens all of the time in the health care industry. It seems that there is so much focus on optimizing the nodes that nobody really “gets” that the patient’s experience (and ultimately the outcome of the process) is defined more by the interactions and interfaces than it is by the nodes themselves.

I am really not sure how fundamentally different this is from a pilot asking a passenger to find the maintenance supervisor and tell the mechanic about a problem with a plane.

The net effect is, as I am writing this, the specialist’s office is calling the referring dentist and asking them what, exactly, they want done.. a net increase of 100% in the time involved for all parties to communicate.

While the national debate is on how we pay for all of this, we aren’t asking why it costs so much (or kills more people than automobile accidents do).

Looking at the wrong stuff: America’s Best Hospitals: The 2009-10 Honor Roll

This news piece, America’s Best Hospitals: The 2009-10 Honor Roll, originally got my attention because I hoped someone might be actually be paying attention to the things that make a real difference in our national debate about health care.

Unfortunately, it looks like more of the same.

This survey looks at things like technical capability – what kinds of specialty procedures these hospitals can perform, and their general reputation  and then ranks them accordingly.

But where are we asking about the basics?

Which hospitals kill or injure the fewest of their patients? What is the rate of post-operative or other opportunistic infection? How about medication errors? These are the things that all hospitals should be “getting right” and yet the evidence is overwhelming that most don’t. Further, nobody seems to be paying attention to it except tort lawyers.

Now take a look at this post on Steven Spear’s blog, and especially the Paul O’Neal commentary that he links to.

Tell me what makes a “good” hospital?

Paying the Bills vs. Dealing with the Costs

House Dems want to tax the rich for health care – Yahoo! News

The health care debate in the USA is increasingly focused on how to pay (meaning who will pay) to operate a dysfunctional system with costs out of control.

I fully acknowledge that in government circles, this is about the only thing they can address.

But the real question is not “How do we pay?” but “Why does it cost so much?”

The care delivery system itself is error prone, dangerous for the patients (and psychologically dangerous for the providers). The net effect is much of the effort of the dedicated, but overworked, staff is siphoned off to deal with problems and chaos that shouldn’t be there in the first place. But there is no system in place, at least not in any operation I have ever see (including some claiming to be “lean”) that systematically detects, responds, corrects, and solves those thousands of little issues that occur every day. People seem too focused on the “big stuff” that creates lots of press.

The financial system is worse. The processing of payments and claims is inefficient (which is a kind word), error prone, chaotic, unresponsive to issues and problems, and treats the patients as though deciphering the “THIS IS NOT A BILL” statements is the only thing they have to do.

Honestly, I don’t have any ideas here. I just see that we are in a political quagmire debating how to pay for a system that shouldn’t be costing half of what it does… and it isn’t about controlling over payments or sharpening pencils on the billing.

What if one major HMO actually “got it” and became the Toyota of health care. Any takers?

More about Overburden (Muri) in Health Care

The last post got way too long, and I wanted to get it out there. But of course, there are afterthoughts.

At a level higher than simple process chaos, overburden hits the entire organization when perceived demand is significantly greater than perceived capacity.

As I noted in the earlier post, segregating what should be routine from the true exceptions goes a long way, especially when there is work to continuously improve execution of routine things. This results in less capacity being used to process routine, and therefore, more capacity available to handle the true emergent stuff.

The next phase is to repeat the process, step by step, on the exceptions. Identify what makes them exceptions. Is there another process that can be isolated and segregated? Can you move something from “exception” to “routine” in some way?

Then look at what is left.

About 20 years ago, Philip Agre wrote a seminal PhD Dissertation at M.I.T. called “The Dynamic Structures of Everyday Life.” If you can find it, read it. This work was a major contributor to turning the science of symbolic artificial intelligence on its head. One of his conclusions was that almost everything we do is routine, and we do non-routine things in routine ways.

This thinking applies to complex, one-of-a-kind process situations. What “experience” brings to the table is knowing what things, that we know how to do routinely must be done; in what order; to gain control of the uncontrolled; and get the desired outcome.

In our heads, this is much messier than we want to believe it is. Fundamentally what we do is to try something we believe will have a certain effect, then see what effect it actually has. If the effect is the one we predicted, then we are one step closer to control and the stage is set for the next action; if not then we learn what did not work, gain a bit more understanding and try something else.

This is also how we build that thing called “experience” step by step, stretching our understanding, moving what we do not know into what we do. We do this as individuals, but it is only a truly exceptional organization that can do it as an institution. Learning is a process of prediction, testing and comparison.

The objective in these situations is to move an unknown, uncontrolled situation gradually toward familiar ground and make it into something routine.

Steven Spear quoted a health care worker that summed it up pretty well: “Air goes in and out, blood goes round and round. If either of those is not happening, we have a problem.” And in the most extreme medical emergency, the first steps are always to stabilize vital signs so that the patient will live long enough for the caregivers to understand the problem and develop countermeasures.

This is still, however, a customized sequence of tasks that should, themselves, be routine. Only the macro level varies. The more that can be done to stabilize the delivery of treatment to the patient, the less harried people will feel. They should not worry about the small things so they can pay attention to the big things.

The weak points in a complex system are the interconnections. People are not sure who should do, or has done, what. There are repeated transfers from one caregiver to another, often with far less than complete information – leaving it to the next caregiver to assess the situation all over again. Every time this happens presents an opportunity to overlook or misinterpret something that is already known.

By working very hard on execution of the things that should be routine, that much more mental capacity is made available to care for the patients. This means attacking ambiguity where ever it is found.

Mura, Muri (and Muda) in Health Care

Corrie van den Hoek, a regular reader and correspondent from The Netherlands, is working on applying kaizen in the health care industry. She left a comment on ‘The White Board’ asking my thoughts on the concepts of mura and muri in the health care field.

I think it is first important to define the terms because (1) Not everyone has heard them and (2) The translations from Japanese can differ a bit.

Mura is usually translated as “inconsistency.”

Muri is usually translated as “overburden.”

Mura and Muri are the brothers of the better-known Muda, which, of course, translates as “waste” or “unnecessary work.”

I am aware that it is possible to split hairs on the translations, but I think these suffice for the sake of discussion.

Like any industry, Health Care has a product to deliver (treatment of patients) and the administrative processes that support the care givers, patients, and keep it running as a business. There is huge room for improvement in both of these areas, and of course problems in one have impact on the other.

I started to get to these issues in this post, but did not go into any depth. The cool thing is that the article I was writing about in a general sense is actually written from a health care context. So I highly recommend reading it as some additional background.

Muri – Overburden – “Asking the unreasonable or impossible.”

In the article, Tucker and Edmondson refer to an “error” as doing something inappropriate or unnecessary, and a “problem” as something which interferes with accomplishing a task in the specified way.

Problems as Overburden

They cite a typical example of a problem. A Team Member’s task is to change linens. This task is routine. She goes to the storage area for linens on her floor, and finds none. She goes to another floor, and perhaps another, and ultimately finds the linens she needs, then returns to the task she was trying to accomplish in the first place. (She at least did not have to hire a taxi to deliver fresh linens from the service, as other caregivers reported they had done.)

At the end of the shift, however, I would wager this Team Member wasn’t able to get everything done. Or she had to hurry to do things. Perhaps the work left undone is now passed to someone else and will disrupt their work. All of this is an example of overburden – asking (or implicitly expecting) Team Members to do more than they should, or more than they can. At the very least, the floor she took the linens from now has fewer than they probably need, and another safari will be launched from that floor tomorrow.

In this case, the Team Member is implicitly expected to “do what must be done” in order to deliver care. There are no avenues to address, or even call out, the existence of these problems. Calling them out carries at least an implied professional or psychological risk of being branded a complainer, or “not a team player.”

Indeed, working around these kinds of issues is a major source of satisfaction and pride in the work culture. I quote from a quote in the article:

Working around problems is just part of my job. By being able to get IV bags or whatever else I need, it enables me to do my job and to have a positive impact on a person’s life – like being able to get them clean linen. And I am the kind of person who does not just get one set of linen, I will bring back several for the other nurses.

For management, the question is a simple one: Is this task one which you would deliberately design into this person’s work process? If not, then question why it must be done at all. But you can’t just question it. That implies the person doing it is doing something wrong. She isn’t. She is doing exactly what must be done to do the job she was given. Question why it must be done so you can remove the necessity to do it.

The Muri of Unnecessary Life-and-Death Decisions

Overburden is also the case where a Team Member is asked to make multiple perfect decisions in high-stress situations. I am not talking about deliberate decisions about, for example, what type of care to deliver. Rather I am talking about the simple decisions that are repeatedly forced on Team Members during the routine delivery of care. Many of these seemingly simple decisions are overburden because the Team Member should not be asked to make them at all. Making them adds to the work stress because, in medical care delivery, the consequences of an error can be catastrophic in terms of “negative patient outcome.”

A case that comes up time and time again in examples I hear – both from literature and in my own conversation with people inside the system is a classic one: A Team Member selects the wrong small vial of colorless liquid from a shelf or tray and injects it into a patient. Sometimes this is harmless. Other times it is fatal. These mistakes, however, only get the attention of the system when there is harm to the patient. And the attention of the system is nearly always focused on finding out who did it and assigning blame.

Steven Spear recounts a typical case in Fixing Health Care From The Inside.

He cites an investigation into a case where a woman recovering from routine surgery suddenly developed seizures. Her blood sugar level crashed, she lapsed into coma and died. Here is a key point from the investigation:

a nurse had responded to an alarm indicating that an arterial line had been blocked by a blood clot, and he had meant to flush the line with an anticoagulant, heparin. There was, however, no evidence that any heparin had been administered. What investigators did find was a used vial of insulin on the medication cart outside Mrs. Grant’s room, even though she had no condition for which insulin would be needed.

Instead of asking “Why did the care giver administer insulin instead of heparin?” how about asking “Why was insulin even in the room in the first place? This is simple 5S – eliminating the things that are not needed. Actually no. This is somewhat advanced 5S, because it is eliminating the things that are not needed NOW. Perhaps it is appropriate to have insulin in the room for some patients. But it apparently was not appropriate for this patient. And even if there are non-routine conditions which could require insulin, then the insulin should be stored in a place that forces a conscious and deliberate decision to retrieve it.

Key Point: Separate the routine from the non-routine. Separate normal from abnormal.

Another example was cited directly to me by a friend who works in Health Care. In another big-name big-city hospital a woman was in routine surgery. A staffer in the operating room chose between two clear vials of clear liquid, picked up the wrong one, and administered a cleaning substance to the patient, killing her.

Of course this scenario begs exactly the same questions as the one above it. If it doesn’t go into the patient, why is it in the room at the same time the patient is? And if must be in the room, why is it accessible in a routine way to a routine process?

Spear points out that for every death or serious injury there are many instances of these errors that do not result in serious problems, and many times that number of instances where the error is almost made, but it caught and corrected in time.

This is, in my opinion, a form of “overburden” because people are being asked to make decisions that have life-and-death consequences, and those decisions are entirely unnecessary if someone would only ask “Why did this person have to choose?” instead of “Who made the wrong choice” or (a little bit better) “Why was the wrong choice made?”

Whenever we inject ambiguity into the situation (or even allow ambiguity to persist) we are expecting someone – who may not expect it – to see it and resolve it.


Most times the proposed solution is around better labeling and identification. But I would like to suggest that “mistake proofing” is actually a process of:

  1. Systemically eliminating sources of errors by eliminating choices;
  2. If that can’t be done then putting up barriers that stop the process if an error is about to occur;
  3. and if that can’t be done by doing something that breaks unconscious routine in a way that forces the person to notice the impending error.

Better labeling falls into the third category here. Ask tougher questions, and support your people better.

What about Mura, or inconsistency?

Traditionally this is about a widely varying workload. In industry, the countermeasures are to establish a takt time, apply production leveling, set cycle times to the takt, and in general, work hard to keep the workload as even as possible. There are a lot of good benefits to this and the performance of the companies that do it very well suggests that doing it is worth the perceived costs and trouble.

One of the things frequently cited by Health Care is how their workload is wildly variant and unpredictable. These perceptions are certainly not unique to Health Care, but it is probably worthwhile exploring the situation from their context. I certainly don’t expect the Health Care community to make the leap from consumer goods or dump trucks to patient workloads and processing insurance claims.

Based on my limited dealing with Health Care, I am going to do a little conjecture, then attempt to go from there. If I am totally off base with my assumptions, feel free to correct me in a comment, and I’ll re-think.

As I see it, two big drivers for high day-to-day variation of demand on the system are:

  • Patients can show up at any time. This is especially true in Emergency Services, where, by definition, demand is unprogrammed.
  • Each individual case is potentially unique, or at the least, any one of them could go from routine to non-routine at any time.

Does that about capture it?

Shifting The Thinking A Bit

Not everything I propose here will work every time – there are true exceptions out there. But, in general, at least one of these concepts have usually helped people find some foundation of stability they can leverage.

Rather than looking at a varying aggregate workload, start breaking things down into individual streams, and finding components of stability within the variation.

Workload Variation

This graph represents a wildly varying workload. Most reasonable people are going to look at this and conclude they pretty much have to either be ready for anything, in any form, at any time.

But even in the face of wide demand swings, it is a rare operation the experiences -zero- or close to zero demand. There is some element which is reliable. Perhaps that element is small, but, at some level, it is usually there.

At first you probably won’t be able to control the wide swings, but what you can do is apply the principle of isolating instability.

Elements of Variation

This is exactly the same graph as the first one. The difference is the shading. The consistent part of the workload is shaded in green, the unstable or varying workload is shaded in red.

If you look for sources of stability, vs. causes or sources of instability, most operations can usually find something to leverage. This works particularly well in administrative processes, but I’ll work on applying it to the care-delivery flow in a bit.

An Administrative Flow

(Thanks to the GHC team for making me think about this in their context)

Imagine, if you will, a routine administrative process that is carried out many times a day. Many, if not most, of these processes involve something along the lines of:

  • Getting some initial piece of information that triggers the process itself.
  • Confirming known information, frequently doing routine research to gather more information.
  • Summarizing that information in some formal manner – a report, a request, a transaction.

In my little example a process just like this one was experiencing wildly varying workloads from day to day. Some days they could process 15 or more, other days they would get bogged down with one. Some days they would receive a lot, other days they would receive a few. The Arrivals followed all of the queuing models – work arrived in batches, in distribution biased to the right, with a long left tail. The team was working Saturdays and long hours just to keep up, and was often getting further and further behind.

To level the workload we had to do two things. First, we needed to understand the actual demand over some reasonable period of time. We took a week since that time interval matched the kinds of deadlines they were usually under. Your mileage may vary. Based on that, we looked at how many per day they needed to get through, every day, to keep up with the demand they were experiencing. From that we established a nominal takt time of an hour.

For the cases that arrived reasonably complete, and were reasonably routine, one person could easily complete the work in an hour. The first countermeasure, therefore, was to put an upstream filter into place. The idea was that one person would be dedicated to routine transactions. The supervisor would do a quick review for completeness, and if the “routine” criteria were met, they would be placed in the appropriate work queue.

This process had a built-in check. The assumption being tested was that a complete case should take an hour to process, never longer. If a case took longer than an hour to process, it should not have been placed in the “routine work queue.” Thus, at the 60 minute mark, if the processor was not done, he kicked that one out of the work queue, back to the supervisor and started the next one.

This process immediately stabilized and accelerated the throughput on the vast majority of cases which were, in fact, routine. Everything went faster because they were no longer stopping the entire train to deal with an exception. The routine stuff went through routinely. They isolated variable processing from routine processing.

Of course they didn’t ignore the abnormal cases. There were two types of exceptions to handle.

  • The case that should have been routine, but was not because it was lacking something required to process it.
  • The case was truly an exception – something difficult or complicated, which even with complete information, requires more work than normal to be processed.

In the first few weeks, the team had a lot of cases get kicked out of the “routine” work queue. Then the numbers started to drop. This is because, each time, the team learned a little more about what causes line stops, and did a little better job:

  • Defining what they needed from their upstream processes, and making sure they got it.
  • Screening the incoming work to make sure it was set to process routinely and quickly.

What about the true exceptions? These, of course, remained. But they no longer clogged up the pipeline and stopped processing of the routine. The true exceptions were managed from a priority queue with a visual control. The other team members would pick the next one on the queue, and work it. The group’s supervisor could re-shuffle the work queue at any point, so the most important was always the next one to be picked. However, as a rule, he would not interrupt a Team Member from one case to work another.

Over a fairly short period of time, the group’s throughput went up dramatically, they were no longer working weekends and overtime, and there was far less rework involved because they were catching the reasons for rework up front.

Now, apply this same thinking to any transaction that occurs in your Health Care arena. Processing insurance claims (or other financial transaction), for example, seems like something fairly similar to this.

But here is the point: Isolate the routine from the true exceptions. Establish a routine process to do routine things in routine ways. Process the exceptions separately.

What about delivery of care?

This gets a little trickier, but I think the same basic processes apply. If you think about it, most Emergency Rooms already do this with triage. But where they fall short is in establishing routines to do routine things, and having checks in place to make sure those things are happening as specified.

Thus, even with the best of intentions, the exceptions become the norm because they are allowed to become the norm.

Let’s look at routine, scheduled, surgery. There are fixed sequences of steps to prepare the patient, prepare the facility, and prepare the team. But I would contend that, even though “everybody knows what to do” there isn’t an expectation that everybody does it a particular way. The “Who does What, When” is not part of the expected routine. Thus, people don’t expect routine things to actually BE routine, so the non-routine things that mess up the process are taken as a matter of course.

Instead, assume that a routine, smooth, consistent process is possible. Then look for what keeps it from being ideal, and embrace those little things as kaizen opportunities… then address them!

This post is MUCH longer than I set out to make it. But I think the original question gets to the very core of the work most Health Care organizations need to tackle. I am going to stop writing, and throw it out there. I apologize if it is a little unpolished.

Hopefully it will generate a little discussion.