Saturday, March 26, 2011

Top 3 Insights from Jim Womack on the Lean Blog Podcast

I just listened to Jim Womack's interview on Mark Graban's Lean Blog Podcast.  Really good stuff, especially the part where Mr. Womack talks about healthcare.  Here are the ideas/concepts that really resonated with me...

  1. Healthcare is not scientific.  Mr. Womack says we think of the practice of medicine as a scientific endeavor, but when you go to the gemba of a healthcare organization, you often see a highly craft-oriented culture.  Process variation between physicians is sometimes the norm, rather than the exception.   The decision to perform a process differently is often not based on outcomes data, but rather on the way the process was taught to the physician by her mentor.  Scientific, this is not.
  2. Physicians are the front-line workers.  Whereas in manufacturing the "touch labor" employee might be an entry-level blue collar worker, Mr. Womack discusses that in healthcare this role is performed by highly-trained, highly-compensated physicians.  This creates all sorts of unique situations that we must be aware of when trying to promote kaizen in a hospital setting.
  3. Nurses are the main ones thinking about process.  When I came to healthcare as a newcomer less than a year ago, I was surprised that the nurses are pretty much the ones running the show, from a process perspective.  As previously mentioned, the physicians are the touch labor employees.  Mr. Womack indicates that his leaves the nurses as sort of the stewards of the horizontal flow of patients across our processes.  Of course, nurses are also touch labor employees, so horizontal flow often gets pushed aside when the nurses have to focus on performing a touch labor task.
I highly recommend listening to the interview with Jim Womack.  He talks a lot about his new book, his approach to walking the gemba, and other insightful tidbits.  Check it out.

Friday, March 25, 2011

Measurement System Analysis for Attribute/Discrete Data

My background is mostly in Lean, so to expand my skill-set, I recently went through a really solid Lean Six Sigma training course at the UT-Arlington's Texas Manufacturing Assistance Center (TMAC).  TMAC does a great job of developing your analytical skills, and this week I got to use one of my newfound skills--calculating Kappa.

What is Kappa?

It's a score that tells us how reliable our data collection system is when the data being collected is attribute/discrete data like pass/fail, good/bad, etc.  Basically, we take two scorers (the folks who decide if something should be recorded as 'pass' or 'fail') and we have them score a sample of products twice.  We want a minimum sample size of 40, with about half being good products and half being defective products.  Once the samples are scored twice by each scorer, we then plug the results into a spreadsheet and do some calculations to get the Kappa score.

Why two scorers?  Why two rounds of scoring each?

Having two scorers lets us see scoring variation between scorers.  Having each scorer score the samples twice lets us see scoring variation for one individual across two rounds.  If the scorers are consistent with each other, we feel good.  If the scorers are consistent with themselves between the two rounds, we again feel good.

What is a good Kappa score?

When looking at the Kappa score between two scorers, if we get above 0.70 (out of 1.0), we've got a pretty good data collection system.  When looking at the Kappa score for one scorer between two rounds, if we get above 0.85 (again out of 1.0), we've got a pretty good data collection system.

How does this fit into Lean/Six Sigma and management in general?

Whether we're leading a Lean/Six Sigma project or using data to guide us in everyday management, we want to know if our data is valid.  That's what a Measurement System Analysis (MSA) is all about, and a Kappa calculation is just one way of doing a MSA if our data is attribute/discrete data.

Of course, even if we prove that our data is valid, we should never rely on data alone.  We can surely use data to point us in the right direction to where problems are, but we should always go to the gemba and check out the gembutsu with our own eyes.  Never let data get in the way of facts.

Where can I learn more?

There's a guide I recommend, The Lean Six Sigma Pocket Toolbook by Michael L. George, et al.  Starting on pg. 100, you'll see a complete explanation for how to calculate Kappa.

Thursday, March 24, 2011

Standard Work for ER Residents

As a non-clinical member of a large hospital, when I can get even 30 seconds with an ER physician, I consider myself lucky.  Today, I got about 5 minutes with one, which gave me the opportunity to throw some ideas out there about ways to standardize and kaizen repetitive aspects of his job.

The Concept

I mention 'standardize' and 'kaizen' together, because as Taiichi Ohno said, "Where there is no standard, there can be no kaizen."  Standard work gives us a baseline from which we can analyze deviations, which leads to the discovery of problems, which through good problem-solving leads to continuous improvement.  Without the baseline, we can't even tell if we have a deviation.  That's why I was discussing standardization with the ER physician today.

The Specifics

We specifically discussed standard work in the context of the Resident-to-Attending report-out.  This is the process by which a Resident (a med school graduate who is in-training) reports to the Attending (a senior physician) on the condition of a patient and what the treatment plan should be.  This is typically done verbally, which makes it critical that there be some sort of structure around the verbal report-out.

In med school, students are taught reporting structures such as SOAP that help provide some standardization to the report-out process.  If we say that the SOAP approach is our standard, we can at least check to see if it is being used and look for deviations.  If there are deviations, we can ask why and keep asking why until we get at the root cause.  If needed, we can find a better standard.  The point is, we need something to get us a baseline from which we can assess the process.

The Reason

But why do we even need to worry about the Resident-to-Attending report-out process?  Because it causes patient delays, which can cause patient safety and quality of care issues.  Until the Resident reports to the Attending and a plan of care is agreed-upon, you don't usually see any orders being placed.  No orders, no treatment.  Nurses can do their best to monitor and support sick patients, but until orders are placed it's hard to provide much care.  That's why we need the best Resident-to-Attending report-out process possible, which is why we need standard work and good problem-solving.

Of course, this whole problem makes me think, is there a better way?  Is there a different model that would allow Residents to get the training and monitoring they need from the Attending without creating delays for patients?  That's true north for the Resident/Attending relationship.

Tuesday, March 22, 2011

Hey y'all, it's Hospital Kaizen

Not sure what exactly I'm going to do with this blog, but I'm hoping to explore kaizen concepts within the context of a hospital. Should be fun.