Great Healthcare Quality Projects Repeat Themselves


David Kashmer, MD MBA MBB (@DavidKashmer)

As healthcare adopts more and more of the Lean Six Sigma techniques, certain projects begin to repeat across organizations.  It makes sense.  After all, we live in the healthcare system and, once we have the tools, some projects are just so, well, obvious!

About two years ago, I wrote about a project I’d done that included decreasing the amount of time required to prepare OR instruments.  See that here.  And, not-surprisingly, by the time I had written about the project, I had seen this done at several centers with amazing results.

Recently, I was glad to see the project repeat itself.  This time, Virginia Mason had performed the project and had obtained its routine, impressive result.

This entry is to compliment the Virginia Mason team on their completion of the OR quality improvement project they describe here.  I’m sure the project wasn’t easy, and compliment the well-known organization on drastically decreasing waste while improving both quality & patient safety.

Like many others, I believe healthcare quality improvement is in its infancy.  We, as a field, are years behind other industries in terms of sophistication regarding quality improvement–and that’s for many different reasons, not all of which we directly control.

In that sort of climate, it’s good to see certain projects repeating across institutions.  This particular surgical instrument project is a great one, as the Virginia Mason & Vanderbilt experience indicate, that highlights the dissemination of quality tools throughout the industry.

Nice work, Virginia Mason team!

Warning: Will Your Quality Improvements Really Last?

David Kashmer, MD MBA MBB (@DavidKashmer)



OR turnaround time is a classic opportunity for quality improvement in hospitals. The surgeons typically say it takes way too long to clean and prepare the ORs.  The materials management and housekeeping staff often add that they’re doing everything they can to go as quickly as possible–without sacrificing their safety or doing a bad job for the patient.  Anesthesia colleagues may add that they too are going as fast as possible while completely preparing the rooms and maintaining patient safety.  However, the rest of administration will remind the team of an estimated cost of OR time so as to put a face on the costs associated with that downtime when no one is operating in the ORs.  I’ve seen these range from as low as $50/minute to as high as $100/min!


Here’s a classic quality improvement project


Here, then, is a classic project that involves many stakeholders,  shared OR governance, and an obvious opportunity to decrease what many hospitals consider non-value added time (VAT).  I bet it’s a project that your healthcare system has performed before, will perform soon, or is eyeing as a potential for significant quality improvement.

And you know what?  Even if you’ve gotten this challenging project done in your healthcare system, the issue may not be behind you my friend.  Let me tell you why…

Once upon a time, at one hospital, the goal of an important quality improvement project was to reduce that turnaround time in the operating rooms.  And wow had it ever worked!

The team had adopted a clear definition of turnaround time, and had used a DMAIC project to significantly decrease that time–it was almost like a NASCAR pit crew in there.  It was safe, orchestrated, complete, and really helped the rest of the staff improve OR flow.  The time required to turnover a room had also become much more predictable, and this decreased variation in turnover times was also a big help to patient flow and scheduling.

The team used several classic tools, including a spaghetti diagram to decrease wasted motion by the “pit crew” team, a kanban inventory system, and a visual control board to notify all of the players in the process (Anesthesia, Surgery, Pre-op Nursing, & the holding room) when the operating room was ready to go.  They saved days worth of wasted motion (time spent walking) for the OR prep crew when projected out over a year’s worth of turnovers.  The OR staff could complete about one extra case per room per day.  Truly amazing.

…but only three months later, the turnaround time had crept back up again to where it had been before the changes–a median of 25 minutes per case.


Good quality projects never die.  And if you plan them right, they don’t even fade away.  –Anonymous


Nobody noticed, at first, that the turnaround times were slowing down from great to just pretty good again, until one day the OR got very backed up because a couple of turnarounds took 40 minutes. The Chief Surgeon wasn’t happy and didn’t hesitate to tell anyone she could how she felt.

What had kept the gains from being sustained? (You’ve probably seen these culprits before.) It was a combination of factors. Two new people started in the OR; one longtime employee in the facilities-services department had retired. The new people weren’t educated all that well about the turnaround system, and they also didn’t know exactly where everything was yet.  But that wasn’t the real problem.


Failure is much more likely when there’s no control plan


In fact, the quality-improvement team hadn’t built a control plan into the system. The first sign they may have had a problem was when the Chief Surgeon fired off an angry e-mail to the rest administration and most of the staff.  The signal should’ve come much earlier, when the variation in turnover times increased unexpectedly.  That signal could’ve been noticed weeks before.

How?  The team could’ve used an ImR control chart (more on that here) to notice that the range of times for room turnover had gone out of control.  The team could’ve had someone, a process owner like the OR administration, positioned to sound the alarm that the process needed to be solidified when, weeks earlier, several other turnovers took an unexpectedly long time.

Fortunately, in this case, the project team recovered.  They quickly deployed an ImR chart and also reviewed their data.  The Chief Surgeon had been correct:  yes, those cases did take an unexpectedly long time when viewed in the context of the OR’s data.  A root cause analysis was performed and the quality team quickly realized that several issues lined up to make those times take so much longer.

After addressing the issues, the team was back in full swing only a week or two later.  The pit crew was back at it, and the NASCAR-like precision had returned.


The take-home


The lesson:  creation of a control phase plan to maintain the good work you & the team have done is an essential part of quality improvement projects.  Without an excellent control plan, it is very difficult to maintain the improvements you’ve made as a foundation for future improvements.  Failure to plan a control phase is, unfortunately, planning to fail.


Excerpt originally published as part of Volume to Value:  Proven Methods for Achieving High Quality in Healthcare

Coming Soon: We’re Going From Volume To Value

By:  DMKashmer MD MBA MBB FACS (@DavidKashmer)


Yup, Healthcare is going through a major transition and we all know it.  Whether you’ve followed along with the blog, or even if you haven’t, you probably know that Health & Human Services is transitioning us to a focus on value delivered to patients rather than volume of services we deliver in healthcare.  If you haven’t heard exactly what’s coming, look here.

So, in order to help prepare, I’m sharing tools and experiences with quality improvement that lead to improvements in value delivered to patients.  Take a look at Volume to Value, coming soon on Amazon.

Now, more than ever, a clear focus on well-known quality improvement tools is paramount for success.


Did You Know Lean & Six Sigma Studies In Healthcare Are On The Rise?

By:  @DavidKashmer

Whew!  Finally!  I’ve been waiting for some years now for our healthcare system to start to widely adopt standard, well-known quality improvement tools.  It seemed like many new quality articles I read concerning the healthcare system frequently invented some new way to look at quality.  You’ll find multiple blog entries on here where I implore our healthcare colleagues to start to use well-known quality tools instead of re-inventing the wheel.  Here’s one now.


Well, thanks to our colleagues at Minitab, we have some evidence that, in fact, the use of Lean & Six Sigma techniques is catching on in healthcare.  Look here:

Lean & Six Sigma Techniques trend plot from the Minitab blog (
Number of Lean & Six Sigma studies in healthcare trend plot from the Minitab blog (


What a great visual!  Now we see how the number of studies per year is increasing, and we can sense how 2015 demonstrated quite a jump in the number of Lean & Six Sigma studies.  Time will tell if the rate of increase in number of studies per year has significantly changed.


At the end of the day, here, we see evidence that Lean & Six Sigma techniques are catching on in healthcare.  It’s no surprise, as the transition from volume to value helps healthcare focus on proven techniques to make measurable, and sustainable improvements.  Healthcare colleagues:  here is the call to action to learn and use the standard techniques of Lean & Six Sigma.







Do You Know How To Represent Patient Risk?

By:  David M. Kashmer MD MBA MBB FACS (@DavidKashmer)


Different Ways To Represent Risk


There are several approaches to the management of risk in your healthcare system. When we hear the words “risk” and “risk management”, we typically think of some of the legal ramifications of work done in our hospitals across the country every day. However, there are some other ways to quantify risk. For example, what if we were trying to represent the risk for a given patient entering a given system in our hospital or healthcare system? Well, how would we go about doing that? Today I am going to share with you some tools to demonstrate the risk for a certain outcome for patients as they enter whatever system you define. For example, what if you wanted to quantify the risk of a given patient who enters your emergency department and has to wait really more than 7-10 hours in your emergency department to get to their final destination? How would you represent that risk? Would you do it on a case by case basis where you review those cases that just really seem to take too long? Would you just review those egregious cases and make changes based on those? Would you review routine cases where the patient only took maybe four hours, especially is four hours is the most routine value that your system offers up? How would you go about demonstrating and representing patient risk for waiting a long time, whatever a long time may be by your definition, in your emergency department? Well, there are several techniques to do this and today I’m going to share with you some of the ones we use routinely and a way to demonstrate the full spectrum of risk and to do it in a clear way.


The Podcast In One Word:  “Width”


So, if we had to sum up today’s podcast and tool in maybe one or two words, we would use the words range or dispersion or width. Now, let me explain exactly why we use those terms. Also, let me direct you to the video version of our podcast. For this particular entry, it’s going to be especially useful to see some graphs and charts of patient outcomes. So, lets return back to this example of a patient who enters your emergency department and you are trying to manage the risk of them waiting too long. One of the key tools of Six Sigma, as developed and put together by Motorola and other groups, is that it can apply to really not just manufacturing processes, but also services like ours in healthcare. The tools work very well because all they are there to do is represent our data and to represent it in a way that is clean and intuitive. So, one of the ways to manage or to think of risk in your system for a certain outcome is that width of the curve that demonstrates your systems performance. So, what I mean by that is, let’s pretend we make a histogram of the number of patients. Okay, so just this bar graph of the number of patients who take zero minutes. They come in the door and they see a doctor right away, and then we add to it the number of patients, on the same graph, who wait maybe five minutes. There would be a few more of those and the bar would be a little higher, and keep doing that for patients as they enter your system.


Now, we won’t get into specifics of sampling in this entry, but there are ways to get a sense of how big a sample we need to adequately characterize our system, but let’s say we’ve done that, and for more information on sampling you can visit here. That’s our healthcare quality blog. You can go there and search for sample size and it will give you the very straightforward ideas on how to figure out if you have a large enough sample to demonstrate what you’re looking to demonstrate. So, we make this curve and this curve will be a curve to demonstrate our performance. This will be a histogram demonstrating the number of patients that took different amounts of time until they see a doctor. On the video version of this podcast, I’ll show you, very straightforward, a way to do that in Minitab or a similar program. There are lots of options for software packages that can do this. Minitab is a great one to do it, Sigma XL is another option, and that second one is an excel plug in. However you do it, making this curve will demonstrate your systems performance. We’ll make one and put it on the video version of the blog and walk you through it. To find that, you can go to our YouTube channel, and that YouTube channel is under The Surgical Lab. You can find us there. We’ll put a link to that under the Healthcare Quality Podcast, so you can follow through our links and find the video version of the blog if you choose to do that.


So, once we’ve made a curve, a histogram that demonstrates how our system runs, there are certain characteristics of it which we’ll talk about in another blog entry that includes whether this curve is normal distribution, whether these data follow the normal distribution, or whether they follow something else, but for this example all we care about is the full width of that curve because that width of the curve, that dispersion of data, that range of data, demonstrates the risk that any particular patient entering our system experiences. So, what’s interesting about that is it is a clear, rigorous way to demonstrate that a patient coming to our emergency department may experience one of these values and the wider that curve, the more at risk they are. If the curve was very narrow and all values fell within a given smaller range, well then we would say, “these patients, their risk is less”, because they are going to have one of these sets of values much more likely than this broader range of values. So, that’s part of the idea of statistical process control. It is controlling the width of this curve with the variance, which is a very clear way demonstrating that variance, that width, that range, it’s a very clear way to embody patient risk. So, it follows a narrower, tighter curve and is less risk for your patients. It’s a very straightforward way to do this and to clearly define and to clearly demonstrate risk to patients over the breadth of values in your system, rather than trying to mull through on a case by case basis, what we intuit puts our patients at risk. Let me share with you some of the rest of the power of this approach.


If You’re Able To Fit Many “Widths” Of The Curve Between The Upper & Lower Spec Limit…That’s Good!


Let’s pretend that your organization by policy or good medicine or what you think says, “okay, we don’t think it should take any more than six hours for our patients to come to the ER and leave and reach their final destination”. Let’s say your value is six hours. We can call that an upper specification limit. In this case, it’s one that you set for your system, but in other cases we’ll use the voice of the customer, how long the patient feels it should take. Now, often in healthcare the patients really don’t have a sense of how long it should take, but there is still often a lot of value in asking what they expect, especially for other systems, but let’s say in this case, however you establish it, you say the upper spec limit is six hours. Well, any value above six hours is a defect, it took too long, and it doesn’t mean anyone in particular did anything wrong, as you know, we have talked about the six causes of special cause variation and the multiple factors. Sometimes in healthcare we use the Swiss cheese model where we say, many holes have to line up to produce the defect, but whatever it is that you use for your concept of why defects occur, anything greater than this upper specification limit, well that’s a defect. Now, the wider your curve between zero minutes, the patient shows up and sees the ED doctor right away, and above the upper spec limit, six hours, the wider that curve the more at risk a given patient is to experience a value over six hours, in other words to have a defect. So, again, risk is the width of your performance curve versus your upper specification limit and your lower specification limit if you have one, in this case that’s zero because it’s almost challenging to imagine a situation where it’s too fast. The patient comes in, sees a doc, gets to where they’re going right away. So, in this case the lower spec limit is zero. My point is, again, with the curve variants it demonstrates clearly the risk to your patients in your system. So, the whole idea of Six Sigma is to fit many widths, entire widths of this performance curve between the lower and upper spec limit. Sigma is just a term for standard deviation and standard deviation is an indicator of the width of the curve or a measure in part of variants.


We won’t get into the specifics of standard deviation here, it only applies to normal distributions and not all of these curves are normally distributed. The standard deviation is not a full width of the curve obviously, for those of you who enjoy statistical process control, but it’s an indicator of variants and ultimately related to the width of the curve that we’re talking about.


So, Six Sigma is this idea that we want to try to fit multiple widths of the curve into this acceptable range of values, and that a good process is one that looks like you can fit six standard deviations, six of these sections of variants between the lower specification limit and the upper specification limit, in short, drastically reducing the amount of the potential for defects experienced by a patient. So, that’s where the term comes from. So, I hope you’ve found this useful today as a way to measure risk in a clear way because we discuss this all the time in healthcare, we talk about all patient risk and this patient is at risk… there are some very clear ways to demonstrate, when we look ourselves squarely in the eye at our performance, and to keep us together as a team by using our data as a team to demonstrate our systems performance. One of the ways to do that is to generate this curve, this histogram that we’re happy to show you in the video podcast, whether it’s from Minitab or another programme, that makes us look at ourselves squarely in the eye and say, how do we perform versus our upper specification limit and our lower specification limit. Again, the width of that curve indicates the amount of risk a given patient has when they enter our system for having a bad outcome. I hope you found this useful today. If you have any questions, please get back to us on the podcast’s homepage, which is


I have really enjoyed hearing from you, from people all around the country who share new statistical process control, the tools of LEAN and Six Sigma or others, and I’ve really enjoyed interacting with you. So, please, get in touch with us anytime, ask your questions, and if you’re curious about using statistical process control tools in your healthcare system, get in touch any time. Have a great day.

Here’s How Bad Data Affects Your Bottom Line



By:  David Kashmer, MD MBA MBB (@DavidKashmer)

LinkedIn Profile here.


Hello, and welcome to the Healthcare Quality Podcast.  My name is David Kashmer and my background is as a Lean Six Sigma Master Black Belt.  I am also a surgeon and an MBA, and my passion is data; data collection and using data to improve quality in healthcare.  Today I wanted to talk with you about data fidelity and certain thoughts on data quality.


40% Of Your Company’s Data Is Probably Inacurate


It turns out when we look at data by the numbers, approximately 40% of all company data is found to be inaccurate.  This is by halo business intelligence as seen on Data Science Central.  About 92% of businesses admit that their contact data is not accurate and about 66% of organizations believe they are negatively affected by inaccurate data.


Seems Like A Bigger Problem In Healthcare


In healthcare, experientially, our numbers are much higher.  Routinely when we go to pull charts and data, well, data fidelity and validation is a big problem.  One of the questions you may ask yourself is, now that we’re looking at just how good our data are, does this impact our businesses bottom line?  How does this impact our business, whether we’re a hospital or some other aspect of industry?  Well, it turns out there is evidence about what happens with a data fidelity or data quality initiative per  There’s a link to this article at our blog, and that’s  If you go there, you’ll find more information on data quality under an entry called 17,000 men are pregnant.  We’ll get to more on that in just a moment.


Again, it turns out that data quality initiatives show large changes in business end points, including 10-20% reduction in corporate budget, about a 40-50% reduction in IT budget, and 40% reduction in operating costs.  Increases are typically seen according to Data Science Central in both revenue and sales for industries where those end points are more applicable.


Dirty data can be damaging.  For example, the title for that blog, 17,000 men are pregnant, comes to us from the fact that due to incorrectly entered medical codes in certain British hospitals, thousands of men appear pregnant and seem to require obstetric and prenatal exams.  Those errors caused disastrous results in billing claims and compliance per the century at  So, there are a lot of factors that go into quality data, and having quality data, recording it and making it accessible and useful.  Again, experientially, this is something we teach and talk about when we talk about the use of statistical process control in our hospitals.


How Do We Fix This Problem?


Let me tell you how we do that.  One of the main focuses when we teach and work in quality in hospitals is to get data directly from the process.  When I say directly from the process, I don’t mean get data from a data warehouse the next day or query or registry for data.  Those things are all typically what we do.  We have registries and it’s great to have them, but it turns out it’s a lot more valuable to go to where the process is occurring and collect continuous or discrete data, depending on how you’ve set up your particular data collection plan, but to go right to the process and to collect those end points.  For more information about continuous versus discrete data, you can visit us on the blog,, and also where we talk about discreet versus continuous data.  The point here is, whichever data end point you use, focus on getting the data directly from the process at the point the process is occurring and doing so in a prospective way is key.  This is because we see that by the time data leaves the process, gets into the registry that you’re using, a lot of different things happen.


First, the operational definition for the end point you want to look at, the one that has meaning for your quality improvement project, doesn’t always line up with what the registry asks or wants.  So, because we know so well that often definitions, often fields that need to be entered, often those things don’t line up.  We focus on going right to the process and collecting data.  Now, there are a lot of challenges in that and one of them is resources.  Typically, what we hear in hospitals I’ve helped out with, hospitals where I’ve worked in the past, one of the things is, “boy, staffing to collect data is very challenging”.  It’s really just not valued.  Hospital staffing, a great amount of the costs to run a hospital comes from labour.


If you agree that approximately 60% of hospital costs are labour costs, and that’s broadly speaking what it is across organizations, it’s very challenging to make the argument for why you should have an FTE (full time employee) or a part time employee go to the place where the process is occurring and collect data.  It’s hard to make that argument, but I think you’ll understand based on the numbers we just shared about how data fidelity and poor data impacts our business end points.  I think you can agree now that it’s very worthwhile to have the best data you can.  If your decisions are based on data and you run a very data driven shop, you can probably intuit that its key that the data we use are accurate.  So, if you think that it’s too expensive to collect good data, well you’re likely incurring the costs and expense of not having good data and that tends to be much more significant than you anticipate.


Again, as noticed that when data quality projects are done, projects that focus on the quality of what we put into our registries or what comes to us in a timely fashion to make decisions, well in those projects we see again reductions in corporate budget of 10-20%, IT budget reductions, operating cost reductions, and we see increases in revenue.


So, for today’s entry, I wanted us to talk just a little bit about data fidelity and how it impacts our bottom line.  Again, a lot of what we talked about can be found on and there is a link to this article.  You can find this article with the link at, and we have a little gloss on it and then a link to the article.


Again, if you think it’s too expensive to collect good data, well you should try not collecting good data because that’s a lot more expensive.  So, again, in summary, we just wanted to highlight for you all today some of the really dramatic costs associated with bad data.  Again, our advice and my advice from having done many quality improvement projects over the years, and a typical teaching in healthcare quality improvement projects is go right to the place of the process you’ve teased out.  Go right to it, take the stopwatch, clipboard or what have you, and take a look at it.  Take a look and collect your data right from the process.  It won’t be as cleaned as the registry may make it, it won’t be fraught with the challenges of taking the operational definition that you want to look it and somehow shoehorning that into what the registry wants.


So, good luck with your data collection and your quality improvement projects, and if you have any questions or stories about the use of data in your healthcare system, whether it be a success story, a question about how to have a success story, or a warning for other data users out there, feel free to visit us at and share your experiences.  We are always happy to hear.  Have a great day!




This One Technique Aligns Your Healthcare Culture With Outcomes You Want

By:  David Kashmer MD MBA (@DavidKashmer)

LinkedIn profile here.



Hello, and welcome to The Healthcare Quality Podcast. My name is David Kashmer. My background is as a surgeon and MBA, and also a Lean Six Sigma Master Black Belt. I have a special interest in quality improvement in gamification and today I’d like to share with you some of the interesting facts about gamification in healthcare. These are those things about what you should know about the up and coming field of gamification and what it means to us in healthcare as providers and participants.


Why Bother With Gamification?


First, why bother with gamification? It turns out in America there is an engagement crisis. More than approximately $500 million per year in revenue is lost to the fact that employees are not engaged with their jobs. Gallop and Deloitte report that approximately 70% of American workers are either disconnected emotionally from their work or are actually actively seeking to hurt their company. To me, that was a sobering statistic when I first learned about it. It shows that there is a huge opportunity not just regarding things that are obviously lost owing to lack of engagement, but to other issues and missed opportunities that we see in healthcare and other industries owing to lack of engagement.

It turns out the crisis seems to extend across America and it’s insidious. Meaning, it’s just very challenging to tell engagement and to quantify engagement. So, this happens in ways that are difficult to perceive. Now, one of the solutions to this is the technique of gamification and that’s the application of strategies, tools and techniques from the gaming world, ones we more typically see in computer games, board games and other game situations, and using those to help inspire, motivate and engage staff.


An Example Of Gamification Used In Healthcare


So, here’s a story about how I’ve helped use gamification previously. Once upon a time there was a section of surgery and it was attempting to engage residents in dramatic culture change, and there were certain mission critical issues that were not being realised or brought to completion, and these changes that were trying to be made in the system did not translate easily into the everyday behaviours for residents and attending staff. So, what we went ahead and did is set up a game system, and there are several techniques that can do this. There’s something called the gamification canvas, which is a play on the business model canvas from Alex Osterwalder, and the gamification canvas, again an adaptation of Alex’s work, to the gaming world is a one-page way to design an environment that leverages game techniques. Now, these techniques especially resonate with Generation Y and that’s what we saw when we did this. We used the job satisfaction survey which was a validated survey used in healthcare to clarify how people felt about their jobs. We used that and then deployed these techniques and rechecked the Job Satisfaction Survey after. (More on the experience here.)

Now, of course, these studies have limitations, but we saw significant improvements from the pre-deployment state until the after deployment state. So, for us, it made a big deal. It made a big impact on what we did every day. We could see that experientially and the Job Satisfaction Survey indicated that the staff seemed to like it a lot better. So, for both attending and resident staff, we seem to make a statistically significant and experientially a difference that we could see every day.

So, I’m sharing with you that story to tell you some of the positives I’ve seen on gamification. I want to share a negative. We learned that using the word ‘gamification’ in healthcare had a certain unexpected connotation to it. When staff hear gamification they say, “oh, are you going to turn my education or my job into a game?” and clearly that’s not the intent, but I did want to share with you that that is a common question that we get. So much so that there are other ways to talk about the system, like an engagement project. So, we may call it the surgical engagement project or something similar, because again the idea is to do something, do anything to alleviate this engagement crisis that we typically see.

So, we had seen how different philosophies of care were circulating in the department and it was challenging to align our culture, and that gamification seemed to make a difference for us. So, gamification is the use of game dynamics, techniques and themes to improve staff engagement, but one of the most commonly used techniques includes points, badges and leader-boards.


Gamification Is MORE Than Just Points, Badges, & Leaderboards


This is often called PDL’s. Points can be awarded for certain actions according to what the designers feel are important, badges highlight special achievements and levels reached by the participants, and a leader-board uses peer benchmarking and peer motivation to help participants understand where they are relative to others in their group.

Now, each of these techniques can be used in a certain way that is more valuable. The leader-board can be used so that staff know who they are in the leader-board, but who no one else is. So, you can do anonymous peer benchmarking and we found that to be much more useful. Under points, we also found it useful to have the participants in the system be able to evaluate the people who set up the system, whether that’s having a parallel system for administrators where they’re evaluated, or some mechanism to give feedback. We’ve also found it to be more valuable when the group participating sets out what events or what abilities or what rewards are unlocked at different levels of attainment for points. It’s very valuable for them the participate in that.

It turns out these are three of the most common techniques used in gamification, but they are by no means the only three. The gamification process is much more robust than simply points, badges and leader-boards. There are other dynamics, like an appointment dynamic where showing up at a certain time for a certain event recurrently garners points. So, there are all sorts of different ways to set this up. So, PBL’s may be some of the external signs of gamification, but there are other important techniques. We talked about the appointment dynamic and there are several other dynamics that can typically be used.

Another very positive one is attaining mastery or unlocking new skills. Sometimes this gets called levelling up, but it’s a way to do competency based skill attainment to demonstrate that when you’ve reached a certain number of points for doing certain things, you are then evaluated as competent to do something new. Like for surgical residents, clear the cervical spine for traumatically injured patients, or place central lines with supervision, but not supervision with staff physically in the room at the start of the case. There are all sorts of things, there’s a spectrum of what can be done. My point is that this attainment of mastery is a powerful motivating dynamic and this levelling up is part of that and is really key.


Particulars Of Scoring In The System


One of the particulars is how scoring is conducted. I won’t get into the nitty gritty of how scores are allotted, but we have several sort of rules when we’ve done this before and one of them is that points can only be given and can never be taken away. It keeps it very positive and very focused on doing things in a positive way that are rewarded. So, points can only be given. Another issue is how points are given, the actual process of doing it. One of the ways is to use a leaderboard as part of a website, and here’s an example of one, with these participants, and these are the levels at which new things are unlocked, and then a simple interface allows submission of scores for the people who are giving out the scores. We can talk about specifics of ways we do things, like prevent scoring the same issue twice etc. There are lots of ways to do that, and if you have any questions about specifics, feel free to get in touch. I’ll share an email address with you at the end of our talk.


Not Expensive To Do


Gamification can be very inexpensive to deploy. A website for $100-200 is not even necessary. There are other techniques like using your own internal email system, for example, and again this system can be very inexpensive to deploy. It doesn’t need to cost tens of thousands of dollars, and again, techniques like the gamification model canvas help you design your particular system and use certain techniques that work well with what you have.


Closing Thoughts


So, in summary, gamification is a powerful technique or group of techniques that allows systems to align with culture, and we do that for quality reasons. It can really change how a system or a healthcare workplace aligns with different initiatives. One of the other important things that we didn’t mention, but should be mentioned here, is that these techniques resonate much more with generation Y and subsequent generations. They are much more used to being digital natives or experiencing the world through the lens of gaming, and it’s a very powerful technique to help motivate, especially generation Y and we think likely the generations that follow.

So, I share that gamification is often inexpensive and is pointed to an engagement crisis that we see across the United States. If you have any questions, feel free to contact me. Here is the email address, and I’m happy to discuss gamification with you. Also, you can find more techniques about gamification and more specifics at the blog, which is, where we have tools, tips and techniques on gamification in several entries. So, thanks so much for your attention today, and if you have any questions, please get in touch.



Here’s How To Deal With Non-Normal Data

By:  DMKashmer MD MBA FACS (@DavidKashmer)

LinkedIn Profile here.

Have you ever wondered how to work with non-normal data sets?  Data that are not normally distributed can prevent special problems, and this podcast helps explain how to deal with that special situation in healthcare quality improvement.  Audio podcast version here or click the icon above.  Video podcast version here.