http://bit.ly/2izQO63 In this podcast, we discuss 2 key ideas to evaluate your quality improvement system.
David Kashmer (@David Kashmer)
How would you evaluate a healthcare quality improvement program? Let’s say you’re looking at your healthcare system’s process improvement system and wondering “How good are we at process improvement?” How would you know just how well the quality system was performing?
I’ve sometimes heard this called “PI-ing the PI”, and it makes sense–after all, the idea of building a quality system even extends to learning how well the process improvement (PI) system works.
In the many systems I’ve either worked in, helped design, or have consulted for I’ve found the question of “How good are we at PI?” can often be boiled down to a matter of efficiency and effectiveness.
This dimension of the PI process can be thought of as how little waste there is in the PI process. What is the cycle time from issue identification until closure? How much paper & cost does the PI process incur? Do projects take more than 120 days?
The efficiency question is very difficult to answer in healthcare process improvement, and I think that’s because our systems are not so well developed yet as to have many benchmarks for how long things should take from identification until closure (for example). I often use three months (90 days) as the median time from issue identification to closure, because there are a few papers that cite that number for formal DMAIC projects.
Now, there are a few important statements here: (1) when I say 90 days to issue closure I mean meaningful closure & (2) if 90 days is a median target…what’s the variance of the population?
Let me explain a bit: Lean Six Sigma practitioners are often comfortable with thinking of continuous variables as a distribution with a measure of variance (like range or standard deviation) to indicate just how wide the population at hand is. Quality projects often focus on decreasing the standard deviation to make sure things go better in general. This same approach can be used to “PI the PI” effectiveness. What is the standard deviation of how long it takes to identify and close out an issue for the PI system, for example? How can it be reduced?
These are some of the key questions when it comes to measuring the efficiency of the PI system.
This dimension is, arguably, more important than efficiency. For example, imagine working really hard to decrease the amount of time it takes someone to throw something away. Yup, imagine working hard on improving how well someone throws away a piece of trash. Making a process efficient, but ultimately ineffective, probably isn’t worth your time. (I’m sure there’s some counter example that describes a situation where waste disposal efficiency is very important! I just use that example to show how efficiency can be very far removed from effectiveness.)
When it comes to measuring the effectiveness of your PI system, where would you start? Being busy is one thing, but being busy about the right things is likely more important.
One important consideration is issue identification. How does your PI system learn about its issues? Does it just tackle each item that comes up from difficult cases? How do staff highlight issues to PI staff? Is that easy to do? Does your system gather data and decide which issues are a “big enough deal” to move ahead? Does it use a FMEA and COPQ to look at factors that help prioritize issues?
These are some of the most important issue identification factors for your PI system, but by no means are the only ones related to effectiveness.
Once the right issues are acquired in the right way at the right time, where do they go from there? Are all the stakeholders involved in a process to make improvement? Does the system use data and follow those data to decide what really needs to happen, or does it only use its “gut”? Is the PI system politicized, so that data aren’t used, aren’t important, aren’t regarded, or just aren’t made?
The staff at the “tip of the sword” (the end of the process that touches patients) and even those who never see a patient but whose efforts impact them (that’s every staff member right?) are armed with data they can understand that describe performance. Even better, the staff receive data that they’ve asked for because the PI/QI process tailor made what data the staff receive. (More on that a little later.)
Once issues are identified, and the PI system performs, what happens with the output? This is another key question regarding effectiveness that can let you know a lot about the health system. There’s an element of user design (#UX) in good PI systems. Do the data get to the staff who need to know? Do the staff understand what the data mean? Are the data in a format that allow the data to impact performance? Are the data endpoints (at least some of them) something unique and particular that the staff asked about way-back-when?
Lean Six Sigma is 80% people and 20% math.
You may have heard that old saying. In fact, it’s been said about several quality programs. (I’ve discussed previously that, yes, the system is 80% people but getting the 20% math correct is essential–otherwise the boat won’t float!) It is on this point about effectiveness that I’d like to take a second with you before we go:
One of the major items with quality improvement is the ability to use trusted data to impact what we do for patients for the better.
That’s the whole point right? If the data don’t represent what we do, are the wrong data at the wrong time, or are beautiful but no one can understand them, well, the PI process is not effective.
This, to my mind, is the key question to gauge PI / QI success:
Do we see data impact our behavior on important topics in a timely fashion?
If we do, we have checked many of the boxes regarding efficiency and effectiveness, because, for that to happen, we must have identified key issues, experienced a process that somehow takes those issues and creates meaningful data, taken that data in a format that is understood by the organization, and we must have done it all in a timely fashion that actually changes what we do. That is efficient and effective.
http://bit.ly/2iigxwl This episode explores To Err Is Human, & the idea that healthcare is a decade behind other industries in some important areas.
By: David Kashmer (@DavidKashmer)
Did you know? Our field lags behind many others in terms of attention to basic safety. For those of you who focus on healthcare quality & safety, that’s probably old news. After all, the Institute of Medicine said exactly that in its To Err Is Human report…from 1999 (!)
Here’s a portion of a recent post I wrote up for TheHill.com which describes exactly that & includes a link to that report:
Healthcare is at least a decade behind other high-risk industries in its attention to basic safety.
In 1999, the IOM published “To Err Is Human,” which codified what many quality experts in healthcare already knew: in terms of quality improvement, healthcare is at least a decade behind.
More recently, a widely criticized paper from Johns Hopkins cited medical errors as the third leading cause of death in the United States. Even if you don’t agree that medical errors are the third leading cause, the fact that medical errors even make the list at all is obviously very concerning.
First published in TheHill.com
Click here for entire article: http://thehill.com/blogs/pundits-blog/healthcare/311570-3-facts-about-us-healthcare-that-wont-change-with-the
What you may NOT know is that our field lags when it comes to the adoption of other emerging trends. For example, here’s a graphic from earlier this year:
Now, all of that said, I spend a lot of time wondering exactly why we lag in certain key areas. Here’s what I’ve come up with, and I’m interested in any thoughts or feedback you might have.
(1) Using the word “lag” supposes that the direction everyone else is going is some sort of goal to be achieved or a type of race
It seems to me that the way the graphic above sets things up implies a progression or goal of digitization. In that graphic, it seems as if we are ranked in terms of progress toward some endpoint of digitization. Let’s take some time and consider whether framing the situation as progress toward some digital endpoint really makes sense.
Perhaps no one likes technology more than me. I tend to be an early adopter (and sometimes an innovator) with new devices and software that help me get done what I want to do both personally and for patients. Yes, I use a Fitbit. (Not so special nowadays really.) And I use services like Exist.io to look for meaningful correlations across things I do, such as how much sleep I get with how I perform. This system takes me no time (it all happens under the hood) and sometimes even gives me non-intuitive correlations, which are perhaps the most useful. Here’s an example of what I mean, but this one is weak and I wouldn’t do anything differently based on it:
The bottom line is, I think, every time I see a Big Data article or learn about how websites figure out things about my health that I don’t even know, well, I think we are pretty much all-in on this progression towards the digitization idea…at least I am!
So, on this one, I believe that (yes) there is a meaningful progression toward digitization across industries and, yes, I feel it’s more useful for healthcare to get on board than it is to lament where things are going or to question whether digitization is meaningful for healthcare…and I especially feel good about it when I remember the days of my training and how I used to have to hunt for Xrays on film, yet now I have the Xray or CT scan on my computer instantly!
(2) In part, we are slower to adopt because we deal with people’s health.
We don’t build cars or fly planes, really. Although certain lessons learned from other industries are very important, many in healthcare believe our service is different. Some are even skeptical of whether we should adopt tools that worked well across other industries. We work with people’s health, after all. In the United States especially, that’s a very big deal and many regard it as a true calling. So, being the careful people we are (I often wonder just how risk-averse we are) it seems to make sense to me that our field may be slower than others to adopt new things. It’s very conservative and maybe even highly adaptive to be that way.
When it comes to certain aspects of our work, like patient safety and quality, I should add here that there are well-worn tools that apply to all services–even services like ours called healthcare. We should adopt these, and unfortunately are still behind. I’ll add that adopting these tools helps us as providers even as it helps our patients. (If you’re interested in specifics, take a look at Volume to Value.)
So, bottom line here: part of why healthcare may be slower to adopt emerging trends is because we feel very strongly that only the best, well-worn, known tools should be applied to people’s health.
(3) Sometimes we are slower to adopt because much of the push to adopt has come from outside
About three months ago, I’d just finished speaking at a quality improvement conference in Philadelphia. This one had over a thousand participants from diverse companies. It really ran the gamut from Ford to Crayola to large hospitals to DuPont, and each participant was focused on quantitative quality improvement. After my talk, there were lots of questions. One really struck me in particular:
“How can you improve healthcare quality when you still get paid even when things are bad? I mean, when I make a car if there’s a quality problem and it comes back, I eat that cost…”
This audience member really hit it on the head. Isn’t it difficult to advance topics like quality (where healthcare is a decade behind) if you’re still reimbursed even when there’s a quality issue? What he’d hit on is the tension between a pure fee-for-service model versus value-based reimbursement.
I was able to tell him that healthcare is transitioning, right now, away from being paid even when there’s a quality issue to a model where reimbursement is much more focused on value provided to patients. I also shared with him that things aren’t easy, because we all have to agree on what exactly value and quality means in healthcare, but that we are getting there. We talked about how buy-in from everyone in healthcare for quality initiatives (and more rigorous, quantitative ones), I think, will increase in the next 10-15 years as a result. Sure enough, I think we can see this is already happening:
Our conversation reinforced for me that much of the quality push, and digitization push, has come from outside of healthcare. When the adoption of electronic health records and other forms of digitization are incentivized via meaningful use initiatives, and the HHS department explains that more and more of reimbursement will be tied to value-based metrics, it’s clear that a significant portion of the push to adopt emerging trends has come from outside what may be considered the typical traditional healthcare sphere.
Items that were typically hailed as improvements in healthcare, over the last hundred years, included game-changers like general anesthesia, penicillin, or the ability to safely traverse the one to two inches between the heart and the outside world with cardiac surgery. (Prior to the development of cardiac surgery, some famous surgeons had previously predicted that route would forever be closed!)
Now, especially to physicians, it can be harder to see the value in moving in these directions. Many in healthcare feel they are pushed toward them. Yes, every physician wants the best outcome for the patient, yet seeing quality as the systematic reduction of variation along with improvement in the central tendency of a population is not always, well, intuitive. Given the backdrop of the very specific, individualized physician-patient relationship, it can be challenging to understand the value of a quality initiative that sometimes seems to play to eliminating a defect which the patient in front of the doctor seems to be at low (or even no) risk for.
I’m not saying whether any of this is good or bad, and I’m only sharing what is: we may be slower to adopt these trends in healthcare because they have often come from outside. Rather than commenting on whether this is good or bad, it seems to me that the trend does explain some of why the field is slower to adopt these changes.
Having worked in healthcare for more than a decade through many venues, from cleaning rooms in the Emergency Department to work in the OR as a surgeon, I can share that yes we in healthcare are behind other industries in terms of adopting key trends. However, I believe this is much more understandable given the nature of our work that directly (and individually) affects quality and quantity of human life, as well as the fact that (for better or worse) much of the impetus to adopt these trends has come from the outside. I consider it my responsibility, and all of ours as providers, to be on the lookout for ways in which we can adopt well-worn tools that already exist to improve quality and digitization in our field. Let’s make our call to action one where we get on board with these trends for at least those aspects that we reasonably expect may improve our care.
http://ift.tt/2hNwo7L Have you ever noticed that great quality improvement projects repeat themselves across organizations? Is it because organizations share techniques? Is it that we have so much room to improve in terms of healthcare quality…
@DavidKashmer (LinkedIn profile here.)
President Obama announced Friday that more individuals signed up for insurance on HealthCare.gov on Thursday (12/15) than on any single day since the launch of the low cost Affordable Care Act exchanges three years ago.
Greater than 670,000 people signed up for coverage ahead of the Dec. 15 cut-off date for Jan. 1 insurance.
The traffic congestion caused the Centers for Medicare and Medicaid (CMS) to announce late Thursday that a new cut-off date for enrollment would be Dec. 19. HealthCare.gov handles enrollment for 38 states. Time limits for state exchanges vary, however several now permit enrollment for Jan. 1 insurance for a number of extra days.
Signups rose regularly this passed week. On Monday, greater than 325,000 citizens selected plans on HealthCare.gov. On Tuesday, more than 380,000 Americans selected plans on HealthCare.gov, marking two of the largest traffic days in HealthCare.gov history.
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!
http://ift.tt/2gdwIgQ A lesson from an OR turnaround time project: failure to plan a control phase is planning for your project to fail.
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 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
http://ift.tt/2gHpcLY Here’s a useful story of how one team improved ED throughput by walking through system and finding an unexpected delay.