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It’s A Little Personal…
Let me share a personal story about the important differences between how I was trained in Surgery regarding medical errors and later training in statistical process control. Here, let’s discuss some personal thoughts on the important differences between a more systemic approach to error and the more traditional take on error which includes a focus on personal assignability. I am sharing these thoughts owing to my experience in different organizations. These experiences have ranged from some organizations which seek to lay blame specifically in one person to those organizations that are system focused on error reduction at the systemic level. What are some characteristics of each of these approaches?
M&M Is Useful, But Not For Quality Improvement (At Least Not Much)
I remember well my general surgical training and subsequent fellowships and I’m grateful for them. I didn’t realize, at the time, how much of my training was very focused on personal issues with respect to quality improvement. What I mean is that, at the morbidity and mortality conference, I was trained both directly and indirectly to look at the patient care I provided and to focus on it for what I could improve personally. This experience was shared by my colleagues. The illusion by which we all abide in morbidity and mortality conference is that we can (and should) overcome all the friction inherent in the system and that by force of personal will and dedication we should be able to achieve excellent results or great outcomes based on our performance alone. What I mean is our morbidity and mortality presentations, or M&M’s, don’t focus on how the lab tests weren’t available, how the patient didn’t have their imaging in a timely fashion, or any of the other friction that can add to uncertainty in fluid situations. M & M, as many of my colleagues have said, is a contrivance. Read on, however, because there’s more: while M & M may be a contrivance, it is a very useful contrivance for training us as staff.
Consider that in the personally assignable world of the M&M conference we often take responsibility for decisions we didn’t make. Part of the idea of the M&M conference to this day (despite the 80 hours restrictions for residents) is that the resident understand the choices made in the OR and be able to defend or at least represent them effectively…even if that resident wasn’t in the OR. So from the standpoint of preventing defects, a case presentation by someone who wasn’t in the OR may help educate the staff…yet it probably doesn’t make for effective process improvement–at least not by itself.
Clearly, this “personal responsibility tact” is an excellent training tool for residents. Morbidity and Mortality conference focuses on what we could do better personally. It forces us to read the relevant data and literature on the choices that were made in the operating room. It is extraordinarily adaptive to place trainees in the position where they must defend certain choices, understand certain choices, and be able to discuss the risk versus benefit of the care in the pre-operative, intra-operative, and post-operative phase. However, classic M&M is not a vehicle for quality improvement.
In The Real World, There Are Many Reasons For A Positive (Or Negative) Outlier
What I mean by this is that we in statistical process control know (and as we in healthcare are learning) there are many reasons that both positive and negative outliers exist. Only one of the causes for a “bad” outcome is personal failure on the part of the provider and staff, and, in fact, most issues have roots in many other categories of what creates variation. This does not mean that, as a provider, I advocate a lack of personal responsibility for poor medical outcomes and outliers in the system. (I’ve noticed that staff who, like me, grew up with the focus on personally assignable error and a “who screwed up” mentality typically accuse the process of ignoring personal responsibility owing to their lack of training or understanding of the process.) However, I recognize that outcomes have “man” or “people” as only one cause of variation. In fact, as we have described previously on the blog, there are six causes of special cause variation.
There are six categories of reasons why things occur outside the routine variation for a system. This doesn’t mean that a system’s normal variation (common cause variation) is even acceptable. In fact, sometimes systems can be performing at their routine level of variation and that routine level of variation is unacceptable as it generates too many defects. Here, let’s focus on the fact that there are 6 causes of special cause variation which can yield outliers above and beyond other values we might see. As mentioned before in the blog here, these 6 causes include the 6 M’s, which are sometimes referred to as the 5 M’s and 1 P.
Which approach to error and process improvement do I favor? I favor the more comprehensive approach to error reduction inherent in the statistical process control methodology. This process is not just for manufacturing and I know this because I’ve seen it succeed in healthcare, where much of the task involved was helping the other physicians understand what was going on and the philosophy behind it.
Let me explain why there can be so much friction in bringing this rigorous methodology to healthcare. In healthcare, we are often, I believe, more slow to adopt changes. This is especially true for changes in our thought processes and philosophy. I think this is perfectly fine and is likely acceptable. This conservative approach protects patients. We don’t accept something until we know it works and it works very well. This, however, does make us later to adopt certain changes (late to the party) compared to the rest of our society. One of these changes is the rigorous approach to process control.
Physicians and surgeons may even feel that patients are so different that there can be no way to have data that embody their complexities. (That’s another classic challenge to the Lean and Six Sigma process by the way.) Of course, in time, physicians realize that we use population level data all the time and we see it in the New England Journal of Medicine, The Lancet, and other journals. A rigorous study with the scientific method, which is what statistical process control brings, allows us to narrow variation in a population without ignoring individual patient complexities. After all, we do not commit the fallacy of applying population level data directly to individual patients and INSTEAD make system-wide changes that support certain outcomes. Surprise, after only a month of experiencing the improvements, even physicians come to believe in the methods.
Also, physicians are not trained in this and we see only its fringes in medical education. This is also adaptive, as there is a great deal to learn in medical education and a complete introduction to quality control maybe out of place. However, the culture of medicine (of which I am a part) often still favors, at least in Surgery, this very personal and self-focused approach to error rate. However, I can say with confidence and after experimentation, that the systemic approach to error reduction is more effective.
Lean & Six Sigma Have Been Deployed In The Real World Of Healthcare…And Yes They Work
As a Medical Director and Section Chief for a trauma and acute care surgery center, I had the opportunity to deploy statistical process control in the real world as my colleagues and I re-bulit a program with administrative support. This was highly effective and allowed our surgical team to focus on our rates of defect production as a system. This eliminated focusing on individual differences and instead helped team building etc. It also gave a rigorous way for us to measure interval improvement. These are just a few advantages of statistical process control.
Other advantages included the fact that it allowed us to know when to make changes and when to let the system chug along. Using statistical process control allowed us to know our type one and type two error rate which is key to know when to change a system. For more information regarding type one and type two error rate look here.
There are advantages to both approaches to errors. The straightforward and often more simplistic view of personal responsibility is highly adaptive and very advantageous for training surgeons. I think that, while training surgeons, we should realize (and make it transparent) that this personal approach to error is merely a convention which is useful for teaching, keeping us humble, and focusing on how we can improve personally. After all, the surgical trainees often are in the position where they must take responsibility in a conference format for decisions over which they had no influence. They also must, again, give the illusion that there were no barriers to excellent patient care beyond their control such as multiple trauma activations at once, lab tests not being performed, and no short-staffing on holidays. Again, personal responsibility and the illusion of complete control over the production of errors is important when the focus is on education and for this reason the personal approach to error is highly adaptive.
However, when we want to actually make less defects, a systemic approach to error that recognizes personal issues as just one of 6 causes of potential defects is key as is rigorous methodology to bring about change. Being able to quantify the common cause level of variation and special causes of variation in a system is a very useful tool to actually make less defects. As statistical process control teaches us, prevention is the only portion of the cost of poor quality that has return on investment. For more information on the cost of poor quality, visit here.
Personal Responsibility Is One Part Of A More Comprehensive View
At the end of the day, I view personal responsibility for medical error as just one portion of a more comprehensive view on error reduction, risk reduction, and true quality control. As a surgeon, I strongly advocate personal responsibility for patient care and excellent direct patient care. This is how I was trained. However, I feel that, although this is key, my focus on how I can do better personally is part of a larger focus that is more comprehensive when it comes to the reduction and elimination of defects. Statistical process control gives us a prefabricated format that uses rigorous mathematical methods to embody and allow visualization of our error rate. Other differences from the more classic model of process improvement in healthcare include that statistical process control tends to degenerate less often into a pejorative discussion than the personal focus approach.
Unfortunately, I have been in systems previously where staff are overly focused on who made an error (and how) while they ignore the clear issues that contributed to the outcome. Sometimes, it is not an individual’s wanton maliciousness, indolence, or poor care that yielded a defect. Often, it’s that there was friction inherent in the system and the provider didn’t “go the extra mile” that M&M makes us believe is always possible. Sometimes it is a combination of all these issues and such non-controllable factors such as the weather or similar issue.
The bottom line is, at the end of the day, statistical process control as demonstrated in Lean and Six Sigma methodology allows us to see where we fit in a bigger picture and to rigorously eliminate errors. I have found that providers in the systems tend to “look much better” when there has been this focus on systems issues in a rigorous fashion. Outcomes that were previously thought unachievable become routine. In other words, when the system is repaired and supportive, the number of things we tend to attribute to provider defects or patient disease factors substantially decreases. I have had the pleasure to deploy this at least once in my life as part of a team, and I will remember it as an example of the power of statistical process control and Lean thinking in Medicine.
Questions, comments, or thoughts on error reduction in medicine and surgery? Disagree with the author’s take on personal error attribution versus a systemic approach? Please leave your comments below and they are always welcome.