We ALL make Mistakes

 

Regardless of age, gender, culture or identity, all people at some point will mess up... we ALL make mistakes.  Rarely are they a conscious act for venal reasons.  They almost always come from common conscious distractions, unfortunately usually at the exact wrong time.  Most commonly they occur usually at home, but sometimes they happen at work, and in the exact wrong situation. 

Most mistakes happen where people spend most of their time, which is at home, or for those of a middle age, while at work.  Most are the consequences of inattention and distraction factors, such as in moody moments, or while rushing, or under interpersonal complications, or other external distractions, or moments of stress.  Many are a result of a compulsive need to multitask.

You get my point…  stuff happens, especially when we set ourselves up for risk and failure

People who look at this topic in a somewhat sciencey sort of way say that most of the time we are oblivious to our goofs, although sometimes, at a certain level of consciousness, we trigger a cerebral recognition response that will alert us that we messed up.  Apparently there is a subset that may be more likely to que into this response.  Some studies suggest that women may be more likely to atune to the trigger and more likely to seek confirmation

Many errors have some  things in common.  Most goofs are irrelevant or at worst inconvenient. Sometimes, albeit rare upon rare, they end up with tragic consequences with serious injury or worse.  ( consider daydreaming while driving!!).

It is difficult to find objective information on the frequency of work related errors because the situation to count them does not come up.  The closest we can get to objective monitoring is in those fields where people are required to participate in  objective Proficiency Testing.  We do this in most types of laboratories, as well in industries such as textiles, and ship building, and working with concrete and steel, and coloration, and electrial conduction.  (Consider what happens when a bridge is built with faulty concrete and the bridge falls down!!) In medical laboratories we can see that hands-on laboratory errors occur in most disciplines at a rate of about 1 percent of testing, which sounds pretty good, until you consider that in the United States there are about 14 billion tests done per year!  (United Kingdom- around 1 billion and Canada about 100 million). That accumulates to a lot of medical laboratory errors!!!  The good news is that near 100% of laboratories have to participate in proficiency testing, so you can get a fairly accurate count of errors. 

In other health disciplines, with so called "ocult observation" which means that a person is sitting at a desk and working, but what they are really doing is observing who is washing their hands.  As it rurns out hand washing at its best is usually at 50 percent.

Some self-reporting systems also exist where people who recognize and report a self error can be useful indicators, but only when the people involved actually recognize and report their error.  Clearly the workers need to have a high level of confidence that nothing bad will happen by choosing to report by entering their information. This tends to make the self reporting systems a lot less reliable.

But here’s the bigger (biggest?) problem… Most errors reported as laboratory errors (somewhere near 70% plus) occur long before the laboratory ever touched the sample.  These are called “pre-examination errors which means the error occured  before the sample got to the laboratory.  Sometimes the sample came from the wrong patient, or was collected incorrectly or was put into the wrong container, or were put in the wrong storage place, or was mislabled or transport incorrectly, plus, plus, plus (Lin Y, Spies NC, Zohner K, et al. (2025) "Pre-analytical phase errors constitute the vast majority of errors in clinical laboratory testing."  The point is the sample may go through a proper testing process which may still be wrong.

It is difficult to envision  a  way of detecting or preventing  these problems (errors) before a wrong result is delivered.  Perhaps in the going forward future, samples will be collected by informed AI driven robots that will reduce error collection and transport much closer to zero.  But this is not going to happen tomorrow.

That’s not to say there have not been some improvements in error prevention in healthcare.  Over the years the frequency of in-institution medication errors has dropped since first being reported in 1999 by introduction of computerized physician order entry and Barcode Medication Administration both of which remove people from the loop.   One the other side the number of falls related injuries in elder long-term care has decreased by the introduction of STEADI (Stopping Elderly Accidents, Deaths & Injuries), programs which has added more people into the loop.

If I am trying to make a point (and I am!) let me say that in an area that I know something about we have many, many, many signs of error. Healthcare is replete with error, most of it unconscious and unrecognized… hands that don’t get washed, samples that are collected incorrectly, testing that is not done correctly.  Something has to be done to finally start turning these around.   

If we look at reporting on these sorts of errors, there is little evidence that reporting on any these sorts of errors results in negative repercussions.  

So will healthcare organizations ever successfully address the constant but unmeasurable  internal errors in a meaningful way?  Certainly not today or tomorrow, but today I am more optimistic than I was several years ago.  

As long as we have humans being asked to complex procedures,  the odds of error free healthcare is probably unlikely.

 But with human ingenuity and better  collection and monitoring systems, we might be more likely  to get closer to error free healthcare, at least until we reach a crisis of insufficient working robot batteries. 

NEAR MISSES!!!

 

ISO 7101:2023 requires actions with respect to near misses, without providing a specific definition.  One can find a variety of workable definitions, most of which are similar to the World Health Organization (WHO) that states: “an error that has the potential to cause an adverse event (patient harm) but fails to do so because of chance or because it is intercepted”.   The frequency of near misses is usually indeterminate because if you were unaware of it its existence and similarly unaware of any impact, then it becomes essentially invisible… until it is too late. 

But let me tell you about  near misses that I see, not in healthcare, but closely related. The reason that I think this is relevant is because it is one of those instances where one can actually see, monitor and count near-miss  instances.

I live in a large city with many tourists.  To accommodate, the city provides  “rent-a-bike” stations all over the city.  A station is a rack of bicycles locked in stalls that can be opened with a credit card swipe.  The person picks their bicycle, swaps their card and then backs bike out of its stand and rides away.  It takes maybe 2 minutes. 

There is one across from where I live, so I get ample chance to sit and watch on any given day 2-10 events.

Unfortunately this stand is on the side of a high traffic road  and every day I seem many bicycles being pulled out just as a car goes by with the potential accident being dodged by milliseconds or millimetres.  Not all the renters are oblivious, some, maybe many, look around before pulling out the bike, but on any given day, it does not take a long time before I see a near collision in the making.   

To date I have probably seen well over 50 (maybe 100) near misses,  fortunately no hits…  yet.  Sometimes I have a chance to chat with the cyclist before the ride away.  One or two might respond with some surprise, but the rest are oblivious and are happy to just ride away.

What disturbs me is that what I am seeing is not something like a minor inconvenience.  These are events that when things do go wrong, someone is going to be hurt…. probably very badly.  Blood will spill, bones will break, people will die.

So that’s my observed experience about near misses through a planned, over time, direct but not published or peer reviewed observation.   

People commonly have one thing on their mind and are, in all likelihood, unaware (maybe oblivious)  of the risk around them.  They do this regularly and in all sorts of situations.  People seem to be unaware of the risk of a bad things happening … until it is too late.

I think that’s the point about  a lot, maybe all, near misses,  Dekker talks about drifting into failure or an underappreciation of the situation.  Things happen, and for the most part there are no consequences, indeed no appreciation of the bullet being dodged. 

So why am I raising this?  A variety of authors, including the International Organization for Standardization in their new standard ISO7101:2023  (Healthcare organization management — Management systems for quality in healthcare organizations — Requirements  writes that:  

the organization shall have a documented system to identify risks …. Controls shall define processes to capture and analyse  near misses, etc. and assess the risks and opportunities by identifying and analysing each risk.  

Tough to do when (if I am right) near misses happen around us all the time mostly when we are oblivious. 

 Bon mots.

 

PS:  Let me be clear, the main perpetrator to these potential crises is not the folks getting ready for some cycling fun; it is the jack-asses that put the stand in a dangerous place. 

What do you think?

 

The Fourth year of Awarding the Noble Prize at UBC PathDay 2026 celebrations

Yesterday was the annual even for the University of British Columbia’s Department of Pathology and Laboratory Medicine  day to celebrate students staff and faculty.  It is a day of projects,  presentations and recognition of jobs well done by student, staff and faculty, and an opportunity of us old guys to come back and celebrate with the collective, and a time to give back.

In my case it is the day that we recognize student achievements for projects and presentations that highlight activities and insights in Quality and Improvement.  It’s our (my family’s)  way to support the students who see what others can see but go that extra step to ensure that their work is more meaningful because they focus on eliminating  error and risk, and improving patient care. 

One example:

When people are admitted to hospital because of probable infection it is common place take cultures but also  get patients  started on broad spectrum antibiotics that provide best chance of success but increase the risk of developing complications including resistance.   When the cultures are completed and they have identified both the infecting bacteria  and the most effective antibiotic,  the drugs get changed adjusted quickly, unless the results come out on the weekend.  If the results are reported on a Monday to Friday, the drug change happens on the same day.  But if they arrive on Saturday or Sunday, there is a delay and the change often on  Monday.  One student saw this, and put in the time to develop and organize an observational study, and then asked the important question  “why?”  (Bacteria Don’t Take Weekends Off).  

Highlighting the questionable practice is the first step to change, improvement and reduction of risk!

This year we handed out seven awards to well deserving students that demonstrated a particular level of interest and excellence in projects focused on Laboratory Quality and Improvement.  Congratulations to all.

Making Healthcare Better 

It's CHANGE TIME for HEALTHCARE

I'M BACK!!!

It has been a while since I have been active in MMLQR.  I retired from my position as a Professor in Pathology and Laboratory Medicine with my major focus on Quality Managment and External Quality Assessment.   I was able to find a brilliant scholar with stong Quality Interests, and decided the best way to address change was to WALK AWAY.

My university, was generous and honoured me by granting  my Emeritus Professorship.   While I have not been actively active in the university I have continued in my interests in the arena of Quality, both inside and outside the medical laboratory, and have been active with the American Society for Quality (ASQ).  

I have been away but (I hope) I have kept my brain and interests intact.  

I have returned to MMLQR  because I would like to think I will be able to provide some interesting and perhaps provocative thoughts.

As a starter, I am looking at a BRAND NEW INTERNATIONAL standard based on a foundational  document now nearly 30 years old.

Just Culture

For those of you involved in the Quality arena, you know this phrase.  It does not mean "Just" in the sense of "merely culture".  "Just Culture" was introduced into Quality discussion around 1997 by James Reason (see Managing the Risks of Organizational Accidents 1997) when he was talking about organizations that have a work environment in which people may create problems, but work in an environment of trust in which people are encouraged, and rewarded(?) for drawing attention to what has happened, knowing that at some level there can be and will be a line between acceptable and unaccpetabl behaviour.  Just Culture was intended to provide a safe place to ensure that "messing up" was not always going to end up with someone being punished or fired.   Sydney Dekker embraced the concept in 2007 (see Just Culture: Balancing Safety and Accountability) and again new books on the theme near every 5 years (the last and latest was in 2024)   

All are good reads.  If you can find them, they are nice written, and conversational in tone. 

The books put forward the notion that if the environment is safe and "just", workers will be forthcoming of all their errors, goofs, and near misses, a notion with which I have some struggles.  Without going into detail at this time,  my experience and observation is that many workers are oblivious of their errors, and for those that do notice them,  often the errors are self  interpreted as minor or likely inconsequential. 

I will tell you a story.  A few years back I was given an opportunity to look at files that were gathered by my province (British Columbia) on errors identified in medical laboratories.  The concept was that if people identified they have caused a problem, they would self report into the laboratory computer and the information was then stratified by type of error, interpreted severity of error etc.  I was able to create a number of manuscripts from the data (look for Noble et all, in Diagnosis (Berl) 2017 and 2018).  Anyways, during a presentation on the topic, one laboratory technologist told me that in her laboratory staff would sometimes, create a report, but put another staff persons name on it, NOT because they were afraid of repercussions of reporting, but because it was considered as SAFE MISCHIEF!!

Anyways, the reason that I have picked this up is because Just Culture is about to go international in a big way because the International Organization for Standardization (ISO) has just published a new standard ISO 7101:2023 entitled "Healthcare organization management — Management systems for quality in healthcare organizations — Requirements" which is predicated on these organizations (mostly hospital) embracing (or requiring) the use of Just Culture as the foundation of hospital environment and safety.  

Maybe this will happen, but it certainly won't happen over night.

More on this later.

M

Feels Good To Be Back.

795,000 Serious Diagnostic Errors

 

Over the last many years there has been a wide interest in medical and diagnostic error.  One can see why.  When a person is sick, or worse, when the sick one is their child or significant other,  the first thing you want is good and immediate reliable accurate and timely care.  It would be nice if that was what happened all the time.  Usually it does, sometimes it does not; sometimes it does not… but that is a topic for the next time!

The healthcare community is clearly concerned for all the right reasons to try and understand why things go amiss.   As much as there are too many events of long waits in the ER and too few family physicians, problems tend to occur infrequently, especially in countries with a well developed healthcare system.  Sometimes, probably most times when thing go badly (again, this is a rare event), it is because of person-error resulting in a missed on wrong diagnosis.

In my own studies I was able to look at provincial medical laboratory errors recorded within the healthcare system by physicians, and laboratory workers.  Because of my own knowledge and experience in laboratory quality assessment I was able to confirm the common finding that most errors in laboratory testing occur before the sample ever gets to the laboratory.  Those are really problematic because they samples get tested seemingly without difficulty or error, but the information arising can be wrong and misleading. 

The other observation, unfortunately, was that many in-laboratory errors never get reported, sometimes because people were too busy, and other times just because people chose not to report.  Some bizarrely even used the reporting process for getting others in trouble by reporting errors under another person’s name!)

This month, a group in the United States wanted to put a number on just how many errors occur that result in serious harm.  They did some looking at government and hospital records and did some interesting but definitely iffy arithmetic and came to the conclusion that some 795,000 diagnostic errors result in serious harm to patients each year.  In their paper they made two important comments, one being that in the US there are about 1 billion healthcare visits each year and the likelihood of a serious harm befalling an individual patient was about 1 in 1,000. 

They also acknowledged that their work was largely crude and a gathering of a variety of information and pointed out that much of their information is based on data that is composed of largely unverifiable estimates.  In my own mind it was much less an estimate and much more a crude  guestimate.

But all that will not matter.  Already the media has jumped to saying that people are at peril because there almost a million diagnostic errors every year in the United States.  It provides the news sharers the next new opportunity to tell everyone their very existence at jeopardy.   (For those interested, visit my blog entry on April 28, 2020… “We are all going to DIE”).

We unfortunately live in a society that is disturbingly comfortable with developing and using bad information for its own purposes.   It puts, in my opinion, an additional obligation on serious writers and investigators to ensure that their information does not get abused and misused.

In my opinion these authors have gone through an interesting exercise by, in their own words, pursuing a “novel technique” of gathering disparate information from a bunch of places, and put the information together to see if they could come up with a value that could be used as a form of marker for future study. 

By their own acknowledgement the results are an estimate.  Personally I suspect their calculation is too crude, but as they say in Australia … “Goodonya!”

There are better techniques these days for doing mass data analysis, including AI.  While the authors did not mention trying that, I would be surprised if they did not give it a shot.   

In the meantime, when you read about the near million serious errors that occur each year, before you get too healthcare phobic, put it in context.

 

Newman-Toker DE, Nassery N, Schaffer AC, Yu-Moe CW, Clemens GD, Wang Z, Zhu Y, Saber Tehrani AS, Fanai M, Hassoon A, Siegal D. Burden of serious harms from diagnostic error in the USA. BMJ Qual Saf. 2024 Jan 19;33(2):109-120.

 

Restelli V, Taylor A, Cochrane D, Noble MA. Medical laboratory associated errors: the 33-month experience of an on-line volunteer Canadian province wide error reporting system. Diagnosis (Berl). 2017 Jun 27;4(2):79-86.

 

 

 

 

 

 

 

 

 

 

Artificial Intelligence and The Future of External Quality Assessment -

 

 

I have been away for a while.   I apologize for the delay in writing.

M

I have been watching with some interest all the activity that surrounds Generative AI through using ChatGPT4.  The idea that you can ask a computer a question and it scans the electronic datasphere and gathers a whole bunch of “information” and then compresses it into a number of sentences which can be read in a form of basic interpretable English intrigues me.  It took little time for me to understand why there is so much interest (and fear) about this new tool.

Since it is readily available at a kind-of-affordable cost, I figured I should learn a little more about what it can and cannot do.

Being of a certain age, the first thing I did was buy the book “AI For Dummies”.  For my generation there is a “Dummies” book for almost every topic you can possibly want.  It was not perfect, but then again what could I expect?

The next thing was to jump in with a question: "What is the future of laboratory external quality assessment?"

Almost as soon as I got my fingers of the keyboard, ChatGPT4 started to respond.  It took all of maybe 5 seconds.

What I got back impressed me to the extend that the response was on-topic which means that it was framed around what I understand as  laboratory external quality assessment.

The response was broken down into sections which included:

1.    Integration of artificial intelligence (AI)  to revolutionize the medical laboratories by improving accuracy, speed, and efficiency.   It would do this through analyzing data, and assist through interpreting test results, and help identify potential errors or inconsistencies.

2.    Digitalization and remote testing: The increasing digitalization of healthcare could lead to a shift from traditional paper-based proficiency testing to online platforms.

3.    Remote proficiency testing could allow laboratories to participate in testing programs from anywhere, reducing the need for physical samples and paperwork. This would streamline the testing process, increase accessibility, and facilitate real-time performance monitoring.

4.    Personalized proficiency testing: As healthcare moves towards personalized medicine, proficiency testing may also become more tailored to individual laboratory needs. Laboratories may receive customized samples or challenges that align with their specific testing capabilities or areas of expertise. This approach could help laboratories identify and address any weaknesses or gaps in their performance more effectively.

5.    Continuous quality improvement: Proficiency testing programs are likely to focus more on continuous quality improvement rather than simply measuring a lab's performance. This could involve providing laboratories with detailed feedback and recommendations for improvement based on their performance in proficiency testing. Collaborative learning networks and knowledge sharing platforms may play a role in facilitating continuous quality improvement among laboratories.

6.    Regulatory changes and standardization: Changes in regulatory requirements, such as the implementation of new quality management systems or accreditation standards, may affect the future of proficiency testing. Standardization of proficiency testing methods and metrics across different regions and countries could improve comparability and harmonization of laboratory performance assessment.

Some of this I found interesting, but with apologies to the gurus of artificial intelligence, while the subject was correct, for a lot of the response the tense was wrong.  Most of it dealt with what is the near or distant past, or was just wrong.  

 For example while there is interest in virtual microscopy that can be on-line, for the microbiology and chemistry and blood banking, it is difficult to imagine that test competency can be monitored without physical samples.

Also the notion of personalized proficiency testing has been a fact  for many years.  Laboratories already select the companies, and the sample products they want to receive.  While there may be some refinements, they will likely be minor.

What does sound interesting and maybe even futuristic, the use of EQA to monitor knowledge and performance on continuous improvement and knowledge of regulation changes, is already in place in some EQA programs already.  In our program we call that para-examination EQA. 

So here is what I have learned…  computers have reached a new point where they are able to access the whole datasphere and process large amount of data on a wide range of specific topics here and now.  Their memory systems can be trained to look for specific words and patterns, frame them in a new way and restructure it into something different.   And present that is maybe new and novel, but not ready to take over the world.

Interesting? … Yes.   Helpful?...  In some ways.  Definitive?  ….  Not Yet.

It reminds me of another new thought (????) roaming across the drivelsphere.   "… have a vision of what can be, unburdened by what has been. "