Computer analysis of probable Root Cause/Contributing Cause(s) of preventable patient deaths using elecctronic medical records.

Bob Latino blatino at RELIABILITY.COM
Tue Mar 7 18:29:56 UTC 2017


As a member of this forum for years, whose 30+ year career has been spent in the Reliability Engineering/Root Cause Analysis (RCA) field, I am elated to see these field-proven approaches being seriously considered for application in the Dx error space.

When looking at applicability of these analytical approaches, their effectiveness is not necessarily correlated to where they are applied (whatever domain expertise is involved and the unique type of outcomes they experience), as it is to how they are applied.  During my career I have applied these same approaches in most every type of industry (i.e. - steel, oil, power, counter-terrorism, school bullying, late deliveries by UPS, customer complaints, med order errors, blood redraw rates and many more).  The commonalties between all of these businesses is 1) human decision-making triggers observable consequences and 2) there are cause-and-effect relationships that queue up to cause both desirable and undesirable outcomes.

The Anaphylactoid case study that I posted a while back, was a misdiagnosis case (https://www.youtube.com/watch?v=3XkQAsXWAmM).  However, it demonstrated observable cause-and-effect relationships resulting from poor decisions.  These were backed up by sound evidence that they did indeed occur.  The result was a bad outcome.  Where the biggest benefit of a true RCA approach comes from, is not 'WHO' made the poor decision, but WHY they felt the decision they made at the time was the correct one.  By drilling down on the reasoning process, we will seek to understand what inputs went into the decision that were accurate, and which were not accurate.  For the inputs that are inaccurate, we drill deeper to find out WHY they are inaccurate and thus influencing decision making.  This will delve us deep into exploring our various systems that support efffective decision-making.

Unfortunately RCA has a PR problem, as it is viewed as always associated with being applied to bad outcomes, AND it is unfortunately applied very inconsistently (lack of breadth and depth).  In my world, when we see RCA applied in this manner we call it 'Shallow Cause Analysis'.  It stops short of the understanding of human reasoning/human performance.

As an RCA provider, I can tell you that none of the RCA providers I know, approve of or like the term 'ROOT CAUSE ANALYSIS'.  It is misleading and inaccurate as there is never one (1) root cause. Here is another video (it is a bit dated so excuse the loss of resolution quality) that will express the RCA process in a simplistic manner - https://www.youtube.com/watch?v=gxxbR5qbA0I.

There is absolutely no reason the process of RCA cannot be applied proactively.  Hospitals are required by TJC to conduct FMEA's (Failure Modes & Effects Analyses) every 18 months.  Unfortunately, not many hospitals take stock in the tool and see it as another compliance task to get off their plate.  FMEA is a valuable tool that has been mandated in high hazard industries for decades.  This simple calculation of risk is Probability x Severity = Criticality.  If an FMEA were properly done on any 'process', we could then take an 80/20 split of the results.  Typically 20% or less of the potential Failure Modes will represent 80% or greater of the risks.  It is this 20% that we could apply prospective RCA's, to understand why the risks are so high, and to then mitigate the risks.

This is a strategy that seeks to avoid responding faster to failure/consequences (reaction) and prevent them while they are still at the risk stage (proaction).  This is what Reliability is all about PROACTION and NO SURPRISES.

Unfortunately, most organizations only require RCA's to be conducted after triggers are met, and that usually will involve harm/death, significant financial loss, regulatory violations or high severity near misses.  It is too late by that time.

Here are other texts of mine that would describe my rantings in detail if anyone was interested.

1. Latino, Robert J., Latino Kenneth, C. and Latino, Mark A. Root Cause Analysis: Improving Performance for Bottom Line Results. 4th Ed., 2011, c. 280 pp., ISBN: 9781439850923, Taylor & Francis. Boca Raton.

2. Latino, Robert J. Patient Safety: The PROACT Root Cause Analysis Approach. 2008, c. 272 pp., ISBN 9781420087277, Taylor and Francis. Boca Raton.

3. Contributing Author: Error Reduction in Healthcare: A Systems Approach to Improving Patient Safety. 2nd ed, 2011 [Apr], c. 284, ISBN: 1-55648-271-X, AHA Press.

4. Contributing Author: The Handbook of Patient Safety Compliance: A Practical Guide for Health Care Organizations. 2005, c. 350 pp. ISBN 0-7879-6510-3, Jossey-Bass .

While Dx error is certainly quite complex, it can be logically broken down into its digestible components.  Like I have said in past posts, Dx error is not the 'failure', it is a contributor to the failure (bad outcome).  The act of making a Dx error is what we call a Human Root Cause (decision error).  The pot of gold is in understanding why well-intentioned physicians, felt the diagnosis they made, was the correct one at the time (or Latent Root Causes).


Robert J. Latino, CEO
Reliability Center, Inc.
1.800.457.0645
blatino at reliability.com
www.reliability.com
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From: Mark Graber [mailto:Mark.Graber at IMPROVEDIAGNOSIS.ORG]
Sent: Tuesday, March 07, 2017 12:02 PM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
Subject: Re: [IMPROVEDX] Computer analysis of probable Root Cause/Contributing Cause(s) of preventable patient deaths using elecctronic medical records.

Completely agree – we have a lot to learn about the prospective approach and “Safety 2” ideas.  Gary Klein made  a similar point at DEM several years ago –that instead of focusing on what goes wrong, we should spend more time learning from what goes well, which is much more common.  Bob Wears work on this is similarly relevant.

Thanks to David Woods for providing us with some starting points on learning how to do this.  At first blush, the new approach seems an order of magnitude more difficult than retrospective analysis, resembling the difference between retrospective RCA’s (detailed, but at least approachable) and prospective PRA’s (which get very complex very fast).

I’d love to see an example of where this new approach has been used to improve diagnosis or address some type of diagnostic error, if anyone has one.

Mark

Mark L Graber MD FACP
President, SIDM
Senior Fellow, RTI International
Professor Emeritus, Stony Brook University
[cid:image003.png at 01D29740.24437EF0]




From: John Brush <jebrush at ME.COM<mailto:jebrush at ME.COM>>
Reply-To: Listserv ImproveDx <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG<mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>>, John Brush <jebrush at ME.COM<mailto:jebrush at ME.COM>>
Date: Tuesday, March 7, 2017 at 5:13 AM
To: Listserv ImproveDx <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG<mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>>
Subject: Re: [IMPROVEDX] Computer analysis of probable Root Cause/Contributing Cause(s) of preventable patient deaths using elecctronic medical records.

I think this post by David Woods is really important. This systems approach was brought to health care by Don Berwick and others.
I also think that we could bring a systems approach to our own thinking. Rather than thinking back and blaming ourselves for error (a flawed hindsight approach), we should think prospectively about how we can organize our thinking, develop good thinking habits, use reminder systems, and calibrate our intuition using simple tools like likelihood ratios. This is what I tried to emphasize in my book.
John Brush

John E. Brush, Jr., M.D., FACC
Professor of Medicine
Eastern Virginia Medical School
Sentara Cardiology Specialists
844 Kempsville Road, Suite 204
Norfolk, VA 23502
757-261-0700
Cell: 757-477-1990
jebrush at me.com<mailto:jebrush at me.com>



On Mar 6, 2017, at 11:29 AM, Woods, David <woods.2 at OSU.EDU<mailto:woods.2 at osu.edu>> wrote:


The question posed provides an opportunity to recalibrate some of the discussions about diagnosis.   At the beginning of the patient safety movement,  two of the three  basic values we articulated were:  to move beyond blame and to adopt a systems approach.  The discussion has surfaced the desire to have a computer automatically (or to have a computer aided mechanism) to trace back from adverse event to cause.  This falls into the hindsight bias trap which has plagued and undermine the ability to learn after adverse events.  Tracing backwards from outcome in search of cause guarantees hindsight bias, and hindsight bias will lead to oversimplifications. The oversimplifications will inevitably lead to a component not a systems view and will focus on people and blame. This is laid out in the book Behind Human Error (originally 1994 / 2nd edition 2010), and overcoming hindsight bias was one of the important messages during those early days and the rise of the patient safety movement 1995 to 2000.

The key is to trace forward based on the nature of cues, possibilities, uncertainties, expectations, norms, work activities, etc.  This is laid out in Behind Human Error and then in the later Field Guide to Human Error Investigation by Dekker.

Today  there are two major threads in safety related to the original work on escaping the hindsight bias. One  is captured in the phrase — "the difference between work as imagined and work as done.”  This phrase is used to highlight that improving safety should focus on what usually goes right and what people do in order to make things work. For example blameless postmortems are being used by many capture a much wider range of information about how the system normally works the difficulties it faces pressures that operates under and how  the system really works.  Breakdowns and incidents provide opportunities to learn about how the system really works so that I can be modified in ways  the function better given the real pressures and resource limitations. The second relates to the failure to truly see systemic factors rather than faulty components - usually people. As one health care manager said, “ system, what’s a system? I can’t blame a system.”  This tendency to adopt a systems approach rhetorically, but to continue to analyze adverse events is due to component breakdowns is widespread across industries (or the systems factors become vague category labels like communication). As a result, variety of techniques of been developed (e.g., STAMP and FRAM  and others) and are being used to try to facilitate true systems thinking especially as part of proactive safety management.  A good resource is the PreAccident Podcast series by Todd Conklin http://preaccidentpodcast.podbean.com<http://preaccidentpodcast.podbean.com/>

 The basic points are:
~ to remind people about the contamination that comes from the hindsight bias,
~ tracing backwards from known outcome guarantees hindsight bias and oversimplifications which block learning.

The second part of the comment is — how can computers help us understand diagnostic process looking forward, not backward, and provide insight about the difficulties and vulnerabilities given the wide variety and diversity of clinical situations that can be included under the general label of diagnosis.   This is a quite interesting topic and one that requires weeding away some of the assumptions and misunderstandings that are mixed up in the discussions about improving diagnosis in health care.  But that is for another post.

David


David Woods
Releasing the Adaptive Power of Human Systems

follow @ddwoods2<https://twitter.com/ddwoods2>

Professor
Department of Integrated Systems Engineering
The Ohio State University

Past-President in
Resilience Engineering Association
Human Factors and Ergonomics Society

SAVE the DATE
7th Biennial International Symposium on Resilience Engineering
Liège Belgium, June 26-29, 2017

woods.2 at osu dot edu
614-946-0123

SNAFU Catchers Consortium
https://www.oreilly.com/ideas/situation-normal-all-fouled-up

keynote on autonomy and people see
part 1: https://youtu.be/b8xEpjW0Sqk   part 2: https://youtu.be/as0LipGTm5s  part 3: https://youtu.be/2GEsxMuLWIE

keynotes on resilience and complexity see
https://www.youtube.com/watch?v=7STcaWjJoww&index=7&list=PL055Epbe6d5YDU6sikjqcd_YM9XT4OehD
or
https://www.youtube.com/watch?v=zHJdDMQJXiw&index=8&list=PL7_JAXDeVTvIZ_Y-ddqCiGF-ZKxtM5MLe







On Mar 4, 2017, at 4:52 PM, Phillip Benton <0000000697ec7b18-dmarc-request at LIST.IMPROVEDIAGNOSIS.ORG<mailto:0000000697ec7b18-dmarc-request at list.improvediagnosis.org>> wrote:

Jason,

As a physician-attorney now devoting all of my remaining time to improving medical quality by decreasing medical error, I applaud your great and continuing efforts.

I am exploring the possibility of creating a system that reverse engineers from decisions on Dx and Rx and would like your thoughts: If we know the adverse event [patient death after 6 days illness with undiagnosed (until autopsy) septic peritonitis from diverticulitis with occult rupture] is there any computer program in existence or under development that can input the recorded clinical and pathologic facts to deduce a probability hierarchy of medical errors that would have led to this patients death? In effect, is there software to do probable
'root-cause analysis' based strictly upon the digitized medical record (H&P, imaging, labs, consultant opinions, path reports)?

She was first misdiagnosed as "constipation" on the first ER visit for severe abdominal pain, then again misdiagnosed as "atypical cardiac pain" on ER visit 3 days later. Acute abdomen "signs" were present but not classic, not uncommon for a 72 YO with an aging immune system.  She was admitted and had negative cardiac consultation but no further diagnostic studies, then died 23 hours after admission with cardiovascular collapse from undiagnosed sepsis.

If this type computer retro-analysis were possible, the next step would be to investigate to confirm and then to correct the human and systems errors. Of course an experienced physician(s) has to put it all into context at the end, but just trying to piece together an exact chronology is very difficult, even for top (Harvard & Yale) reviewing medical experts, with our new  electronic hospital records systems. Could 'Watson' or 'Isabel' not do it more quickly?
Thanks,  PGB

Phillip Benton, MD, JD
Atlanta Medical Center
pgbentonmd at aol.com<mailto:pgbentonmd at aol.com>

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