Our approach to study of method of diagnosis

Bob Latino blatino at RELIABILITY.COM
Wed Dec 20 14:47:54 UTC 2017

Dr. Bimal, thanks for your paper explaining your very practical and logical approach.  While I am not a clinician, this is the approach I have been trying to suggest for a long time.

Let me see if I can offer a comparable analogy.  For background purposes I am a career investigator of undesirable outcomes in the high hazard industries and healthcare (HC).

Over the past 32 years I have investigated hundreds of 'undesirable outcomes'.  Such bad outcomes include equipment failures, financial losses, terrorist attacks, deaths/injuries and even bullying in schools.  My point here is that no two cases are exactly the same.  However, the cause-and-effect sequential logic used to solve them is the same.  While all of these bad outcomes are very different, they all have one thing in common; poor decisions were made that triggered the bad outcomes.

Dx error, to me, is a human root cause or decision error.  It triggers either a bad outcome or near miss which is the actual 'Event'.  However, these discussions revolve around 'Why' each individual decision error is made.  So no matter the bad outcome, we will eventually come down to a decision-maker and strive to understand why that person felt the decision they made at the time, was the appropriate decision.

from  this point on, we are delving into understanding what factors went into the decision-maker's reasoning process, to draw the conclusion(s) they did.  We group these into the following potential cause categories:

1.       Organizational System Deficiencies - the usuals include policy and procedure issues, training issues, purchasing issues, communication issues, human factors issues, etc.  Often overlooked are less than adequate (LTA) management/leadership oversight to identify LTA P&P in place, LTA identification of drifts in decision-making where normalization of deviance evolves into accepted practice, LTA review of the quality of RCA's conducted,  to name a few.

2.       Restraining Paradigms/Cultural Norms Examples-

a.       'While safety may be reported to be #1, we all know that budget pressures will force decisions on the floor that will potentially compromise safety'

b.      The belief that 'Compliance equates to organizational safety'

c.       'In order to be viewed as a team player, I will abide by the established rules, knowing they are not as effective as other means I am aware of'

d.      'Our facility has set a '0' harm goal, therefore I am not likely to report near misses and chronic failures that could cause harm, because it may adversely impact the overall safety goal (therefore our feedback systems do not reflect the risk reality and our executives become complacent in their belief the organization is 'safe')

3.       Sociotechnical Factors (External Influencers on Policies and Decision-Making)

a.       Congress and Legislators

b.      Government Regulatory Agencies

c.       Industry Associations

d.      Unions

e.      Insurance Companies

f.        Courts/Legal System

g.       Economy/Finance System (i.e. - $/share)

So no matter the nature of the bad outcome, when it gets to the decision-maker, all of these factors become relevant when exploring reasoning.  I know these are not stated specifically to Dx Error, but conceptually they all potentially apply.

I have noticed in HC when I assist in facilitating RCA's (as an independent investigator), oftentimes team members will want to use a 'Literature Search' as a valid form of evidence to support an hypothesis in a given case.  I will not allow that because a literature search merely demonstrates experience from somewhere else.  It does not represent the same conditions as in the case I am looking at, therefore it cannot conclusively prove in my case that the same issue happened.

As many on this forum are aware, my experience in Dx Error is at best from the perspective of a patient.  I have zero clinical experience. However I have the utmost respect for clinicians and the challenges they face like making accurate and timely diagnoses.  As an investigator I consider myself a 'methodologist' who attempts to reconstruct undesirable outcomes using a very methodical, disciplined and evidence-based approach.

To me, 'Dx error' has to be broken down based on the bad outcomes that are occurring, in order to get a grip on which priorities to attack first.

                                                               i.      Which type of Dx errors are more commonly resulting in unique types of reportable bad outcomes?

                                                             ii.      What are those reportable bad outcomes (Events)?

                                                            iii.      Can those bad outcomes (in which Dx error contributed) be grouped into Event Categories, and %'s applied to frequency of occurrence and impact/occurrence?

                                                           iv.      Can a listing then be sorted from highest to lowest showing which are the highest impact bad outcomes due to Dx error (Dx is not 'THE Root Cause')?

                                                             v.      Normally Pareto would apply and 20% of the types of Bad Outcomes would be occurring 80% of the time (and represent 80% of the adverse impacts).  This would define the population of worst outcomes that should be addressed first, thus breaking overall Dx Error down to manageable chunks.

                                                           vi.      Effective and disciplined RCA could then be applied to Events that are most impactful and would yield the greatest returns in the shortest period of time.

As Dr. Bimal alluded to, have there been any studies that contrasted the results of the Bayesian approach to his 'practical' approach, when looking at the same cases?  I have attached a paper I wrote a while back where we applied the more common RCA approaches on the market to the same case, and demonstrated which were more comprehensive.  Has anything like that been done on Dx Error?

Here are some video case studies that will demonstrate what I mean by reconstructing an undesirable outcome.  My intent is not for you to focus on the content/SME as much as the structure of the thinking, and the drilling down past decision makers and into the reasoning of the decision.

1.       Michael Colombini MRI Death/RCA - https://www.youtube.com/watch?v=0nA-UceHMqc<https://www.youtube.com/watch?v=0nA-UceHMqc%20> (~25 min)

2.        Pt Death Due to Missed Anaphylactoid Reaction - https://www.youtube.com/watch?v=3XkQAsXWAmM<https://www.youtube.com/watch?v=3XkQAsXWAmM%20> (~ 15 minutes)

I realize I'm a fish out of water on this forum, but I do believe that some of the concepts and disciplined approaches we use from other industries can help attack this massive Dx Error problem that we all are impacted by.

Thanks for your patience.

Robert J. Latino, CEO
Reliability Center, Inc.
blatino at reliability.com
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From: Jain, Bimal P.,M.D. [mailto:BJAIN at PARTNERS.ORG]
Sent: Wednesday, December 20, 2017 7:38 AM
Subject: [IMPROVEDX] Our approach to study of method of diagnosis

In this attached paper, I explain my approach of studying the method of diagnosis which consists of investigating and analyzing diagnosis in actual practice. This approach has been taken as I find the prescription of the Bayesian method to be highly unsatisfactory for a number of reasons which I discuss in this paper.
Please review and comment on this paper.


Bimal P Jain MD
Northshore Medical Center
Lynn MA 01904.

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