NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.

Elias Peter pheski69 at GMAIL.COM
Thu Feb 22 18:13:02 UTC 2018


First, I am going to point out that there is a difference between preventing errors and preventing harms. Not all errors result in harm, and not all harm is a result of error (let alone diagnostic error). This is worth remembering while we work on identifying and addressing error.

The diagnostic process is just that - a process, not an event. It does not always have a fixed endpoint, at least in primary care. It is almost always messy and based on information that is incomplete and incorrect. In some ways, as a clinician, I have felt that labelling a specific step in my diagnostic process as ‘error’ feels like being told I added the following numbers incorrectly: 5 + 9 + apples + perhaps approximately 2 if it is Tuesday, but 4 on some other unspecified days. Diagnosis in the real world is inherently both approximate and tentative. 

Various definitions have been offered for diagnostic error, but SIDM uses the one accepted by the National Academy of Medicine, excerpted here from the SIDM website:

"The National Academy of Medicine (formerly the Institute of Medicine) defined diagnostic error as the failure to (a) establish an accurate and timely explanation of the patient’s health problem(s) or (b) communicate that explanation to the patient. Simply put, these are diagnoses that are missed altogether, wrong, or should have been made much earlier.”

There are difficulties operationalizing this definition. Examples:

A fifty year old patient presents with hoarseness during hay fever season. He and his clinician decide this is allergies and post nasal drainage and treat it as such. It improves but it does not respond completely. Four weeks later, visualization of the cords shows a nodule. One week later the path report shows a squamous cell carcinoma. Four weeks later after surgery and neck dissection, it is fully staged. Which of the diagnoses are errors? 
A 19 year old college student presents with sore throat, temp of 100.2, exudate on tonsils and nor URI symptoms and rapid strep test is positive. She is penicillin allergic. Treatment is with ciprofloxacin. Now imagine three outcomes. One is that she worsens dramatically over the next 36 hours and re-presents with Lemierre’s syndrome. The second is that her throat improves some but she returns with prominent adenopathy and excessive fatigue and is found to have infectious mononucleosis. The third is that she improves but 6 months later is found to be HIV (+) and her sore throat was probably the primary infection. Was her strep diagnosis an error in each of these cases?
A thirty year old woman is found by her PCP to have (asymptomatic) microscopic hematuria. Renal evaluation is normal but pelvic ultrasound shows a complex cystic mass on an ovary. This information is transmitted to her by phone and to her GYN provider by phone and faxed report. At her next gyn routine visit 12 months later this is not pursued and 12 months after that she is found to have an ovarian cancer that was clearly not present 2 years earlier, but that might not have occurred if her ovarian mass had been removed. Clearly a preventable bad outcome from an error - but what (and how many) are the specific error points?
A woman with recurrent non-specific vaginitis (itching and discharge) is seen multiple times by two clinicians in her primary office and by two gyn consultants, resulting in 5 different diagnostic labels but no effective treatment. (The episodes resolve in 5-8 days each time, with or without treatment.) Her pharmacist points out that she comes in for a prescription for her vaginitis quite reliably the week after her husband is treated with Septra for his recurrent prostate infections. She is allergic to Septra and her vaginitis was allergic in nature. 

Assuming one has addressed the problem of specific operational details, there is still a HUGE problem with using available data: people studying the data do not always use the same definition (or specific operational process) and the published data is incomplete and uses inconsistent definitions.

This is a long preamble to my response to the issue Bob Latino poses of ‘quantifying’ the problem. I think of ‘harm from diagnostic error’ as a huge umbrella category that is impossible to work with as a whole. It would be like trying to reduce ‘harm from moving vehicles’ as a category. Canoes? Automobiles? Taxis? Trains? Trolleys? Chairlifts? Commercial jets? War planes? Skateboards? Amusement park rides? Snowmobiles? No one would reasonably suggest addressing all these with one approach. I feel the same way about diagnostic error.

It seems to me one has to pick a chunk and work on that.  Data that tells us where the most errors occur and/or where the most harm occurs would be useful in determining which chunks to prioritize, but this data does not need to be as comprehensive or accurate as the subset data used to prevent errors and harms. Once one has picked a chunk to address, one can begin to ask questions like what kinds of diagnostic error are most common and/or most harmful in this chunk, what are the outcome signals that should be tracked, can the outcomes or the errors be prioritized…etc.

Sorry for the length of this. I didn’t have time to shorten it…

Peter


On 2018.02.22, at 4:24 AM, Bob Latino <blatino at reliability.com> wrote:

Thanks Peter.
 
I was asked a while back to answer some questions by SIDM about this very issue.  This is an excerpt of my answers related to this line of questioning:
 
1.       Defining Scope of Problem.  I have not been able to understand from SIDM what the definition of a Dx error actually is, therefore I cannot grasp a scope.  It seems SIDM groups all Dx error in one big bucket, as if all of the conditions would be the same or similar.
2.       Quantifying the Problem.  I don’t believe SIDM can be proactive, until they get a handle on the reactive.
a.       Getting a grip on reaction.  I have seen no attempt to break Dx error down into manageable chunks, based on severity of outcomes.  This has been proposed by Dr. Rob Bell and myself for years, to members of the SIDM forum.
                                                               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.

This is how we would normally approach a 'problem' from an industrial perspective.  I don't think it should be different in HC, but I am not an SME in HC.  I do know in any environment that data is necessary to define an analytical direction forward.  I do not know where you all would get such data (if it exists), but i have not seen any consensus path forward for solving 'Dx Error'.  No matter what data is available, it will be based on what is reported.  So we can rest assured the 'real' problem is a multiple of what is reported (i.e. - the under or not reported reality).
 
Perhaps I am missing it because of my lack of an 'insider perspective'?
 
Thanks again for your patience with my questioning attitude.
Bob
 
Robert J. Latino, CEO
Reliability Center, Inc.
1.800.457.0645
blatino at reliability.com <mailto:blatino at reliability.com>
www.reliability.com <http://www.reliability.com/>
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From: Elias Peter [mailto:pheski69 at GMAIL.COM <mailto:pheski69 at GMAIL.COM>] 
Sent: Wednesday, February 21, 2018 6:28 PM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG <mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
Subject: Re: [IMPROVEDX] NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.
 
I suspect there is data about this, but I don’t have any. Perhaps others…?
 
Peter
 
 
On 2018.02.21, at 3:54 PM, Bob Latino <blatino at RELIABILITY.COM <mailto:blatino at RELIABILITY.COM>> wrote:
 
Thank you.
 
Is there any data that shows more diagnosis errors are made by a certain democratic (I.e. - young, old, certain specialty, certain type of outcome, etc.)?

Sent from my iPhone

On Feb 21, 2018, at 5:49 PM, Elias Peter <pheski69 at GMAIL.COM <mailto:pheski69 at GMAIL.COM>> wrote:

I don’t know that my perspective does more than offer a way to visualize how context plays a role, in the primary care setting.   I found it useful, though, when teaching. It provided a way to reassure learners that a key lesson to learn was not that they needed to master ‘all of medicine’ but that they needed to recognize those rare instances where one had to be right, right now, and what to do in those rare instances. Beyond that, accuracy counts more than speed.
 
About incentives.  I would take issue with my own statement that the consequences are small, unless qualified by saying the the external consequences are small. For me, and for the clinician mentors and colleagues I have learned from and admired, the incentive was always internal and personal rather than external and structural. The best clinicians I have known have been those who were driven to find the right answer, not those driven to check the right boxes or avoid litigation. I don’t know how to make that standard. It would seem that there are two parts. First, the selection process. Second, a system that focuses on internal rather than external rewards (reversing course in many ways) and is based on transparency and valuing honest self-scrutiny, admitting ignorance and error in order to learn from them. Culture, in other words.
 
Peter
 
 
On 2018.02.21, at 12:07 PM, Bob Latino <blatino at reliability.com <mailto:blatino at reliability.com>> wrote:
 
Thank you (as always) for your experience and well-reasoned reply.
 
Seems to me that you have outlined a draft priority schedule for the diagnoses that actually result in the worst outcomes.  Is that a start to trying to break 'diagnosis error' cause category down into its manageable chunks and start to analyze what system's level factors contribute to such decisions?
 
If the perceived consequences to the clinician are small, what is the incentive for t hem to take the time to try to be more accurate and timely in our diagnoses?
 
Thanks again Peter
Bob
 
Robert J. Latino, CEO
Reliability Center, Inc.
1.800.457.0645
blatino at reliability.com <mailto:blatino at reliability.com>
www.reliability.com <http://www.reliability.com/>
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From: Elias Peter [mailto:pheski69 at GMAIL.COM <mailto:pheski69 at GMAIL.COM>] 
Sent: Wednesday, February 21, 2018 1:32 PM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG <mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
Subject: Re: [IMPROVEDX] NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.
 
I understood the question to be, “What are the consequences TO THE DOCTOR for not making an accurate diagnosis the first time?"
 
Having to admit “I don’t know” and run the risk of feeling competent or being considered incompetent but the patient.
In a training setting (medical student, resident, fellow) there is the risk of being criticized by supervisors.
In a clinical setting, there is the risk of being criticized or thought less of by colleagues, or harm to reputation.
There is the concern about legal risk if negative consequences result from the delay.
 
Forty years as a primary care clinician led me to see this issue in somewhat separable clumps:
 
The infinitesimally small number of cases where there were dire medical consequences for not knowing what it is and what to do, right now, this instant, in real time. OB is the classic example, with things like unsuspected breech or shoulder dystocia during delivery, or an obtunded newborn. 
The larger but still quite small number of cases where one is unlikely to get a second try but seconds and minutes do not count. 
The big chunk where first-pass diagnosis makes you feel good but doesn’t change the outcome. (A case of cutaneous anthrax is one I remember.)
The very large chunk (I’d guesstimate 60% or more) where an accurate diagnosis cannot be made on the first pass without doing a large number of inappropriate tests - where time and the natural history are the best diagnostic tools. This applies to much of rheumatology, many non-specific but common symptoms: fatigue, pruritus, constipation, nausea, weight loss, insomnia, dizziness, various mood and behavior disorders, pain without findings on exam.
 
But, in response to the question posed by Bob Latino, I think the consequences to the clinician are generally small. (This does not apply to all areas of medicine, of course.)
 
Peter
 
On 2018.02.21, at 9:54 AM, Grubenhoff, Joe <Joe.Grubenhoff at CHILDRENSCOLORADO.ORG <mailto:Joe.Grubenhoff at CHILDRENSCOLORADO.ORG>> wrote:
 
I think that is condition-specific. If it’s sepsis or impending cardiac arrest from an OD, then the negative consequence is massive. If it’s pediatric lupus a few weeks to months is probably not catastrophic for the patient. The potential negative consequence to trying always be accurate on the first patient encounter is over-testing, unnecessary testing and astronomically skyrocketing cost.
 
Case in point: Mother brings in her well-appearing toddler with fever for 2-3 hours. No other symptoms. The possible causes are effectively (not literally) infinite and I can’t test for all of them. I can order a CBC which tells me nothing of the source or nothing at all if normal. I can order blood cultures (knowing that the ratio of true infection to contaminant is around 1:5 to 1:7). I could shoot a CXR to assess for occult pneumonia, cath the child for urine culture, etc. etc. I can use a shotgun approach and be no closer to a diagnosis after a 3 hour ER stay but have exposed the patient to a number of harms (pain, radiation, dysuria, possibly introducing an infection).
 
We have to balance the negative consequences of missing a dx with the negative consequences of searching for absolute certainty. And we have to explain the ambiguity to our patients. Lastly we need to help them understand that in many cases, time is a diagnostic test.
 
From: Bob Latino [mailto:blatino at RELIABILITY.COM <mailto:blatino at RELIABILITY.COM>] 
Sent: Wednesday, February 21, 2018 9:43 AM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG <mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
Subject: Re: [IMPROVEDX] NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.
 
Outsider question that may be obvious to you experts:  
 
What is the negative consequence to the doctor for not making an accurate diagnosis the first time?

Sent from my iPhone

On Feb 21, 2018, at 11:40 AM, Elias Peter <pheski69 at GMAIL.COM <mailto:pheski69 at GMAIL.COM>> wrote:

Some years ago, I wrote a short blog piece about my approach to teaching FP residents to question both their diagnosis and their certainty:
 
http://petereliasmd.com/node/10 <http://petereliasmd.com/node/10>
 
 
Peter Elias, MD
 
 
On 2018.02.21, at 6:44 AM, Joe Graedon <jgraedon at GMAIL.COM <mailto:jgraedon at GMAIL.COM>> wrote:
 
Bill,
 
You are a very insightful mentor and teacher. The problem is that in our time-challenged environment “discordant data” are often ignored or overlooked. Please take time to read Larry Weed’s brilliant book, Medicine in Denial. You will quickly appreciate that Art has brought Dr. Weed’s vision to reality. 
 
On another note, we were thrilled to see that patient engagement is now a priority for ImproveDX. When patients and family members are considered equal players in the diagnostic process we could see real advances in what has been a challenging dilemma. 
 
Joe Graedon
The People’s Pharmacy

Sent from my iPad

On Feb 19, 2018, at 12:14 PM, Follansbee, William <follansbeewp at UPMC.EDU <mailto:follansbeewp at UPMC.EDU>> wrote:

Art,
 
I agree with your thoughtful comments. I would also add, however, that for a disease like cellulitis, which I agree is frequently over diagnosed and treated unnecessarily, the answer is not going to be in decision support tools. Clinicians are just not going to consult them for such a common diagnosis. It is also to teach them how to be a little more thoughtful and analytic in their bedside decision making.   We teach trainees to use small groups of common sense but not uncommonly overlooked questions at appropriate times in the diagnostic process in a systematic fashion. In this context, one question we emphasize that they should ask themselves when considering a diagnosis is, “is there any discordant data?” Cellulitis is rarely bilateral yet many patients admitted and treated for apparent cellulitis have red and swollen legs bilaterally, ie discordant findings.  If their illness script for cellulitis includes bilateral disease, then that is a knowledge problem that also has to be addressed.
 
Best,
Bill
 
 
William P. Follansbee, M.D., FACC, FACP, FASNC
The Master Clinician Professor of Cardiovascular Medicine
Director, The UPMC Clinical Center for Medical Decision Making
Suite A429 UPMC Presbyterian
200 Lothrop Street
Pittsburgh, PA 15213
Phone: 412-647-3437
Fax: 412-647-3873
Email: follansbeewp at upmc.edu <mailto:follansbeewp at upmc.edu>
 
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This email may contain confidential information of the sending organization. Any unauthorized or improper disclosure, copying, distribution, or use of the contents of this email and attached document(s) is prohibited. The information contained in this email and attached document(s) is intended only for the personal and confidential use of the recipient(s) named above. If you have received this communication in error, please notify the sender immediately by email and delete the original email and attached document(s).
 
 
 
From: Art Papier [mailto:apapier at VISUALDX.COM <mailto:apapier at VISUALDX.COM>] 
Sent: Monday, February 19, 2018 11:17 AM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG <mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
Subject: Re: [IMPROVEDX] NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.
 
Likewise VisualDx had Schnitzler’s at the top of the differential, but as much as I agree that all physicians need to understand and use point of care diagnostic decision support, we should recognize that relatively rare diseases like Schnitzler are uncommon and relatively easy for decision support to “pick up”.   The real need is to handle the cases when clinicians do not know they need help, but do need help.  How do you know what you don’t know?  Uncommon diseases are uncommon, and therefore variants of common are much more common that rare diseases.   Our real challenge in decision support is to provide tools that also provide useful and valuable content around the common, and more particularly with the variants of the common so clinicians have decision support top of mind.  80-20 rule:  If 80% of diagnoses are common, then it is reasonable to assume that variants of the 80% dwarf the super rare diseases in number.  It is also safe to assume that clinicians who are in a constant rush, and bogged down by mind-numbing EHR charting exercises, will question the efficiency of using these tools.  We are focused on variation in disease presentation in our work with the goal of expanding the use of decision support beyond use for seemingly rare presentations.  We belive that the memory based training and care delivery system creates self-fulfilling prophecies where clinicians ask questions around the “classic presentation disease” scripts they memorize, but do not know the questions to ask around the related variants.  As an example,  over 100,000 people are admitted to hospitals each year for cellulitis when they do not have cellulitits.  This is a boring “story” for decision because cellulitis is common, but there is so much harm happening just from error around this single diagnosis.  How do we bend this curve and reduce unnecessary admissions while recognizing all true positives?   By focusing on commn diseases and their variants we can expand the use of decision support.  
 
Thanks to Lisa for another wonderfully written great case and prompting discussion at SIDM !
Art
 
Art Papier MD
CEO VisualDx
Associate Professor of Dermatology and Medical Informatics
University of Rochester
From: Edward Hoffer [mailto:ehoffer at GMAIL.COM <mailto:ehoffer at GMAIL.COM>] 
Sent: Sunday, February 18, 2018 6:40 PM
To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG <mailto:IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
Subject: Re: [IMPROVEDX] NYTimes: Her Various Symptoms Seemed Unrelated. Then One Doctor Put It All Together.
 
This story makes a very good case for the use of computer-based diagnostic decision support systems. I entered the findings into the one with which I work, DXplain, and Schnitzler's came in ranked #1 I did not try Isabel, but would not be surprised if it also had the correct diagnosis near the top. Much easier than spending the reported "hours" in PubMed that the hero expended to arrive at the correct diagnosis.
Ed
Edward P Hoffer MD, FACC, FACP
 
On Sun, Feb 18, 2018 at 9:16 AM, Joe Graedon <jgraedon at gmail.com <mailto:jgraedon at gmail.com>> wrote:
https://www.nytimes.com/2018/02/14/magazine/her-various-symptoms-seemed-unrelated-then-one-doctor-put-it-all-together.html?smprod=nytcore-ipad&smid=nytcore-ipad-share <https://www.nytimes.com/2018/02/14/magazine/her-various-symptoms-seemed-unrelated-then-one-doctor-put-it-all-together.html?smprod=nytcore-ipad&smid=nytcore-ipad-share>

Chills, sweats, hives, achey bones — the older woman was sick for years before someone figured out the unusual disease that ailed her.


Sent from my iPad
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