What Does Carl Sagan's Observation About The Effects of Medicine Really Mean?

I started reading Carl Sagan's book The Demon Haunted World based on what I heard about it on Twitter.  Of course I was very familiar with his work based on his television persona but none of his writings. Part of the way in, I ran across the above quote as a footnote on page 13. It hit me immediately based both on my personal medical care and also the thousands of people I have assessed over the years.  There was also a clear contrast with what is in the popular and professional press.  The media has been obsessed with metrics of medical systems for various reasons. First, it is sensational.  When they can get a hold of a controversial statistic like the estimated number of people killed by medical interventions every year.  Change that to the equivalent number of 757 crashes per year and you have a hot headline.  Second, generalizations about the quality of health care lack granularity and precision.  There are no epidemiological studies that I am aware of that can even begin to answer the question he asked at the dinner party.

From a research standpoint, researching this endpoint would take an unprecedented level of detail. Standard clinical trials, epidemiological studies, and public health statistics look at mortality as an outcome typically of few variables and limited age groups. Nobody publishes any clear data on avoiding mortality - often many times over the course of a lifetime.  The same is true about avoided morbidity. Researchers seem focused on binary outcomes - life or death, cured or ill, recovered or permanently disabled.

The closest literature seems to be the way that chronic illnesses accumulate over time but that endpoint is not as striking as a mortality endpoint.  Every study that I have seen looks at specific cause of mortality or a collection of similar causes and not all possible causes.  The best longitudinal data I have found is in a graph in this article in the Lancet (see figure 1).  Please inspect this graph at the link and notice the trend in the number of chronic illnesses and how they increase with age.  The population studied here was in Scotland.  This is very impressive work because as far as my research goes I can find no other graph of chronic illnesses with this level of detail.  Data in the US have very crude age groups and the number of chronic illness is often limited.  If I look at CMS data for Medicare beneficiaries 34.5% have 0-1 chronic medical conditions, 29.5% have 2-3 conditions, 20.7% have 4 to 5 conditions, and 15.3 have 6+ conditions.  By selecting certain age groups the percentages change in the expected directions.  For example, looking at beneficiaries less than 65 years of age, 45% have 0-1 conditions and 11.2% have 6+ conditions.

Chronic conditions are the most significant part of medical effort and expenditure, but as indicated in Sagan's quote - they are only a part of the medical experience of people across their lifetimes. Now that some previously fatal conditions are being treated as chronic conditions the demarcation between morbidity and mortality is blurred even further. The experience of being treated and cured for a potentially fatal illness is left out of the picture.  Being treated and cured from multiple fatal conditions over the course of a lifetime is also not captured.  Two common examples are acute appendicitis and acute cholecystitis.   These diagnoses alone account for 280,000 appendectomies and 600,000 cholecystectomies each year. The vast majority of those people go on to live normal lives after the surgery.  Those surgical treatments are just a portion of the surgery performed each year that is curative and results in no further disability and in many situations the prevention of significant mortality and morbidity.  A more complete metric of life saving, disability preventing, and disease course modification would be most useful to determine what works in the long run and where the priorities should be.

One way to get at those dimensions would be to look at what I would call the Sagan Index.  Since I am sure that there are interests out there licensing and otherwise protecting Carl Sagan's name I am going to use the term Astronomer Index instead - but make no mistake about it - the concept is his.

I have included an initial draft of what this index might look like in the supplementary notes below.  Higher number correlates with the number of times a life has been saved or disability prevented.  Consider the following example - an average guy in his 60s.  When I take his history he recalls being hospitalized for anaphylaxis at age 16 and a gangrenous appendix at 19.  With the appendectomy he has a Penrose drain in his side and had a complicated hospital stay.  He traveled to Africa in his 20's where he got peptic ulcer disease, malaria and 2 additional episodes of anaphylaxis from vaccines that he was allergic to. When he was 42 he had an acute esophageal obstruction and needed an emergency esophagoduodenoscopy. At age 45 he insisted on treatment for hypertension.  At 50 he had polysomnography, was diagnosed with obstructive sleep apnea (OSA) and treated with continuous positive airway pressure (CPAP). At age 55 he had multiple episodes of atrial fibrillation and needed to be cardioverted twice.  He is on long term medication to prevent atrial fibrillation.  At age 60 he had an acute retinal detachment and needed emergency retinal surgery.  At age 66 he needed prostate surgery because of prostatic hypertrophy and urinary tract obstruction.  Assigning a point for either saving his life or preventing disability would yield a Astronomer Index of 11.  In 5 of these situations he was likely dead without medical intervention (3 episodes of anaphylaxis, gangrenous appendix, and acute esophageal obstruction)  and in the other six he would be partially blind, acutely ill with a urinary tract obstruction and possible renal failure, experiencing the cardiac side effects (or sudden death) from OSA, or possibly a stroke with disabling neurological deficits from the untreated atrial fibrillation. The index would take all of these situations into account as well as life threatening episodes of psychiatric illness or substance use.

Compare the Astronomer Index (AI) to all of the media stories about the number of medical errors that kill people.  Preventing medical errors is an essential goal but it really does not give the average person a measure of how many times things go right.  When I see stories about how many planes full of people die each year because of medical errors I think of a couple of things.  The first is a NEJM article that came out in response to the IOM estimate of people dying from medical errors.  It described the progress that had been made and what problems might be associated with the IOM report.  The second thing I think of is the tremendous number of saves that I have seen in the patients I treat.  I have to take a comprehensive medical history on any new patients that I assess and I have talked with many people who would score very highly on the AI.

Another aspect of treatment captured by this index would be the stark reality of medical treatment. The vast majority of people realize this and do not take any type of medical treatment lightly. There is a broad array of responses to these decisions ranging from rational decision making to denying the severity of the problem. Everyone undergoing medical treatment at some point faces a decision with varying degrees of risk. That should be evident from the current television direct-to-consumer pharmaceutical ads that rapidly list the serious side effects including death every time the commercial runs.  The decisions that people make also have to answer the serious question of what their life would be like without the treatment and associated risk. There are no risk free treatments as far as I know. In the case of the hypothetical patient, he has taken at least 11 significant risks in consenting to medical and surgical treatment that have paid off by living into his seventh decade.

I have not seen any metric like AI applied across the population.  Certainly there are many people who make it into their 60s and have fewer problems than in our example but there are also many who have more and actual disability.  The available epidemiology of chronic, cured, and partially cured conditions is extremely limited and I don't see anything that comes close to a metric that captures an individuals lifetime experience like the AI index might.  The rate of change in the index over the lifespan of the individual and across different populations might provide detailed information important for both prevention and service provision. In terms of psychiatric treatment - a good research question would be the response of people to treatment for psychiatric or substance use disorders with high scores on the index to people with low scores. Is there a potential correlation with cognitive decline?

The bottom line for me is that life is hard and most of us sustain considerable damage to our organism over the course of a lifetime.  Only a small portion of that is covered in most medical and epidemiological studies.  This index might provide the needed detail.  It might also provide some perspective on how many times each of us need serious medical treatment over the course of a lifetime.


George Dawson, MD, DFAPA


Reference:

1. Karen Barnett, Stewart W Mercer, Michael Norbury, Graham Watt, Sally Wyke, Bruce Guthrie,
Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study, The Lancet, Volume 380, Issue 9836, 2012, Pages 37-43,

Supplementary:

A copy of the Astronomer Index (AI) is shown below:

Morning Report

I don't know if they still call it that or not - but back in the day when I was an intern Morning Report was a meeting of all of the admitting residents with the attendings or Chief of Internal Medicine.  The goal was to review the admissions from the previous night, the initial management, and the scientific and clinical basis for that management. Depending on where you trained, the relationship between house staff and attendings could be affiliative or antagonistic. In affiliative settings, the attendings would guide the residents in terms of management and the most current research that applied to the condition. In the antagonistic settings, the attendings would ask an endless series of questions until the resident presenting the case either fell silent or excelled.  It was extremely difficult to excel because the questions were often of the "guess what I am thinking" nature. The residents who I worked with were all hell bent on excelling.  After admitting 10 or 20 patients they would head to the library and try to pull the latest relevant research.  They may have only slept 30 minutes the night before but they were ready to match wits with the attendings in the morning.

Part of that process was discussing the relevant literature and references.  In those days there were often copies of the relevant research and beyond that seminar and research projects that focused on patient care. I still remember having to give seminars on gram negative bacterial meningitis and anaphylaxis.  One of my first patients had adenocarcinoma of unknown origin in his humerus and the attending wanted to know what I had read about it two days later.  I had a list of 20 references. All of that reading and research required going to a library and pulling the articles in those days.  There was no online access.  But even when there was - the process among attendings, residents, and medical students has not substantially changed.

I was more than a little shocked to hear that process referred to as "intuition based medicine" in a recent opinion piece in the New England Journal of Medicine (1).  In this article the authors seem to suggest that there was no evidence based medicine at all.  We were all just randomly moving about and hoping to accumulate enough relevant clinical experience over the years so that we could make intuitive decisions about patient care.  I have been critical of these weekly opinion pieces in the NEJM for some time, but this one seems to strike an all time low. Not only were the decisions 35 years ago based on the available research, but there were often clinical trials being conducted on active hospital services - something that rarely happens today now that most medicine is under corporate control.

Part of the author's premise here is that evidence-based medicine (EBM) was some kind of an advance over intuition-based medicine and now it is clear that it is not all that it is cracked up to be. That premise is clearly wrong because there was never any intuition based medicine before what they demarcate as the EBM period. Secondly, anyone trained in medicine in the last 40 years knew what the problems with EBM were from the outset - there would never be enough clinical trials of adequate size to include the real patients that people were seeing.  I didn't have to wait to read all of the negative Cochrane Collaboration studies saying this in their conclusions.  I knew this because of my training, especially training in how to research problems relevant to my patients. EBM was always a buzzword that seemed to indicate some hallowed process that the average physician was ignorant of.  That is only true if you completely devalue the training of physicians before the glory days of EBM.

The authors suggest that interpersonal medicine is what is now needed. In other words the relationship between the physician and patient (and caregivers) and their social context is relevant.  Specifically the influence the physician has on these folks.  Interpersonal medicine "requires recognition and codification of the skills that enable clinicians to effect change in their patients, and tools for realizing those skills systematically." They see it as the next phase in "expanding the knowledge base in patient care" extending EBM rather than rejecting it.  The focus  will be on social and behavioral aspects of care rather than just the biophysical. The obvious connection to biopsychosocial models will not be lost on psychiatrists.  That is straight out of both interpersonal psychotherapy (Sullivan, Klerman, Weissman, Rounsaville, Chevron) and the model itself by Engel.  Are the authors really suggesting that this was also not a focus in the past?

Every history and physical form or dictation that I ever had to complete contained a family history section and a social history section.  That was true if the patient was a medical-surgical patient or a psychiatric patient.  Suggesting that the interpersonal, social, and behavioral aspects of patient care have been omitted is revisionism that is as serious as the idea of intuition based medicine existing before EMB.

I don't understand why the authors just can't face the facts and acknowledge the serious problems with EBM and the reasons why it has not lived up to the hype.  There needs to be a physician there to figure out what it means and be an active intermediary to protect the patient against the shortfalls of both the treatment and the data. As far as interpersonal medicine goes that has been around as long as I have been practicing as well.  Patients do better with a primary care physician and seeing a physician who knows them and cares for them over time. They are more likely to take that physician's advice.  Contrary to managed care propaganda (from about the same era as EBM) current health care systems fragment care, make it unaffordable, and waste a huge amount of physician time taking them away from relationships with patients.

Their solution is that physicians can be taught to communicate with patients and then measured on patient outcomes.  This is basically a managed care process applied to less tangible outcomes than whether a particular medication is started. In other words, it is soft data that it is easier to blame physicians for.  In this section they mention that one of the author's works for Press Ganey - a company that markets communication modules to health care providers. I was actually the recipient of such a module that was intended to teach me how to introduce myself to patients. The last time I took that course was in an introductory course to patient interviewing in 1978.  I would not have passed the oral boards in psychiatry in 1988 if I did not know how to introduce myself to a patient.  And yet here I was in the 21st century taking a mandatory course on how to introduce myself after I have done it tens of thousands of times.  I guess I have passed the first step toward the new world of interpersonal medicine.  I have boldly stepped beyond evidence based medicine.   

I hope there is a lot of eye rolling and gasping going on as physicians read this opinion piece.  But I am also concerned that there is not. Do younger generations of physicians just accept this fiction as fact?  Do they really think that senior physicians are that clueless?  Are they all accepting a corporate model where what you learn in medical school is meaningless compared to a watered down corporate approach that contains a tiny fraction of what you know about the subject?

It is probably easier to accept all of this revisionist history if you never had to sit across from a dead serious attending at 7AM, present ten cases and the associated literature and then get quizzed on all of that during the next three hours of rounding on patients.
 



George Dawson, MD, DFAPA


References:

1: Chang S, Lee TH. Beyond Evidence-Based Medicine. N Engl J Med. 2018 Nov 22;379(21):
1983-1985. doi: 10.1056/NEJMp1806984. PubMed PMID: 30462934.


Graphic Credit:

That is the ghost of Milwaukee County General Hospital one of the teaching affiliates of the Medical College of Wisconsin.  It was apparently renamed Doyne Hospital long after I attended  medical school there.  It was demolished in 2001.  I shot this with 35mm Ektachrome walking to medical school one day. The medical school was on the other side of this massive hospital.

What Isn't Available In Multimillion Dollar EHRs? Decision Support from 1994

Physician Decision Support Software from the 20th Century

I used to teach a class in medical informatics. My emphasis was not mistaking a physical illness for a psychiatric one and also not missing any medical comorbidity in identified psychiatric patients.  The class was all about decision-making, heuristics, and recognition of biases that cause errors in medical decisions. Bayesian analysis and inductive reasoning was a big part of course. About that time, software packages were also available to assist in diagnostic decisions. Some of them had detailed weighting estimates to show the relative importance of diagnostic features.  It was possible to enter a set of diagnostic features and get a listing of probable diagnoses for further exploration. I printed out some examples for class discussions and we also reviewed research papers and look at the issue of pattern recognition by different medical specialists.

The available software packages of the day were reviewed in the New England Journal of Medicine (1).  In that review, 10 experts came up with 15 cases as written summaries and then those cases were cross checked for validity and pared down to 105 cases.  The four software programs (QMR, Iliad, Dxplain, and Meditel) were compared in their abilities to suggest the correct diagnosis. Two of programs used Bayesian algorithms and two used non-Bayesian algorithms. The authors point out that probability estimates varied based on literature clinical data used to establish probabilities. In the test, the developers of each program were used to enter the diagnostic language and the compared outcomes were the list of diagnoses produced by each program. The diagnoses were rank ordered according likelihood.

The metrics used to compare the programs was correct diagnosis, comprehensiveness (in terms of the differential diagnosis list generated), rank, and relevance.  Only 0.73-0.91 of the programs had all of the cited diagnoses in the knowledge base. Of the programs 0.52 - 0.71 made the correct diagnosis across all 105 cases and 0.71-0.89 made the correct diagnosis across 63 cases.  The 63 case list was used because those diagnoses were listed in all 4 knowledge bases.  The authors concluded the lists generated had low sensitivity and specificity but that unique diagnoses were suggested that the experts agreed may be important. They concluded that the performance of these programs in clinical settings being used by physicians was a necessary next step. They speculated that physicians may use these programs beyond generating diagnoses but also looking at specific findings and how that might affect the differential diagnosis.

A study (2) came out five years later that was a direct head-to-head comparison of two different physicians using QMR software to assess 154 internal medicine admissions where there was no known diagnosis.  In this study physician A obtained the correct diagnosis in 62 (40%) cases and physician B was correct in 56 (36%) of the cases. That difference was not statistically significant. Only 137 cases had the diagnosis listed in the QMR knowledge base. Correcting for that difference, correct diagnoses increased to 45% for physician A and 41% for physician B. The authors concluded that a correct diagnosis Listed in the top five diagnoses 36 to 40% of the time was not accurate enough for a clinical setting, but they suggested that expanding the knowledge base would probably improve that rate.

Since then the preferred description of this software has become differential diagnosis generators (DDX) (3.4). A paper from 2012, looked at a total of 23 of these programs but eventually included only 4 for in their analysis. The programs were tested on ten consecutive diagnosis-focused cases chosen from from 2010 editions of the Case Records of the New England Journal of Medicine (NEJM) and the Medical Knowledge Self Assessment Program (MKSAP), version 14, of the American College of Physicians. A 0-5 scoring system was developed that encompassed the range of 1= diagnosis suggested on the first screen or first 20 suggestions to 5= no suggestions close to the target diagnosis. The scoring range was 0-50. Two of the programs exactly matched the diagnosis 9 and 10 times respectively. These same two programs DxPlain and Isabel had identical mean scores of 3.45 and were described as performing well. There was a question of integration with EHRs but the authors thought that these programs would be useful for education and decision support. They mention a program in development that automatically incorporates available EHR data and generates a list of diagnoses even without clinician input.

The most recent paper (4) looked at a a systemic review and meta-analysis of differential diagnosis (DDX) generators. In the introductory section of this paper the authors quote a 15% figure for the rates of diagnostic errors in most areas of medicine. A larger problem is that 30-50% of patients seeking primary care or specialty consultation do not get an explanation for their presenting symptoms. They looked at the ability to generate correct lists of diagnosis, whether the programs were as good as clinicians, whether the programs could improved the clinicians list of differential diagnoses, and the practical aspects of using DDX generators in clinical practice. The inclusion criteria resulted in 36 articles comparing 11 DDX programs (see Table 2.)  The original paper contains a Forest Plot of the results of the DDX generators showing variable (but in some cases high) accuracy but also a high degree of heterogeneity across studies.  The authors conclude that there is insufficient evidence to recommend DDX generators based on the variable quality and results noted in this study.  But I wonder if that is really true.  Some of the DDX generators did much better than others and one of them (Isabel) refers to this study in their own advertising literature.

My main point in this post is to illustrate that these DDX generators have been around for nearly 30 years and the majority of very expensive electronic health record (EHR) installations have none.  The ones that do are often in systems where they are actively being studied by physicians in that group or one has been added and the integration in the system is questionable.  In other words, do all of the clinical features import into the DDX generator so that the responsible clinician can look at the list without making that decision.  At least one paper in this literature suggests that eliminates the bias of deciding on whether to not to make the decision to use diagnostic assistance.  In discussion of physician workflow, it would seem that would be an ideal situation unless the software stopped the workflow like practically all drug interaction checking software.

The drug interaction software may be a good place to start. Some of these program and much more intelligent than others. In the one I am currently using trazodone x any serotonergic medication is a hard stop and I have to produce a flurry of mouse clicks to move on.  More intelligent programs do not stop the workflow for this interaction of SSRI x bupropion interactions.  There is also the question of where artificial intelligence (AI) fits in.  There is a steady stream of headlines about how AI can make medical diagnoses better than physicians and yet there is no AI implementation in EHRs designed to assist physicians.  What would AI have to say about the above drug interactions? Would it still stop my work process and cause me to check a number of exception boxes? Would it be able to produce an aggregate score of all such prescriptions in an EHR and provide a probability statement for a specific clinical population?  The quality of clinical decisions could only improve with that information. 

And there is the issue of what psychiatrists would use a DDX generator for?  The current crop has a definite internal medicine bias.  Psychiatrists and neurologists need an entirely different diagnostic landscape mapped out.  The intersection of psychiatric syndromes, toxidromes and primary neurological disorders needs to be added and expanded upon. As an experiment, I am currently experimenting with the Isabel package and need to figure out the best way to use it.  My experimental paradigm is a patient recently started on lithium who develops an elevated creatinine, but was also started on cephalexin a few days after the lithium was started.  Entering all of those features seems to produce a random list of diagnoses and the question of whether an increasing creatinine is due to lithium or cephalexin.  It appears that the way the diagnostic features are entered may affect the outcome.

Decision support is supposed to be a feature of the modern electronic health record (EHR). The reality is the only decision support is a drug interaction feature that varies greatly in quality from system to system. Both the drug interaction software and DDX generators are very inexpensive options for clinicians.  EHRs don't seem to get 1990s software right.  And it does lead to the question: "Why are EHRs so expensive and why do they lack appropriate technical support for physicians?" 

Probably because they were really not built for physicians.



George Dawson, MD, DFAPA


References:

1: Berner ES, Webster GD, Shugerman AA, Jackson JR, Algina J, Baker AL, Ball EV, Cobbs CG, Dennis VW, Frenkel EP, et al. Performance of four computer-based diagnostic systems. N Engl J Med. 1994 Jun 23;330(25):1792-6. PubMed PMID:8190157.

2: Lemaire JB, Schaefer JP, Martin LA, Faris P, Ainslie MD, Hull RD. Effectiveness of the Quick Medical Reference as a diagnostic tool. CMAJ. 1999 Sep 21;161(6):725-8. PubMed PMID: 10513280.

3: Bond WF, Schwartz LM, Weaver KR, Levick D, Giuliano M, Graber ML. Differential diagnosis generators: an evaluation of currently available computer programs. J Gen Intern Med. 2012 Feb;27(2):213-9. doi: 10.1007/s11606-011-1804-8. Review. PubMed PMID: 21789717.

4: Riches N, Panagioti M, Alam R, Cheraghi-Sohi S, Campbell S, Esmail A, Bower P.The Effectiveness of Electronic Differential Diagnoses (DDX) Generators: A Systematic Review and Meta-Analysis. PLoS One. 2016 Mar 8;11(3):e0148991. doi: 10.1371/journal.pone.0148991. eCollection 2016. Review. PubMed PMID: 26954234.

Exploits on the Internet

I received the above at my work email address last week.....

I have always been unimpressed with the idea of computer hackers for a number of reasons, the most obvious ones are contained in the above email.  Apart from the obvious extortion, their ability reach out and ruin the day for anybody through any number of mechanisms is a major problem.  I was concerned to some degree about the threat based on me watching porn videos because it would be fairly easy to make it appear that I did it using any split screen video app.  Some online research revealed that there is a hack for Mac cameras.  It might be easy to get a video of me on the computer and then pair it with any pornography video.  

My dealing with identity thieves illustrated how easy it is for criminals to remain anonymous in our society while average citizens deal with their mischief.  I was called at work by a very aggressive person working for a collection company who claimed that I owed them $10,000.  Investigation showed that an identity thief opened a fake credit card based on my Social Security Number and ran up the charges.  I filed a police report and was advised by the local police that it was unlikely that anything would happen, but that the report was necessary in order to file an affidavit with the credit card company to avoid paying the charges.  I was eventually able to track the thief to a Florida address and called the local Sheriff to investigate.  I was told that the Sheriff would not look into it because "anybody could have used that mailbox and it would be an invasion of privacy." It became clear that identity theft was just the cost of doing business for credit card companies and credit reporting agencies - regardless of the cost and time to the consumer.

The source of my of the hacking exploitation is infuriating and that of course is poor computer security.  What is never really made explicit is the reason for the lack of security. It was certainly never really designed in.  Apple claims that it is and they have a detailed explanation about this in their literature.  On the other hand Microsoft operating systems dominate the individual and corporate PC worlds.  If you are going where the money is - it will probably involve a Microsoft OS.  It seems that every Microsoft upgrade involves a raft of new security problems and when they have a stable OS - it gets upgraded and the old stable version gets unsupported anyway.  I suppose you can't make a lot of money on a product that you never upgrade. A lot of the security problems rest with the software manufacturers.

There is the software security industry.  Large companies that make antiviruses, firewalls, malware detectors, and pass word managers.  A dizzying array of free and in some cases fairly expensive software with the guarantee that none of it is foolproof - it might not work at all.  As an example, I was looking at the new collection of password managers for keylogger protection.  The above note describes a keylogger and that is software that records your keystrokes and sends them back to the hacker so that they can discover your passwords and account numbers/logins and steal from you.  Keyloggers can also take screen shots to get similar information. The password managers may or may not protect you against that.

The average computer user seems to pay a premium price for a computer with not very good security and an additional price for software that may or may not add much security.

By default we are left with a semblance of security at our own hands.  The common advice is to not open any email from an unknown source.  Email is a common way that malware and viruses are introduced to computers in large systems with extreme results.  It may allow hacker access to information or in the extreme case hijack the entire system until a ransom is paid to unlock it.  In the case of the message sent to me - I am sitting behind a corporate firewall  that seems to intercept even benign messages and send me a report so that I can decide which one should be deleted and which should be released.  This message sailed right through! 

All of the lack of reasonable security results in the possibility of scaling the criminal enterprise.  Now instead of blackmailing a person who may be engaged in some activity that they don't want anyone to know about - the enterprising Internet criminal can send out thousands or tens of thousands of these messages - just playing the odds. The impact on the other 90% is completely ignored.   

All of the security fixes so far ignore the basic problem of who is basically creating all of this chaos. I did an PubMed search on hacker(s) and came up with 90 references dating back to 1986.  None of them were what I would consider to be scientific papers. Most were opinion pieces either warning about threats or advice on how to secure your data or network against threats. Many were from non-mainstream journals.  

I am also a member of the IEEE and when I check their web site, there are 240,000,000 references to hackers.  Hackers psychology as a search term results in 4.182 million references.  Going to the IEEExplore digital library results in 10 hits - 4 from journals and magazines and 6 from conferences.   The professional literature available to me does not seem to be much of an improvement over what is available in the popular press.  In the popular press there are some articles speculating on who the hackers are and what their various motivations are.  For example, an article discusses how some teenage boys become obsessed with hacking and with time and a singular focus can hack like anyone.  There are stories of American teenagers hacking the American government including military institutions and Russian teenagers being praised by Putin for stealing money from American bank accounts.  An article suggests that these teenagers eventually grow out of it when they recognize it is wrong.  One story suggests that the hacking obsessed teens are on the Autism Spectrum - they have Asperger's syndrome.  There are appeals to come up with a multidisciplinary approach to studying hackers and why the social sciences are important in the effort.  There is a suggestion that some of these programs are out there in the security industry and law enforcement - but nothing very compelling.   

Hackers have a large footprint in popular media.  The average television program suggests that a good hacker has instant access to whatever information they need.  That can range from any video feed to any blueprint to any financial information in any city.  That is an obvious stretch, but that is the way things are portrayed.  A study of how many media portrayals are of white hat versus black hat hackers (the old western terminology applies) might be interesting.  My impression is that most are white hat by a large margin.  And then there are the hacker antiheroes, most notably Eliott Alderson of Mr. Robot and his sister Darlene.  Nothing in the media portrayals to suggest that cybercrime in the US costs an estimated $350-500 billion annually.

I sincerely hope that there is a vast network of concerned cybersecurity experts, that are acting rationally on these threats.  I confess that I am not very confident that there is. The idea that a private contractor can access top secret government files and send them around the Internet suggests to me that even our top intelligence agencies may not know much more about protecting their systems than I do. 

Coming back to the graphic, my overriding concern is that there are tens of thousands of people out there like the person that sent this email.  They can get close to many more people than they could walking up to them and holding them up on the street, but that doesn't mean they are any less sociopathic.  The dominant dynamic is that they will verbally, emotionally, or physically intimidate  you to get what they want.  That tone is clearly there in this email.  I think network providers and the hardware and software providers can do a lot more.  The most compelling evidence there is the disappearance of pornographic email spam from the early part of the century. At first it was up to the individual user to set up filters to get rid of it and then mysteriously one day - the inbox was free of pornography for good.  They should be able to do the same thing with emails like the example here.

For now every user must stay diligent and do what they can to protect themselves.  A home network specialist that can be consulted about the latest gear and standards helps.  Common sense helps.  At the bottom rung is the idea that not all emails need to be opened or responded to no matter how obnoxious they are.   

George Dawson, MD, DFAPA

Supplementary:

Despite the confusing landscape my experience here highlights a couple of points.

1.  It is critical to change your password/login if a business you access on the Internet gets hacked.  In this case the hacker was able to purchase a 2013 password from an Internet site I frequented on the Dark Web and use it in the first line of the email. That password was available because the company I locked into was hacked exposing the personal information of tens of thousands of users.  This highlights the need for changing passwords immediately when there is a report that an online site has been hacked.

2.  In one of the papers I read about password changes - it turns out that frequent password changes required by many companies result in less secure passwords because employees are annoyed by the changes and the suggested complexity of the passwords. The authors of that paper suggested that frequent changes were unnecessary.

Supplementary:

I am very interested in any scientific research on the psychology of hacking and cybercriminals.  Please post any good references that you have. 

References:

1: Hutson M. Hackers easily fool artificial intelligences. Science. 2018 Jul20;361(6399):215. doi: 10.1126/science.361.6399.215. PubMed PMID: 30026208.

2: Waldrop MM. How to hack the hackers: The human side of cybercrime. Nature. 2016 May 12;533(7602):164-7. doi: 10.1038/533164a. PubMed PMID: 27172030.

3:  Committee on Developing a Cybersecurity Primer: Leveraging Two Decades of National Academies Work, Computer Science and Telecommunications Board, National Research Council; Clark D, Berson T, Lin HS, editors. At the Nexus of Cybersecurity and Public Policy: Some Basic Concepts and Issues. Washington (DC): National Academies Press (US); 2014 Jun 16. PubMed PMID: 25057698.

Unsane - It Sure Is

I watch TV while working out - usually Amazon, Netflix, or HBO.  It is all on the Amazon Fire interface.  Today I saw Unsane advertised and despite my aversion to the ongoing One Flew Over The Cuckoo's Nest portrayals of psychiatry - I decided to watch it on the strength of Claire Foy as the leading actor.  Could the actor save the predictable portrayal?  I was skeptical but forged ahead anyway.  The film was a Steven Soderbergh film and I later learned that he shot it on an iPhone 7 Plus.

In the introductory section we learn that the main character Sawyer Valentini (Claire Foy) has moved from Boston to Pennsylvania.  She is a financial analyst in a bank and does financial analysis and reports.  We see her in a contentious phone call with a client in the opening scene.  He coworker expresses some concern and another coworker looks and rolls his eyes.  She meets with her boss and the conversation has overtones of sexual harassment.  Later there is a computer dating scenario where she ends up at her apartment with the date and starts to react like he is assaulting her.  She ends up taking some medication out of a medicine cabinet.  Later we see her Google "Support groups for stalking victims".  She drives out to a psychiatric facility for an initial appointment and that is where the drama begins.  I am going to list the problems point-by-point.

1.  She meets with the intake staff person and describes her concerns about being stalked as well as the residual "neurosis" (her term) of being in an new city and having a tendency to see her stalker everywhere. At one point she alludes to feeling depressed at times and thinking about whether there is any point in going on.  The staff person asks her if she has ever had suicidal ideation and she goes into a detailed discussion of Therapeutic Index and how she would be experimenting with that if she was going to attempt suicide (translation - overdosing).  The therapist leaves and has her complete routine paperwork.

2.  She completes the "routine paperwork" that is also described as "boilerplate" and learns that in doing so she has voluntarily committed herself for 24 hours.  In other words she was tricked into being hospitalized and that trick was apparently irreversible.

3.  While voicing strong objections she is asked by a nurse to disrobe, be searched, and change into hospital clothing.  The nurse's tone is threatening and she complies.

4.  She is taken to a psychiatric ward of about 10 people.  It is a combination of men and women and they are all locked into a room with no supervision all night long.  She is threatened by the other patients, gets into a physical confrontation with two of them and is eventually sedated in the same 10 bed ward in full view of the other patients with no safety monitoring.  She is subsequently restrained in the same manner in full view of all of the male and female patients and not protected.

5.  She finally sees the psychiatrist the next day.  He does the world's most cursory evaluation - largely reading chart notes in between phone calls.  It lasts about 5 minutes. She makes a compelling argument to be released. He informs her that she needs to stay another 7 days based on her assaults on another patient and staff. At no point in the interview does he ask her any direct questions about depression, suicidal thinking, or the details of the incidents of aggression.

6.  She befriends another patient who has smuggled in a cell phone and convinces him to let her use it.  We learn that the patient with the cell phone is really an undercover reporter investigating the hospital.  She calls her mother who comes to the facility and demands that they release Sawyer. The psychiatrist refers her to an administrator. The administrator gives her an irrelevant sales pitch on all of the good work that is done there and passive-aggressively acknowledges that it is her mother's prerogative to contact an attorney in order to get her daughter freed. 

From a creative and artistic standpoint - it was apparent to me from the outset that Sawyer's reality testing was not impaired.  Hypervigilance is not psychosis. So when she recognized her stalker on the nursing staff passing out medications it was not a surprise.

Spoiler alert right here - if you really wanted to be surprised see another film.  If you don't want to know the ending to this predictable one stop reading right here.

A series of implausible scenes unfold that depend both on the stalker as nursing staff and Sawyer's transformation to homicidality bent on killing the stalker/staff person. The stalker gives Sawyer a "megadose" of methylphenidate a stimulant a - controlled substance. Special effects at that moment seem to indicate she has some kind of psychedelic experience from the drug.  The stalker is warned by the nurse that he has to be more cautious of "we could lose our jobs." The stalker ends up killing two patients and torturing one of them with cardioversion paddles - right out of the old action series 24.  Some reviews of the film think this was an electroconvulsive therapy device - more proof that old Hollywood stereotypes about psychiatry don't ever go away.

The stalker traps Sawyer in an isolated seclusion room and in an excruciatingly long exchange, she tricks him and ends up stabbing him in the neck.  Like most films of this genre, he survives and recaptures her outside of the hospital and kidnaps her.  During the kidnap sequence we learn that he killed her mother and the hospital staff person who he has been impersonating.  Sawyer gets another chance to kill him and apparently does in the most gruesome manner  possible.

We flash forward 6 months and see Sawyer eating at a restaurant with a friend.  She looks out into the room and see the profile of a man who appears to be the stalker. She hears him saying things the stalker would say.  She grabs a steak knife and approaches him from behind.............. 

All of the points above are what a psychiatrist would consider to be highly problematic.  By that I mean they would all merit investigation by the appropriate authorities,  legal penalties, and disciplinary action against licensed health professionals. If I was prone to discuss malpractice - the incidents could also lead to that type of civil litigation.  Anyone experiencing a fraction of what Sawyer experienced in this psychiatric hospital should contact the responsible officials or an attorney about what could be done.  In my experience health officials are quite eager to do exhaustive investigations of these complaints both in the case of licensed health care professionals and institutions.  In the film it took a dead body on the premises to get any action from the police.  In real life, a call from Sawyer's mother would be enough to get action in any state that I have practiced in.

The commitment law in Pennsylvania did not seem to be adequately portrayed.  The statute says that any interested party can initiate commitment based on an imminent dangerousness standard.  That was certainly not present in the film.  At no point was Sawyer suicidal and the brief scraps that she was in would not have required physical restraint or forced medication in any setting that I ever worked in.  The maximum period of confinement in the state of Pennsylvania without a court order is 5 days and in this case Sawyer was detained 1 day initially and then another week.  That is a violation of the law.  In the state where I work, the longest period of time that a person can be help without a court order signed by a judge is 72 hours. In cases where it appeared a high risk person would be released, attorneys have always advised me that the person needs to be released according to the law - no matter what the possible adverse outcome.   

There are some continuity problems with the film.  How is it that her stalker would happen to know that she would be inappropriately admitted to a psychiatric hospital and be able to identify and kill a prospective employee in order to work there?  Wouldn't it be much easier to get close to her in real life rather than inside an institution?  And what about Sawyer?  She has insight into the fact that she is hypervigilant and needs to avoid the stalker. Is there a better film just exploring that theme and what happens to people in these situations plus or minus the real stalker?

In the past, my standard for films has been recognizing that they are entertainment and not really about psychiatry.  This film fails at both levels.  I suppose at some point all actors might be interested in doing a horror movie - but the psychiatric hospital as horror genre is as tiresome as it gets.  How many times can you show a gun toting Dr. Sam Loomis battling evil incarnate as a former asylum patient?   How many times can you show hospital staff that are sadistic, abusive, or grossly incompetent? Apparently there is no limit. The idea that a film like this should just be brushed off as fiction minimizes the fact that One Flew Over the Cuckoo's Nest seems to have stigmatized the most effective treatment in psychiatry for two generations.

The psychiatric hospital that Soderberg is reaching for is the spooky old asylum of the late 19th and early 20th century.  What made that asylum spooky was that people were freaked out about severe mental illness.  They did not know what it was and they did not have a name for the symptoms or disorders. They knew that some of their relatives went to these places and never came back. They lived the rest of their lives there.  They were warehoused and never got better.  That was the real scary part.  Most if not all of those places are shut down and have been for a long time.

The real horror story these days is trying to get into a mental hospital when it is needed.  Contrary to Sawyer's experience in the film, nobody is trying to recruit people into hospitals.  They are rationing the beds and turning people away.  All of the beds are typically full.  The emergency department psychiatric staff will do whatever they can to discharge.  A lot of people end up waiting a day or two and just give up and go home.  In some cases if people with mental problems are brought in by the police, the choice is admission to the hospital or jail.  Jail is the most likely outcome.

Jail is the real scary place these days and it has been for at least 20 years.  That is where a diverted patient needs to worry about incompetent or nonexistent treatment, physical assaults, and encounters with the evil people that Hollywood typically, uses to populate psychiatric hospitals.

The real evil out there today - is the system of non care that exists.  That is what people feared - developing a mental illness for which there was no treatment and being sent away for a lifetime. 

That is what Hollywood needs to understand.

That and a ton about modern psychiatric treatment.


George Dawson,  MD, DFAPA





Graphic Credit:  Inked Pixels.  A ghostly figure casts a long shadow down the middle of a dimly lit passage of a dilapidated mental asylum.  Downloaded from Shutterstock per their standard licensing agreement on 11/12/2018.

The NEJM "Addiction As Learning And Not Disease" Article - Clinical Realities

I had anticipated posting a piece on the biological realities that were minimized in this review but I am currently waiting for a graphic that I acquired permission to use.  I have not heard back from the publisher.  In the interim, I will post some information on the clinical reality of treating people with severe substance use disorders or addictions to illustrate why learning is really an inferior paradigm to use in analyzing the problem.   It really comes down to treating all of the features of a profound loss of normal functioning.  These features are not subtle and include insomnia, anxiety, depression, cravings, compulsive use, and protracted withdrawal.  The following comments considers only those people with addiction that is defined as DSM-5 severe substance use disorder and compulsive use of any addictive substance.  By definition that means I am not considering people with less severe problems, such as the average college drinker or cannabis smoker who lacks these features, can easily stop, and invariably stops when they move on with their life after college.  I could post a series of vignettes but for brevity - I can roll all of those problems into one problem, that is generally recognized as the most significant drug problem in American today and that is opioid use disorder.

Consider the following hypothetical and all of the potential solutions and the implications for addiction as a disease or a learning opportunity.

40 year old man with chronic back pain, benzodiazepine use disorder and opioid use disorder.  Prior to admission he was using 10-16 mg clonazepam per day and 240-300 mg of oxycodone per day for 5 years.  The use disorder developed as a direct result of prescriptions of oxycodone 10 mg TID for back pain and clonazepam 0.5 mg TID for back spasm.  The patient was admitted to a residential treatment facility and detoxified with buprenorphine and phenobarbital over a period of 10 days.  On day 15 he is referred for assessment of depression and anxiety.  

He has no history of insomnia, depression, or anxiety prior to the onset of the substance use problems. Since the detox was completed (on day 10) - his anxiety is "through the roof", he is unable to sleep, and he is depressed and somewhat hopeless.  His concentration and focus are so impaired at this point that he can't retain information presented in groups or individual discussion and he feels like treatment is a "waste of money" because he has not learned anything.  He is craving benzodiazepines but also opioids to some extent.  He has drenching night sweats and has to change his shirt 2 or 3 times a night.  He describes muscle and joint pain.  He is concerned that he will relapse immediately upon discharge due to all of these symptoms.  He asks about taking trazodone for sleep, an antidepressant for depression, and gabapentin for anxiety.  He suggests that if the problem cannot be solved - he will go back to his primary care MD and get another prescription for benzodiazepines and that he will "try to control it this time."  

At this point the best intervention (s) to address these symptoms include (choose as many as you like):

a)  Continued 12-step facilitation groups
b)  Cognitive behavior therapy for insomnia (CBTi)
c)  Cognitive behavior therapy for substance use, anxiety and depression.
d)  A family program to educate the patient and his family about the relevant dynamics
e)  An NA group to deal with cravings
f)  Prescribe trazodone for sleep
g)  Prescribe an SSRI for anxiety and depression
h)  Prescribe gabapentin for anxiety
i)  Prescribe a benzodiazepine for anxiety
j)   Prescribe buprenorphine/naloxone (BUP/NAL) for opioid withdrawal and medication assisted treatment (MAT) of opioid use disorder.

Numerous learning and medical interventions for the problem and I have seen several to most of them applied in this scenario.  I have seen many applied repeatedly well past the point of failure to the point that a person may be leaving treatment more symptomatic than they came in.  That is a significant failure because the patient leaving in that circumstance is highly vulnerable.  This scenario is highlighted generally ion the movement to make sure that persons with opioid use disorder are prescribed BUP/NAL and given naloxone intranasal or injection when they make the transition from treatment setting or secure environments where they have had no access to opioids like jails.  That emphasis is important because of the overdose risk with opioids but the risk for relapse to using any substance requiring treatment is very high and potentially leads to a fatal outcome.

The other clinical consideration of addiction as disease is that it is multidimensional.  As highlighted in this case - it is not a simple question of detox, stabilization and discharge.  Significant physical symptoms of illness, intoxication, and withdrawal can persist well beyond any expected period of detox.  Significant sleep problems can persist for years beyond the detox period.  Striking psychiatric symptoms are all part of the mix and physicians not suspecting these disorders can attempt to treat them as depression, dementia, bipolar disorder, anxiety disorders, panic attacks, and even attention deficit-hyperactivity disorder.  Some treatment literature talks about a vague syndrome of protracted withdrawal symptoms that is often used to described any unusual symptoms or perception during the recovery period.  Addiction is a modern day great imposter of psychiatric disorders.  Clinicians following people with all of these symptoms can discuss general guidelines with people about how long it takes various symptoms complexes to resolve before a psychiatric disorder should be considered.   In some cases the symptoms are of sufficient severity that they need to be treated acutely and the issue of disorder versus disorder cause by the substance needs to be worked out in the long term.

A long standing debate in the treatment of substance use disorders is the role of physicians and medical treatment.  Medicine has always had a role in detoxification especially when it comes to potentially life-threatening detox or detox that involves significant discomfort.  The epidemiology of addictive disorders and psychiatric disorders points to an obvious reason to try to treat both disorders at once and a place for psychiatric treatment. Medication assisted treatment to reduce relapse has been the most recent medical innovation.  All of these roles are consistent with a disease model that seeks to correct or address a loss of normal function in the human body or brain.

I am an advocate of psychosocial therapies not just in addiction, but in just about all areas of psychiatry.  Further I am an advocate of 12-step recovery because it is cost effective, it works, and it has the realistic long term goal of abstinence.  In addiction treatment, those therapies work best if a person is detoxified, cognitively intact, all of the associated comorbid symptoms are treated, and (where possible) craving and relapse potential are reduced as far as possible to break up the cycle of compulsive irrational substance use.

Given all of those considerations what is the correct answer to the question?  None of the verbal therapy or experiential (a though e) options work, but I have seen them applied even when the person was in significant distress and no progress was being made.  There are no known talk therapies that adequately treat intoxication, withdrawal, or many of the intermediate states associated with early recovery that in some cases extend for 1-3 years.  What about the symptomatic treatment of psychiatric symptoms?  Not the best options either.  In this case, I have seen patients on multiple antidepressant, anxiolytics, trazodone, atypical antipsychotics, and even stimulants for the symptoms described.  In many cases the associated medications led to additional morbidity.  So treating this multidimensional illness as a single or a collection of psychiatric disorders is also the wrong answer.

The correct answer in this case is  j) Prescribe buprenorphine/naloxone (BUP/NAL).  In practically every case like this that I have been involved with since the advent of BUP/NAL prescribing the anxiety, sleep disturbance, depression, and physical symptoms all resolve or at least the portion of the illness that is directly attributable to opioid use.  In this case the patient was also using a benzodiazepine with a long half life and may also need to address those symptoms.  Protracted withdrawal from benzodiazepines has been described since the late 1980s and the symptoms can also last for a long time.

The clinical approach to addictive disorders provides clear information on why addiction is a disease whether you happen to accept any of the models proposed by Volkow and Koob or not. At every step of the way in the above example, the underlying systems are described in either of the main addiction texts.  There is clearly a loss of normal functioning that does not respond to talk therapy or other learning interventions.  In fact, these interventions presented to a distressed person typically create more problems than solutions. Although it is possible to insert neurobiology into any medical or talking intervention these days, learning interventions for the above problems can be expected to have little to no effect on the major problems that this patient is experiencing.    

All of those problems at any stage of addiction are a loss of normal functioning or a disease state. With addiction the loss of normal functioning is not trivial. It is disabling, severe, and life threatening. Any quality treatment program should be able to address them and not depend solely on a learning environment to assist these patients.


George Dawson, MD, DFAPA

Computational Aspects of the Human Brain

As part of my lectures on the neurobiology of addiction - I digress briefly to discuss the computational aspects of the brain.  A lot of that discussion is focused on on the above graphic showing that overlaps in capacity with a list of the world's ten fastest supercomputers.  At least that is the estimate of the AI Impacts group.  It is basically a computation based on edges and nodes. I include power estimates for a brain from existing hardware to the actual power estimate of the human brain that I would guess every physical chemistry student from my era had to contemplate at one time.  And then I try to stimulate some discussion of supercomputers versus the human brain and it generally falls flat.  My Socratic process goes something like this:

"OK so we know that humans can't really beat computers on straightforward calculations so what advantages do we have?"

"I will give you a hint - why do we all go thorough residency training? Why can't you learn your specialty by reading about it in a book?"

The first lesson is pattern matching.  The human brain is designed not only to match patterns but to be trained to match a lot of them.  Some research article suggest about 88,000, but when  you consider what has to be matched that has be very a very low estimate.  I quote references from 15-20 years ago and a course I used to teach on diagnostics and diagnostic decision making.  Ophthalmologists correctly diagnosing diabetic retinopathy at a much higher rate than nonspecialists.  Dermatologists diagnosing rashes faster and correctly classifying ambiguous rashes with greater precision than nonspecialists. If I am really on a roll I might digress to talk about Infection Disease rounds at the Milwaukee VA sometime during 1982.  I was the medical student on a team of residents and fellows doing a consult for possible subacute bacterial peritonitis.  As the attending listening to the presentation he was also looking at a rash on the patient's shin.  By the time we were done he had also diagnosed a strep infection in addition to the peritonitis.  When you have significant pattern matching capacity, and you have been exposed to relevant patterns you can recognize them quickly and improve the speed and accuracy of the diagnosis.

I move on at that point to illustrate that the computers are catching up.  The simple captcha is less robust in discriminating machines from humans.  Opening an account may take more that checking the "I am not a computer" box. Now you might have to look at 8 pictures and check the one that contains an automobile or a stop sign.  Some of these photos are often difficult for humans to decipher.

At that point I touch on human consciousness - both the unique aspects and computational power it takes to generate.   About a decade ago I started saying that if there are 8 billion people on the planet - there are 8 billion unique conscious states. It makes sense at a number of levels especially when I put up hard numbers on cell types, protein types, the genetic information represented, and the typical stream of consciousness that every person experiences every day.  What is the content and flow of that activity? How does it get biased in psychiatric disorders and addictions?  How much computational power does it take to generate all of this information?

My latest step is what I like to consider The Matrix observation.  If I am standing in front of a room of 15-20 residents - what does it take to generate the physical representation of all of the people and all of the objects in that room? What does it take to make all of those representations unique? There can be a general consensus about what is happening - but just looking around it is clear that there are obvious different experiences.  One person looks very interested and one semi-interested.  One person is more focused on her Smartphone and is indifferent to my presentation.  Some people look sleepy.  Others look irritated.    They also appear to be indifferent to the context.  I know that my job is to try to get this information across and make is semi-interesting.  There is no real expectation on the residents.  It is clear from the questions I ask that they really don't know too much about the brain.  There are parallel streams of information processing that allow us all to evaluate what is occurring on the fly both the information content and emotion.  In some case there are pre-existing heuristics and in other cases associative memories and biases.  All of this represents a tremendous amount of information or computational power depending on how you may want to discuss it.

I have been preoccupied myself with the computational power and estimating it accurately. I used to try to model it in terms of electrical buses and neuronal firing rates - but the numbers I got were far too low.  There really are no good equivalents in the physical world with the possible exception of the Transversed Edges per Second (TEPS) metric used by the AI Impacts group for the above graphic.  You can't really use estimates of typical audio or visual information and concluding that is what is being processed by the brain.  I have never really seen an accurate estimate of all of the sensory information that the brain is handling in real time.

I went to bed last night and waited for sleep reverie or that period of time where you stream of thinking is jumbled and illogical just before you fall asleep.  As a chronic insomniac it is one of the few reliable cues that I am probably getting some sleep.  It happened when I had a sudden image of a baby high up on a brick wall, followed immediately by a person who seemed to be me sitting in a single seat futuristic car.  The salesperson was describing it to me and suddenly the car and everything else was being swept down what appeared to be a very sophisticated hydraulic roadway. The roadway was bright orange and the salesman shifted his pitch to tell me the advantages of this kind of a roadway with this car.  The roadway was moving at about 20 miles per hour.

I shifted briefly and remembered it was 2018 and I was in my bedroom in Minnesota.

And for a minute I thought about being able to estimate the information necessary to generate that brief full color science fiction scene and the three or four more I would encounter that night.


George Dawson, MD, DFAPA


Some additional examples as they happened:


1. Dream of 11/22/2018:  I am back on my old inpatient unit.  The layout is exactly the way it was 20 years ago (the building has since been razed).  I am working with the same staff.  I walk into the examination room to look at the templates for the day.  In those pre-EHR days I had designed a template with all of the relevant features necessary for the billing and coding requirements.  At the time we were all threatened with legal action if we did not comply with these regulations even though they were totally subjective.  In those days I worked with a physicians assistant who prepared the templates ahead of time before we started interviewing patients and completing the subjective aspects of the evaluation and documenting the progress.

The templates were all stacked in two circular patterns - ten templates in each circle.  They appeared to be the exact temples that we used right down to the blurred fonts from being photocopied too many times.  The precise handwriting of my physicians assistant in the diagnostic section was exactly the way he wrote things down.  The placement of the exam table and crash cart were exactly where they were in reality.  The table we used was circular and about 6 feet in diameter with a laminated blonde wood finish and it was also exactly the way it was in that now 20 year old reality.

I looked at the templates and asked myself: "Why are they all face down?  I can't see the patient's name or identifying data.  I will have to go through them all to find the correct template when I start interviewing patients."

I felt somewhat irritated.

And then I woke up. 

2. Dream of 11/23/2018: I am in a large modern, multi-floor medical facility. It is not one that I specifically recognize, but it seem like there are elements of many that I have been in.  I am rushing around on the ground floor. The impression I have is that I am late for a lecture. It doesn't seem to be an explicit CME lecture but everyone else there (including myself) is too old to be a medical student or resident. I run into the elevator just beating the door as it closes.

I make to to the lecture.  It is basically a large room - maybe 50' x 50' and for some reason I burst through the door running at full speed.  Just before the crash into the back wall, a guy standing on the side wall grabs my arm to slow me down and stop me.

I ask myself if that was really necessary because my plan was just to stop myself by reaching out and planting my hand on the back wall.  I notice that there are several people who I assume are physicians that are standing and sitting near the back wall and they seem a little alarmed about something.

Then I am back in the elevator and headed to the ground floor.  I am walking out of the building and realize that I am chewing something metallic.  I realize that is is a collection of machine screws, nuts, and ball bearings. I realize that is purchased them on the ground floor of this building and that they are sold for that purpose.  I also know that I cannot really chew them or I will break my teeth.  I have to cautiously move them around in my mouth.  They remind me of a chap stick product that is applied with a ball bearing device at the end of the dispenser.

I wake up with a metallic taste in my mouth.

3.  Dream of 11/24/2018:  I am back in my home town. The streets and buildings are identical to the way they look in reality.  I am with a friend of mine and we are looking at a 1960s vintage Buick.  It is large and chalky white.  He tells me that his sister recently bought it and she wants to take everyone for a ride.  He thinks I should come along, but just then I remember something that his sister said to me in the last 15 years that would make me not want to go with them. He is talking about the car as though it is a great buy, but as I walk past the tail end of the vehicle, I notice that it has a new paint job and that whoever did it just painted over the decals of the previous dealers.  You can see them faintly through the paint.

I tell my friend that I can't stay around because I have to go grocery shopping. Just then one of his friends comes out and tells me that he has a lot of groceries he can just give me so that I will not have to go to the store.  I decline but he continues to insist. I reluctantly accept free groceries and sling them over my shoulder in a large garbage bag and start to walk home.

The real path home is just 6 blocks - 4 blocks south and 2 blocks east. It is all residential. But in the dream I encounter a large modern baseball park right next to the street. The game is just completed and they are interviewing the winning pitcher. She is in her mid 20s and short and compactly built.  Her uniform and short brown hair are drenched with sweat.  Just then I notice that it is hot. The announcer asks her if the heat was a factor in the game and she says:

"The hot was so hot that when my hot fingers touched the hot ball - I could barely feel it." 

The ballpark looks real.  There are thousands of cheering fans and the announcer and the pitchers statements are amplified over the PA system.  Everything is in color.

I wake up and feel hot and flushed.

The NEJM "Addiction As Learning And Not Disease" Article

The latest installment of what appears to be an endless debate about whether addiction is a disease or not hit this weeks New England Journal of Medicine in an article entitled "Brain Change in Addiction as Learning and Not Disease." I have looked at a few of the previous articles along the same line that purport to show why addiction is not a disease and it is fairly easy to show that disease or not a disease generally depends on the author's definition and pointing out why the other definitions do not seem to fit. It is basically an exercise in rhetoric.  Those approaches invariably end up at quite a distance from opinion polls that illustrate that most of the public and even more medical professionals consider addiction and severe mental illnesses to be diseases.  I will come back to the philosophical underpinnings of those polls at the end of this article.

In this case the author is essentially making three arguments.  Two of the arguments are in side panel graphics and the third argument is in the main text.  The first side panel argument (p. 1552) concerns the Brain Disease Model and Stigma. In it the points out that the disease model can be destigmatizing but it also can be stigmatizing to some people.  Although I do not agree with some of his premises let us accept that his argument is basically a wash and the people who feel stigmatized and recoil from the prospect of the addiction illness perfectly cancel out those that accept the model are are consoled by it. I recognize that a substantial part of the recovery community base their recovery work on the disease concept of addiction although it is not strictly similar to the biomedical disease that is typically described.  This entire panel described a sociocultural model of disease (2).  This concept is basically that different societies and the physicians in that society may have diverse views of diseases that vary from other cultures.  A secondary factor is that medical recognition may change how that disease has come to be viewed by the society at large.  For example, an illness that was once thought be be caused by moral deficiency is seen differently after it is recognized as a process that may be beyond the control of the afflicted person.  Mental illness, alcoholism, and addiction are common examples.  An associated feature of this model is that this concept cannot be used by the medical field that must concentrate on understanding the biological mechanisms that underlie the disease.  That makes this panel irrelevant to a medical disease concept.

The second side panel (p 1553) looks at Learning Models and Empowerment.  It can also be understood as a sociocultural model.  In this panel the author develops a number of arguments to suggest that if people were free of thinking they had a disease they would be more prone to self examination and less dependent on professionals and the need to adhere to what professionals tell them.  He suggests that disease mechanisms would lead to pessimism on the part of the person with the problem that would not exist if they were engaged in any number of learning programs to help them recover.  He uses the familiar quote that most people recover spontaneously without any help from professionals.  This argument depends on a couple of premises that are clearly flawed.  The first is the group that is described as having an addiction.  The convention I use for that is Volkow's definition of being equivalent to severe DSM-5 substance use disorder in any category.  That category has a high level or mortality, comorbidity, and chronicity. In this case the author seems to minimize the interventions used by addiction professionals to "making life-style choices to improve their prognosis."  That minimization serves his purpose to suggest that learning is an entirely novel approach to addiction when it has been used for decades.  Spontaneous recovery is an often quoted argument against a disease model, when it happens all the time in other conditions (obesity, metabolic syndrome, diabetes mellitus Type II, hypertension).  The fact is, spontaneous recovery by any number of conscious interventions does not preclude a disease process.

The bulk of the author's argument in the main text is based on illustrating how learning in addiction and normal learning are similar if not identical processes and therefore disease is a learning problem rather than a disease.  The most logical way to analyze this argument is to examine the conclusions first.  Looking at the conclusion highlights the seriously flawed premises in the author's argument that addiction is not a disease but is just learning.  I did not see any qualifiers that addiction is a special case of learning or not.

The author's believes that he has developed a "balanced model of addiction" that incorporates various learning mechanisms into what he calls and "embodied cognition model" of addiction.  In this model he sees baseline and adaptive biology interacting with the environment to produce the addiction.  It is interesting that the key environmental feature of drug use disorders - exposure to the drug is way down his list of other social, cultural and familial factors.  Some of his examples illustrate this point.

He discusses the socially disadvantaged youth raised in an adverse environment: "These persons tend to find increased meaning in drugs that reduce stress or promote feelings of security and well being especially because these effects can be attained without medication by other people." That does not explain the flood of advantaged white middle class youths who became addicted to heroin and represent a substantial number of overdose deaths.  It also does not explain the difference between two inner city youths who have to walk past 3 drug dealers on their way to school each day and one of them becomes addicted and the other does not.  One of the important lessons of the current  opioid epidemic should be that exposure to a highly addicting drug in biologically predisposed people is one of the central mechanisms of addiction.     

The authors "addiction spiral" is also problematic.  It begins with "early adversity and trauma" as the first step effectively limiting any explanatory power to that population. In step 2, he discusses development changes in the autonomic nervous system that may occur in response to childhood trauma that can lead to hypercortisolemia as an adult. That makes this model appropriate only for adults who have been traumatized as children and even then - only those children with this pathophysiology.  There can be a broad range of factors that lead to behavioral inhibition and anxious temperament (3). In step 3, he discusses early childhood adversity as a cause of epigenetic changes that can predispose to addiction.  He omits the concept that exposure to compounds like nicotine and other addictive substances are much more potent causes of an array of epigenetic changes and correlate highly with addiction. Kandel and Kandel (4) among others have shown that DNA hyperacetylation from nicotine is associated with cocaine use.  Epigenetic changes from drugs of abuse are widespread .  A recent study of the impact of smoking on the human genome concluded that as many as one third of genes in the human genome can be affected (5) by methylation of 18,760 statistically significant cytosine-phosphate-guanine sites. In order to claim a more potent learning effect at least an equivalent neurobiology of learning with equivalent impact that it applies across the entire population of people with addictions should be presented.  I don't think this paper reaches that threshold.   

That brings me to the point of whether it is relevant to use the disease concept at all.  I am sure that students have heard me say from time to time that it is not. That statement is usually accompanied by the statement that it still has to be recognized as a severe problem that is a significant cause of mortality and morbidity.  There is a little used philosophical approach to the disease concept that I have rarely heard about outside of reference 2.  That concept is disease as a departure from normal functioning (p 160).  In this discussion the authors develop the concept that organisms are a special case of programmed systems.  Normal homeostasis in humans is a result of that programming.  Biomedical research is focused on being able to discover that program and how it is coded, uncoded, and expressed as disease.  One of the authors' conclusions is:

"There is reason to believe that as research progresses, more and more biological processes at all levels of organization will come to be understood as programmed processes."

They refer to closed programming that are those resulting from direct decoding of the genome with inborn errors of metabolism being a key example.  Other phenomenon require an interaction with the environment to result in the full development of the programmed process.  They go on to suggest the existence of "open" programming where some form of learning or conditioning is required to complete the process.  Some of the programs may be "closed" at a certain point and not amenable to further decoding.  All of these programs are shaped by the evolutionary process.  Viewing organisms as biologically programmed systems (p 163) takes social values and norms out of the equation and provides a definition of normal functioning and it also defines the acceptable evidence necessary to delineate abnormal functioning.  The authors' straightforward definition of disease is given below:

"Disease is a failure of normal functioning."

Consider the following vignettes to illustrate that definition. None of the subjects noted had any adverse childhood experiences or pre-existing psychiatric disorders.  They all had positive family histories of addiction.

Patient 1: 22 year old woman who received hydrocodone after her wisdom teeth were removed at age 20.  She received a 14 day prescription and continued to take it even when her pain was gone.  At this point she started to acquire opioids from nonmedical sources and eventually switched to heroin for economic reasons and was injecting herself 4-6 times per day.  She went to treatment and was placed on buprenorphine-naloxone 16 mg/day.  On that dose she had no cravings for opioids and no withdrawal symptoms.  Her family has decided to withdrawal support based on considerable expenditures for various therapies that have been ineffective. She goes to a sober house but after a week there learns that there are fentanyl based products available.  She leaves the sober house in search of these products.

Patient 2:  45 year old man who is an IT professional.  His father and grandfather were alcoholics.  His grandfather died of cirrhosis. He decided at an early age that he needed to avoid alcohol in order to avoid alcoholism and did well with that strategy until about age 40.  At that point professional pressures to socialize with clients lead to some drinking that he escalated at home.  He can work from home and his drinking escalated significantly to the point he was drinking a liter a day of vodka that he consumed between 7PM and midnight.  This pattern continued for several years until he started to get episodes of alcoholic pancreatitis that required longer and more complex hospitalizations. He tried to stop drinking on his own.  He tried online courses that used cognitive behavioral therapy.  He went to Rational Recovery and eventually AA. Nothing worked and he knew that every episode of pancreatitis at this point was life threatening.       

Patient 3: 30 year old carpenter with no previous history of substance use. He was working in a new construction area and found one of his coworkers inhaling paint out of a plastic bag.  He tried it and experienced an intense episode of euphoria.  That night he went home and found Internet sites where solvent-inhalant users compare their experiences and give tips on usage. He picked up a popular computer duster product and was soon inhaling many cans a day. He eventually crashed his truck while inhaling the solvents and as the police pulled him out of the vehicle - he was still inhaling the solvent. When he was seen in the emergency department he told the physician there that he could not stop using inhalants because: "It felt like pure dopamine was coursing through my veins!"

The previous examples are not extreme cases in addiction medicine and addiction psychiatry. They illustrate a failure of normal functioning by compulsive use of a substance despite knowing that this use is irrational and repeated failures to stop.  One of the common comments about the majority of people with addiction stopping on their own totally ignores the people being seen in addiction settings.  It is this combination of severity, inability to stop despite severe consequences, and chronicity that leads physicians and lay persons alike to consider addiction as a disease.

What about the evidence of failure?  It can come in various forms.  In a standard medical format there is a signature clinical course or phenomenology of the illness.  Symptoms can be obvious in a physical or mental status exam. Laboratory testing including chemical and microbiological analyses, electrophysiological studies, imaging studies of various regions and tissues can be undertaken.  In all of these determinations the evidence can always be equivocal, false positive, false negative, or truly positive.  It often takes a level of expertise to interpret the evidence and a good example is electrocardiography.   

From a philosophical standpoint the authors in reference 2 point out the initial value of a functional-failure model of disease.  It has obvious implications for basic science research of disease mechanisms.  That research should be focused on discovering the programming errors in the human organism that results in failure of normal functioning with the hope of understanding the underlying pathophysiology and correcting it.  The model clarifies a role for statistics in the disease model specifically the strength of association of certain variables with normal and abnormal functioning as well as ways to analyze tests for those variables.  And finally, the concept makes it very clear that the disease in question is real and exists independently of societal biases.  I don't think for example that any of the above vignettes could be considered anything less than a failure of normal functioning. In the people addiction specialists treat, there is generally a trajectory of progressive isolation, multiple psychosocial losses, loss of relationships, poverty associated with addiction, and in too many cases - premature death due to the direct or indirect results of addiction.

That is the reality and it is captured by disease as a loss of normal functioning.

I am going to bring this post to a close at this point, but look for a more extensive look at the specific types of learning listed in this article compared with the biological impact on plasticity when people are exposed to addictive drugs.  I started out thinking that I was just going to continue my opinion about the disease concept being irrelevant but instead find that I have been invigorated by a view from a book I read over 20 years ago that is still relevant today.  I will end with a communication I received from one of the authors that I hope sums up this post and illustrates why physicians should probably not cloud the disease concept with popular notions like stigma or  empowerment:

"Most people would think epistemology is always irrelevant to ordinary life, but clearly it isn’t."


George Dawson, MD, DFAPA



References:


1: Lewis M. Brain Change in Addiction as Learning, Not Disease. N Engl J Med.2018 Oct 18;379(16):1551-1560. doi: 10.1056/NEJMra1602872. PubMed PMID: 30332573

2:  Albert DA, Munson R, Resnik MD.  Reasoning in Medicine: An Introduction to Clinical Inference.  Baltimore, Maryland: The Johns Hopkins University Press, 1988: 150-180.

3: Fox AS, Kalin NH. A translational neuroscience approach to understanding the development of social anxiety disorder and its pathophysiology. Am J Psychiatry. 2014 Nov 1;171(11):1162-73. doi: 10.1176/appi.ajp.2014.14040449. Review. PubMed PMID: 25157566.

4:  Kandel ER, Kandel DB. A Molecular Basis for Nicotine as a Gateway Drug. The New England journal of medicine. 2014;371(10):932-943. doi:10.1056/NEJMsa1405092.

5: Vaillancourt K, Ernst C, Mash D, Turecki G. DNA Methylation Dynamics and Cocaine in the Brain: Progress and Prospects. Genes (Basel). 2017 May 12;8(5). pii: E138. doi: 10.3390/genes8050138. Review. PubMed PMID: 28498318.

5:  Joehanes R, Just AC, Marioni RE, et al. Epigenetic Signatures of Cigarette Smoking. 2016. Circulation: Cardiovascular Genetics. 2016;9: 436–447. Full text

Supplementary 1:

My thanks to both Ron Munson and Mike Resnik two of the authors of Reasoning in Medicine - reference 2 above.  Further thanks for Ron Munson for the quote at the end of this post and encouragement to explore his ideas about the disease concept.  It means a lot to hear from both of these authors at a point when they could have easily ignored me.  It is a sign that there are many kind and thoughtful scholars out there. 

As I type this at 2AM that thought about scholars gives me a warm feeling.


Supplementary 2:

The quote used for patient 3 is found on the Internet and used for this hypothetical patient.  I have feedback from at least one addiction psychiatrist that the vignettes provided above are realistic and typical of addiction psychiatry practice.


Supplementary 3:

I added this on 12/22/2018 when I encountered an excellent example of Wittgenstein's work in Existential Comics.  In this case consider the parallel argument about disease or non-disease based on the hot dog versus sandwich argument.  What do you think Wittgenstein would say?

Existential Comics: Is a Hotdog a Sandwich? A Definitive Study.  December 2018.