Who was at fault here? UK Woman left to die after computer decision support blunder

Who was at fault here? Those who modified the fall height parameters, those who designed the decision support system such that it could override life threatening problems based on a single parameter, endusers, their managers, or all?

Or was the problem the syndrome of inappropriate confidence in computers (SICC syndrome)?

I opine all of the above, in this cautionary tale:

Woman left to die after 999 ambulance blunder
By Laura Donnelly, Health Correspondent
Telegraph.co.uk
Published: 9:00AM GMT 21 Mar 2010

An investigation into a woman’s death has exposed a catastrophic decision by ambulance chiefs which may have cost hundreds of lives.

The blunder arose when call centre staff were not warned of flaws with a computer system that prioritises emergencies before dispatching ambulances.

Bonnie Mason, 58, fell down the stairs and died from a head injury after 999 controllers in Suffolk failed to identify her situation as “life-threatening”.

An investigation by The Sunday Telegraph has uncovered a critical danger placed in the software used by most ambulance services. For years, 999 calls in life-threatening situations like Mrs Masons’s were accidentally “downgraded”, with call handlers told not to send the most urgent response.

While some services spotted the risk, ordering operatives to override the computer’s orders manually, five of England’s 12 ambulance trusts did not allow call handlers to upgrade such calls [A belief that "the computer is omniscient" seems to be the only basis for such an exclusion of human judgment - ed.] They include the East of England ambulance service, which covers Suffolk and which only identified the risk after Mrs Mason’s death.

The danger in the system was created by the country’s most senior ambulance officials as they altered the program used by most control centres in an attempt to manage demand for 999 services.

Most ambulance services use an international computerised system designed in America. In the US version, a fall of more than 6ft receives the maximum priority response. However, the government committee which governs its use in this country decided that such cases should be deemed less urgent [what were they thinking? - ed], and excluded from an eight minute category A target response time.

In doing so, they created a potentially lethal flaw in the system. It meant that if a call involved a fall of more than 6ft it was designated a lower priority – a category B response – despite the presence of life-threatening conditions which were supposed to receive the most urgent category A response.

[NOTE: If the other life threatening conditions were ignored by the computer system after its "first-pass" look at the height of the fall, then who actually created the most severe flaw is unclear to me, those who altered the parameter or those who designed the overall decision support logic - ed.]

As a result, Mrs Mason lay unconscious for more than 38 minutes. The first ambulance sent to her home in the village of Eye, Suffolk, was diverted to attend to a drunk woman who had fallen on a pavement 22 miles away in Thetford, Norfolk. Because the inebriated woman had fallen at ground level, her situation was prioritised over that of Mrs Mason [perhaps because their was no entry of a "height of fall" - ed.], who was close to death by the time paramedics arrived. The East of England ambulance service, which also covers Bedfordshire, Cambridgeshire, Essex, Hertfordshire and Norfolk, said its operatives were instructed never to “override” the advice of the automated system.

Ambulance dispatchers instructed to "never override the advice of the automated system?" Simply stunning if true.

Read the whole story at the link above.

On another note: government committees have rarely worked well in domains where critical thinking is essential. (I can't wait for the comparative effectiveness committees using flawed data from flawed EMR's to start their work. I'd written about that issue here.)

Finally, "Our policy is to always trust the computer" is not a way to run life-critical healthcare services. Ever.

-- SS

Post Title → Who was at fault here? UK Woman left to die after computer decision support blunder

The Syndrome of Useless Information

I occasionally elevate comments and replies to the level of full posts if I feel they better illustrate and clarify significant points I raise.

In my Jan. 9, 2010 post "Does the CEO of Google Use Google? - And: Platform, Platform, Who's Got The Platform?" I lamented the intrusion of ill-informed, reductionistic, "database platform"-centric views of non-clinical IT personnel into healthcare.

I received the following feedback from an anonymous commenter:

Anonymous wrote:

Or then again, there's this:

"Non-physicians may reach correct diagnoses by using Google: a pilot study."

http://www.ncbi.nlm.nih.gov/pubmed/19130327

"Researchers found that almost six-in-10 difficult cases can be solved by using the world wide web as a diagnostic aid."

http://www.dailymail.co.uk/news/article-415562/Doctors-using-Google-diagnose-illnesses.html

I think this post [i.e., my HC Renewal post about Google's CEO and "platforms" - ed.] misses the larger point that Gawande and Schmidt were addressing (and to some extent agree on) - the "art" of the practice of medicine must be transformed to the science of the practice of medicine. And today, science and IT are necessarily intertwined in practical terms.

The future will no doubt involve ever more sophisticated and useful clinical DSS. Historically speaking, invoking the complexity argument is fraught with issue as technological advances provide better and better ways to represent and manage it.

January 16, 2010 10:03:00 AM EST

Anonymous apparently meant these article references to exemplify the coming Age of Cybernetic Miracles in medicine.

My response to this anonymous feedback was placed in the comment thread of the "Does the CEO use Google" post and covered a number of bases.

I've reproduced my response, and added additional explanatory notes not in my original response in bold red italics below:

MedInformaticsMD wrote:

Re: Anonymous Jan 16 @ 10:03 AM-

The article [the first, at nlm- ed.] you cite reports the following:

Non-physicians may reach correct diagnoses by using Google: a pilot study.

OBJECTIVE: We endeavoured to determine whether individuals who are not physicians are likely to arrive at correct diagnoses [note the stated objective carefully -- "are likely to arrive at correct diagnoses" - ed.] by using Internet resources.

METHODS: In this prospective study four non-physicians used Google to search for diagnoses. They reviewed the 26 diagnostic cases presented in the case records of the New England Journal of Medicine during 2005; they were blind to the correct diagnoses. The main measurement was the percentage of correct diagnoses arrived at by non-physicians by using Google. The diagnostic success of the four non-physicians was compared to that of four young physicians.

RESULTS: The average diagnostic success of non-physicians was 22.1% (95% confidence interval [CI] 4.5-39.7%). There was no statistically significant difference between the non-physicians regarding this outcome (p = 0.11). They took 8.9 +/- 6.7 (mean +/- standard deviation) minutes for case record reading and 17.4 +/- 7.9 minutes for Google searching per case. Non-physicians performed worse than physicians (50.9% [95% CI 37.4-64.5%]) in regard to diagnostic success (p <0.001).

CONCLUSION: Non-physicians, at least those who have similar characteristics to the participants in the present study, may occasionally reach correct diagnoses by performing a brief web-based search. Doctors should realise that patients may assume a more active role in their health decision-making process and take this development into consideration in physician-patient interaction.

--------------------------

This article suffers from what can be termed "the syndrome of useless information."

[It is, in fact, a failure or negative finding with regard to its stated objective - ed.]

Let's see:

The average diagnostic success of non-physicians was 22.1%

They omit the opposite semantic: that the google-armed nonphysicians got more than three quarters of the diagnoses WRONG. Will you trust your grandmother to them?

Non-physicians performed worse than [young, a.k.a. inexperienced] physicians (50.9% [95% CI 37.4-64.5%]) in regard to diagnostic success (p <0.001).

Young, inexperienced physicians (trainees or residents?) arriving at 51% of the diagnoses correctly using ONLY google (not, for example, Harrison's, and other standard medical texts that would not be highly usable to most non-physicians lacking background to fully understand it) is not unexpected.

What is surprising is that the article omitted an essential control group: *experienced* physicians. It's not that they're hard to find.

The article concludes:

Non-physicians, at least those who have similar characteristics to the participants in the present study, may occasionally reach correct diagnoses by performing a brief web-based search.

Occasionally reach correct diagnoses? How about "most often reach incorrect diagnoses?" Cf. a broken clock is still occasionally correct.

[I repeat, the article is, in fact, a failure or negative finding with regard to its stated objective of "determining whether individuals who are not physicians are likely to arrive at correct diagnoses." They are in fact unlikely to get it right, with only a 22% hit rate, although the authors appear to have de-emphasized that fact. This will only make physicians' work harder as they "take this development into consideration", i.e., deal with patients armed with search engine-gleaned misdiagnoses - ed.]

I do not view this article as revealing anything of practical value other than perhaps the dangers of allowing non-physicians armed with search engines to think they can perform medical diagnosis to any meaningful extent.

Anonymous wrote: the "art" of the practice of medicine must be transformed to the science of the practice of medicine. And today, science and IT are necessarily intertwined in practical terms.

Reductionist views of non-medical IT personnel spouting off about 'database platforms' will not advance the science or the art of medicine.

Also, yes, IT is a tool of science; however, it and its designers and implementers facilitate science; the enablers of science are: scientists, using their insight, creativity, ingenuity, experience and expertise.

Concerning the second article [at dailymail.co.uk - ed.], I note:

"But they [the authors] stress the efficiency of the search and the usefulness of the retrieved information depend on the searchers' knowledge base." [The 'searchers' in this case were apparently - experienced physicians - ed.]

In other words, search engines can facilitate experts. That is not exactly new knowledge.

The 'art' of medicine, i.e., judgment, likewise is both indispensible, and irreproducible via "database platforms." Perhaps one day with advances in cognitive computing we will get to that point, but at present we can't even do as well as a cat. Note the statement from the IBM P.I. that "there are no computers that can even remotely approach the remarkable feats the mind perform."

Until we get there, I think it's not unreasonable to hold off on non-clinicians touting reductionist information retrieval-centric views.

Anonymous wrote: Historically speaking, invoking the complexity argument is fraught with issue as technological advances provide better and better ways to represent and manage it.

You must not have read my original post. It is advances in information science (i.e., in informatics) that will provide those advances, not advances in [information] technology. IT is a tool; information science is an activity of the mind.

Your statements clearly demonstrate a conflation of information technology and information science.

Computers facilitate information science research, but they are certainly not its sine qua non.

I should also add that the second article referenced by "Anonymous" refers to "obscure conditions such as Cushing's syndrome." I'm not exactly sure to whom Cushing's disease is an obscure disease. A non-medical IT person, perhaps?

Now, back to reality. Computers serve as aids to clinicians, when the IT is "done well." However, there is no substitute -- except in sci fi -- for expertise.

Medical expertise can only come from ~4 years of premed and then 4+ years of hard medical study in a wide variety of preclinical and clinical sciences leading to the M.D. degree, 3-4 years of postgraduate residency, and often 2+ additional years of postdoctoral fellowship training beyond residency for specialists (it should be noted, unfortunately, that there are no additional medical degrees beyond M.D., although residency and fellowship training often makes pursuing a Ph.D. in most fields seem like a cakewalk). Add to all that years of additional clinical experience in actual practice.

I am quite disturbed that this study and experience has become so casually regarded outside of medicine, for example in the IT sector. I think it reflects poorly on the IT culture specifically, and on our current culture as a whole.

Medical judgment is borne of that study and experience, not of healthcare computer dabbling typical of the business IT/MIS world in hospitals, and the all-too-often technical bachelor's degrees held by leaders in that domain. Google CEO Schmidt at least is a true computer scientist with a doctorate in CS; that does not, however, qualify him to comment on medical and medical informatics-related issues as in my prior post.

Stated frankly: he and many others with similar views are venturing far outside their competencies and as a result are talking nonsensically.

Incidentally, I believe it's time to move on from continually responding to the non-medical, IT-personnel proffered platformorrhea on how IT databases, decision support, artificial intelligence etc. will transform medicine from an art to a science, revolutionize medicine, and similar positions trafficked for at least several decades now.

They are largely manifestations of the Syndrome of Inappropriate Overconfidence in Computing (SICC syndrome), a term I coined in the 1990's and described is some detail here in a post entitled "A 21st Century Plague? The Syndrome of Inappropriate Over-Confidence in Computing." At that post I stated that:

I, for one, would welcome a cessation of claims that IT will "revolutionize" any field that depends primarily on cognition, such as biomedicine, and a return to more temperate attitudes instead of the almost bellicose grandiosity about HIT we see today. That is to say, that HIT - with proper contributions from the aforementioned specialties [e.g., social science, social informatics, biomedical informatics, HCI, etc.] will facilitate better health care, not "revolutionize" it.

In the future, similar comments as those from "Anonymous" will simply get referred back to the post you are now reading and the bolded one on SICC above.

Finally, I will not hold my breath for Emergency Medical Hologram Mark I, or R2D2 and C3PO to appear anytime soon.

-- SS

Post Title → The Syndrome of Useless Information

Have we suffered a complete breakdown in the scientific method with regard to EHR and clinical IT?

Have we suffered a complete breakdown in the scientific method with regard to EHR and other clinical IT?

I read announcements like this with trepidation:

http://govhealthit.com/articles/2009/03/31/sebelius-confirmation.aspx
“The goal,” Sebelius said, “is to provide every American with a safe, secure electronic health record by 2014." The nominee also endorsed efforts to use data gleaned from electronic medical records to conduct “comparative effectiveness research" (CER) to provide information on the relative strengths and weaknesses of alternative medical interventions to health providers and consumers.”

Recovery Act funds have been allocated to NIH specifically for comparative effectiveness research. NIH has further specified the definition of CER as:

"[A] rigorous evaluation of the impact of different options that are available for treating a given medical condition for a particular set of patients. Such a study may compare similar treatments, such as competing drugs, or it may analyze very different approaches, such as surgery and drug therapy."

NIH states that such research may include "the development and use of clinical registries, clinical data networks, and other forms of electronic health data that can be used to generate or obtain outcomes data as they apply to CER."

The problems I foresee concern the word "rigorous" as in the above definition.

The use of EHR data to reliably detect uncommon (but strong, discrete) early warning signals from a single drug or treatment -- to then be subject to more rigorous study with reasonable controls -- is itself a Medical Informatics "Grand Challenge." An example would be finding VIOXX's association with myocardial infarction earlier than we did, via an EHR-based automated postmarket surveillance process.

Doing this is a "grand challenge" due to the nature of EHR data, which is as far from "clinical trials clean" as possible. It is what might be called highly uncontrolled. The statistical methods needed to reliably pull signals out of the muck for even a single drug are still exploratory, the problems formidable if one wants to stay scientifically sound. I wrote about the experimental nature of such efforts a few years ago here, and believe an effort got underway at U. Indiana/Regenstrief to test such methodologies for postmarket surveillance about the same time.

Now we have had what appears to be a leap of faith and logic of irrationally exuberant proportions, and probably a deviation from sound science as well. The government has announced enthusiasm for EHR data-based comparative effectiveness research (CER) not to aid science, but to cut costs (implying skipping the rigorous confirmatory phases) through elimination of more costly drugs and treatments deemed less effective or at effectiveness parity compared to less expensive choices. Following this thinking, perhaps in the future a metric will be developed for an "acceptable" improved benefit/cost ratio for expensive drugs that are better than cheaper alternatives?

This overconfidence in EHR data is of concern. To detect relatively less concrete (i.e., than major ADE) "outcomes differences" between two or more drugs or treatments via EHR data - did treatment A lower blood pressure more than drug B, did drug C lessen depression more than drug D - rises to the level of "grand overconfidence in computing." To accomplish this task with reasonable scientific certainty from reams of EHR data, originating from different vendor systems, input by myriad people of different backgrounds with differing interpretations of terminologies (students/MD's/RN's etc) under different pressures (time, reimbursement maximization), and so forth, seems a stretch. What will the p values and predictive values be for such studies? Yet our incoming HHS secretary touts such methods?

Ironically, the gold standard in medical science is the controlled clinical trial, yet EHR-based comparative effectiveness research itself as a research methodology, now touted by our government, seems to have gotten a pass.

Even what I would consider minimum requirements for scientific treatment comparisons, such as well designed and reasonably controlled registries as developed here for interventional cardiology, with hundreds of granular, finely defined and "tuned" data elements, appear to be bypassed in EHR "miracle claims." Such precise registries take months or years to develop, implement, and train users to interact with properly. Further, such registries are not portable and must be created for individual medical domains and subdomains. Uncontrolled EHR data is no substitute for such efforts.

The following question arises:

Where are the comparative effectiveness studies that compare 1) EHR-based comparative effectiveness studies of drugs and treatments to 2) controlled clinical trials-based comparative effectiveness studies?

In other words, where are the meta-clinical trials that compare EHR data mining-based comparative effectiveness research as a methodology, vs. the "traditional" gold standard methodology of controlled clinical trials to compare drugs or treatments? How do we know EHR-based CER studies will not produce GIGO that will cause harm through ham-fisted elimination or defunding of useful treatment options?

While there are initial efforts underway to increase understanding of CER, e.g., "Broad Challenge Area 5" (PDF) of the NIH RC1 Challenge Grants in Health and Science Research, ominously, there is a lot of potential advantage to be had with terabytes of uncontrolled data and a political agenda.

I fear that what will come from "comparative effectiveness research" that draws upon uncontrolled EHR data will be politics masquerading as comparative effectiveness research. Good luck to private practitioners and medical innovators. Good luck, pharma. Good luck, patients.

This movement towards EHR uncontrolled data alchemy represents a further deviation from medical science towards the Syndrome of Inappropriate Over-Confidence in Computing (a.k.a. SICC Syndrome) writ large.

It seems the IT industry has now rendered a scientific approach to HIT and its use obsolete. We see this "post scientific era" phenomenon in the takeover of clinical IT by vendors who contractually demand suppression of sharing of problems, we see it in a remarkably uncritical push for EMR's by 2014 now involving force of government (only financial at present, but will punitive licensure issues and other measures be off the table?) despite a growing body of literature advising caution, we see a consortium of big business/payers/vendors/myriad secondary feeder organizations gunning full blast for this technology without consideration of the possible downsides.

Biomedical informatics, a scientific discipline (at least those parts of it not yet compromised by conflicts of interest), as a relevant field is very much a minority player in today's health IT.

Even the contributions from experts and pioneers in the field of Biomedical Informatics, in the form of the Jan. 2009 National Research Council's report that "Current Approaches to U.S. Health Care Information Technology are Insufficient" (here) has not had much impact.

I see Biomedical Informatics' death as a relevant discipline that anyone of importance pays attention to, not too far down the road as well.

-- SS

Addendum April 20:

We've seen this phenomenon in our economy. WSJ "Information Age" writer L. Gordon Crovitz notes:

... In a paper for the scientific journal of the Royal Society back in 1994, Harvard economist Robert Merton wrote that "any virtue can become a vice if taken to extreme, and just so with the applications of mathematical models in finance practice." We know even better now that some risks can be calculated and thus reduced, while some unknowns cannot be turned into probabilities. "The mathematics of the models are precise, but the models are not, being only approximations to the complex, real world."

I believe EMR data at best is a very loose approximation to the real world. It contains many "unknowns" regarding quality and reliability that cannot be turned into probabilities no matter how fancy the math. Asking too much of EHR data becomes a vice, not a virtue.

-- SS

Post Title → Have we suffered a complete breakdown in the scientific method with regard to EHR and clinical IT?

A 21st Century Plague? The Syndrome of Inappropriate Over-Confidence in Computing

This is a longish post that tries to tie together a number of issues regarding overconfidence in computing and healthcare IT's ills. Bear with me.

A 21st century plague might be called the "Syndrome of Inappropriate Over-Confidence in Computing" (SICC syndrome for short).

It's bad enough that we are placing major decisions about industrial policy at the tender mercies of computer models. For example, whether global warming is real or not, dependence on computer models made by scientists who cannot reliably predict the weather, or exactly where an active hurricane under comprehensive observation from sky and satellite may strike, seems presumptuous at best. It reflects a syndrome of inappropriate overconfidence in computing, a belief in "cybernetic magic" if you will.

The same overconfidence, indeed, to the point of irrational exuberance, affects other domains. One domain is healthcare IT. As I shall point out, the SICC syndrome has helped cause major problems in other domains as well. Yet the appetite for yet more computer magic appears to be spreading.

As an aside regarding global warming due to man made causes, as a ham radio enthusiast I am a bit more concerned about what might be happening on good ol' Sol, that class G2 V main sequence dwarf star (the one we see in our sky every cloudless day). Said G2 star is having a problem with generating sunspots in the beginning of its current 11 year cycle, a regular cycle observed now for centuries:

Sunspot (Wikipedia): A minimum in the eleven-year sunspot cycle happened during 2008. While the reverse polarity sunspot observed on 4 January 2008 may represent the start of Cycle 24, no additional sunspots have yet been seen in this cycle. The definition of a new sunspot cycle is when the average number of sunspots of the new cycle's magnetic polarity outnumbers that of the old cycle's polarity. Forecasts in 2006 predicted Cycle 24 to start between late 2007 and early 2008, but new estimates suggest a delay until 2009.

K7RA solar update: Last week's sunspot group was only visible for three days, December 10-12. The average daily sunspot number for all of 2007 was 12.8; if we see no sunspots for the rest of 2008, the average for this year will be 4.7. By comparison, the yearly averages of daily sunspot numbers during the last solar minimum (1995-1997) were 28.7, 13.2 and 30.7. This solar minimum is much lower than the one about 12 years ago.

Emissions caused by sunspots profoundly affect earth's ionosphere layer and thus short wave radio propagation. Those wavelengths refract or "bounce" in the ionosphere and can thus travel beyond earth's curvature.





The little mystery of the current solar clear complexion is in fact unexplainable by any science we know. Heaven knows what others effects are occurring as a result of solar mysteries such as this. The page on Sol linked above contains interesting theories on solar variations, but robust, reliable, predictive computer models for either man-made or solar-related climate change? Ha.

Regarding the SICC syndrome and healthcare IT, physicians and other clinicians at some point must realize their profession is being encroached on by one of the most arrogant occupations known to mankind, the business IT specialty (a.k.a. management information systems or MIS). A belief that mastery of IT in business, whose own track record of failure, waste and excess is far from stellar, gives one the expertise and authority to declare one's self an expert in issues deeply affecting healthcare is about as arrogant as it gets.

Worse, the arrogance is coupled with ignorance about decades of research in social informatics (the study of the social impacts of computing), observational studies, biomedical informatics and computer science research, etc. (A worst case scenario has occurred to me that people who gravitate towards business IT may lack the interpersonal skills and insights into human behaviors necessary to understand the aforementioned domains and their real world importance.) In any case, this encroachment on medicine by the business IT industry is an unwarranted, unparalleled power, territory and profiteering intrusion, a form of cross-occupational piracy.

Further, the gargantuan leap of faith -- with an almost religious fervor -- from health IT as a facilitating tool for clinicians to a tool that will "revolutionize healthcare" in the face of massive, recurrent, serious practical problems is another example of SICC. The recent Joint Commission sentinel alert on Healthcare IT (PDF) is the first formal, widespread acknowledgment of this issue by a healthcare regulatory agency with real clout anywhere in the world, as far as I know.

Those who have written on this issue of HIT risk when improperly designed and implemented have taken reputational hits as alarmists. I've been writing on these same points for at least the past decade, in fact, as have others who share my concerns. I wonder how many of those who critiqued the "alarmists" would after the JC Sentinel Alert now admit their brains were running on 3 cylinders, 80 octane and wishful thinking, while ours on 8 supercharged cylinders, 96 unleaded and reality based observation.

It is perhaps symptomatic of SICC that the recent Boeing 737 accident in Denver, even without loss of life, will be investigated far more thoroughly than all HIT failures combined.

I, for one, would welcome a cessation of claims that IT will "revolutionize" any field that depends primarily on cognition, such as biomedicine, and a return to more temperate attitudes instead of the almost bellicose grandiosity about HIT we see today. That is to say, that HIT - with proper contributions from the aforementioned specialties - will facilitate better health care, not "revolutionize" it.

I also wonder how many of those who critiqued these HIT concerns had a lot of money invested in the stock market's "sure bets" in recent years.

In a Wall Street Journal article about the recent history-making $50 billion+ Madoff financial fraud, "Former Mayor, Millions Lost, Tells How He Was Lulled" (Dec. 20, 2008, subscription required) I note the following:

[Former mayor of Fort Lee, N.J., Burt Ross,who once worked as a Wall St. stockbroker himself] says he remembers being puzzled about how Mr. Madoff was able to show positive returns, even in months when the stocks Mr. Madoff's fund owned were down.

He pushed such thoughts aside. "I thought, 'Who am I to question?'" Mr. Ross says. "This guy has a formula involving computerized trading....It's like Coke. We're not supposed to know the formula."

Mystery formula for computer trading, was it! SICC syndrome incarnate. I wonder just how many people lost their life's savings on similar delusions.

The syndrome has now spread to another critical agency, the FDA. At "Computer debacle: a Broken down process at the agency - or beyond?" I had written that:

I believe [the FDA's failures in building IT systems to track drug adverse events] represent more than a "broken down process at the agency." It's a "broken-down process" in the world of IT, i.e., the belief that IT is a homogeneous industry where expertise in business computing equips one to do all computing. I would be curious to know the backgrounds of those IT personnel who were involved in the leadership, planning and development of AERS II. I would bet most had a technical focus, and I would also bet none had expertise in medical informatics.

Perhaps one day the drug industry, including the FDA, will accept the IOM's recommendations on medical informatics.

Those recommendations involved acquiring and empowering specialized people, not a resort to purported cybernetic miracles.

What does the FDA choose to do instead?

Resort to cybernetic miracles.

In "New Drugs, Virtual Tests" (Wall Street Journal, Dec. 17, 2008) we learn that:

The U.S. Food and Drug Administration plans to use new computer technology to simulate how some drugs in development are supposed to work, helping researchers and regulators spot safety and effectiveness issues before late-stage tests on humans are completed.

Entelos Inc., a Foster City, Calif., company that has developed the technology, said it will enable researchers to obtain computer-generated test results in a matter of days or weeks, compared with years required for most major clinical trials. Far more "simulated patients" also can be tested than in conventional human trials.

Under an agreement with the FDA that Entelos announced Tuesday, three drugs now being studied for heart-related conditions in large human trials will be tested by the simulation technology. Neither Entelos nor the FDA would disclose which drugs will be involved or which companies are developing them. The value of the contract also isn't being disclosed.

... "What this study is about is trying to anticipate bad scenarios before they occur," said Robert Powell, associate director in the office of translational sciences in the FDA's Center for Drug Evaluation and Research.

So, instead of reliance on building better capacity to sample data from the real world, highly speculative and (as far as I know) untested-by-clinical-trials "cybernetic miracle" simulations will be used to evaluate early drug candidates. (Disclaimer: I have no knowledge of or connections to this or any other company involved in such work. I discovered this issue as a result of reading the WSJ.)

Bad enough that insufficiently powered studies and even seemingly robust studies in domains with small effect sizes, financial interests and prejudices, and other factors may be misleading (see "Why Most Published Research Findings Are False", John P. A. Ioannidis, PLoS medicine, 2005 August; 2(8): e124).

Now computer models and in silico simulations that purport to model actual, immensely complex and poorly understood biologic and environmental factors sufficiently well to enable real world predictions will be used to influence clinical decisions. The same clinical decisions that might best made empirically in real biological systems - e.g., via in vitro and in vivo methods. That is a fantastic leap of faith. To the moon in a hot air balloon?

I note the Dec. 17 WSJ article does state that:

Mr. Powell [Robert Powell, associate director in the office of translational sciences in the FDA's Center for Drug Evaluation and Research] said regulators "wouldn't make a decision to kill a drug based on a simulation," but the findings could be used in discussions with drug companies to influence decisions such as the design of clinical trials. Eventually such information also could affect prescribing information included in drug labels.

Knowing the narrow minded, profit-motivated, often conflicted boneheads who have invested our futures in the likes of Mr. Madoff's Ponzi scheme, Fannie Mae and the like, hedge funds, profoundly arcane bundles of financial toilet paper known as "securities" based on the former sources, etc., I have very little confidence that regulators (and worse, non-scientist managers overseeing biomedical research budgets and portfolios such as here) will not use these "cybernetic miracles" in making decisions -- both pro and con -- on new drug entities and other matters.

I propose a new term, The "cyber-industrial complex" to describe these spreading SICC scenarios.

Snake oil salesmen of the 19th century had little on today's Cyber-Übermenschen.

-- SS

Post Title → A 21st Century Plague? The Syndrome of Inappropriate Over-Confidence in Computing