Have you ever wondered what is going on in your doctor’s mind during a consultation? A large part of it is likely to be a process of observation, data gathering and analysis based – more or less accurately – on what you say. I emphasise the ‘more or less’ because many patients are surprised to see how often what they say to doctors is ignored or just plain misrepresented in their medical reports. And if, as Einstein noted in relation to physics, “Theory determines what is observed”, then in the case of the ‘observations’ and ‘data’ gathered by the doctor in listening to you the same applies. Indeed it is often the case, paraphrasing Einstein, that in the case of biomedical practice ‘Theory’ determines not just what is ‘observed’ but even what is heard by doctors. The biomedical practitioner’s chief aim is, like a radio, to distinguish ‘signals’ from ‘noise’ – ‘noise’ being anything the doctor regards as scientifically irrelevant to exercising his diagnostic skills – such as the larger life story behind a patient’s illness, their emotional experience of illness – and of its effect on their life.
Yet what if what doctors are chiefly doing while listening to you is merely functioning as a human ‘black box’ between what they regard as significant ‘input’ and giving what they regard as all-important ‘output’, i.e. probable diagnoses, suggested treatments, prescriptions, referrals for further tests or to specialists? As this ‘black box’, what is really going on in your doctor’s mind is comparable to them going through a type of predetermined computer ‘algorithm’ or ‘decision tree’ in order to arrive at the most likely or statistically probable ‘diagnoses’ from the ‘observations’ and ‘data’ he or she is collecting from you. In which case, however, the doctor is effectively functioning as nothing more than a sort of human computer – and therefore could just as well be ultimately replaced by a computer – one fitted out with what is called ‘automated diagnostic software’. If you think this is a wild, futuristic idea – then think again. For ‘Computer-Assisted Diagnosis’ is already a reality – and is even used to get a ‘second opinion’ by the most highly revered of biomedical diagnosticians.
“At last he spoke. “Lymphoma with secondary hemophagocytic syndrome,” he said. The crowd erupted in applause. Professionals in every field revere their superstars, and in medicine the best diagnosticians are held in particularly high esteem. Dr. Gurpreet Dhaliwal, 39, a self-effacing associate professor of clinical medicine at the University of California, San Francisco, is considered one of the most skillful clinical diagnosticians in practice today… Since medical school, he has been an insatiable reader of case reports in medical journals, and case conferences from other hospitals.To observe him at work is like watching Steven Spielberg tackle a script or Rory McIlroy a golf course. He was given new information bit by bit — lab, imaging and biopsy results. Over the course of the session, he drew on an encyclopedic familiarity with thousands of syndromes. He deftly dismissed red herrings while picking up on clues that others might ignore, gradually homing in on the accurate diagnosis.”
Nevertheless the same New York Times report asked: “Just how special is Dr Dhaliwal’s talent? More to the point, what can he do that a computer cannot?”. It also acknowledged that even the famous Dr Dhaliwal “…occasionally uses a diagnostic checklist program called Isabel, just to make certain he hasn’t forgotten something.” It adds that the program has yet to offer a diagnosis that Dr Dhaliwal missed” – without saying whether this program could actually have done the same job as Dr Dhaliwal, and that in even less than the 45-minutes he is given at medical conferences to display his showman-like skills in diagnosing “vexingly difficult cases”.
Yet aside from a small number of diagnostic ‘geniuses’ and ‘gurus’ of the sort represented by Dr Dhaliwal (as well as in the fictional American TV series ‘Dr House’ – a doctor with similarly encyclopaedic knowledge of biomedicine and insatiable interest in the latest medical research), today there is not a doctor in the world, whether generalist or specialist, with a mental ‘storage’ space of enough encyclopaedic capacity or ‘Gigabyte’ equivalents to remember even what he or she learnt in their medical training – let alone find the motivation or time to keep up with the latest biomedical research. So we end up with a system whereby, reaching the limits of his or her knowledge, your doctor will refer you to a specialist of one sort or another – even though the knowledge of specialists too, is not encyclopaedic – and is no less innately limited by the interest in and time they have in keeping up with the latest research and developments in their field. Hence also the often diametrically opposed opinions that find expression among researchers and/or clinical practitioners in the same specialty – one hardly compatible with the smug complacency of doctors or specialists each of whom generally claim their own personal viewpoints, diagnoses or clinical judgements to be the most accurate or ‘objective’.
The sad fact that comes to light here is that it is precisely because medical practice and the functioning of the medical mind takes data accumulated in the form of impersonal biomedical ‘science’, ‘research’, ‘evidence’ and ‘observations’ as its diagnostic foundation, there is nothing that sophisticated diagnostic software with ever-larger databases of biomedical knowledge could not in fact do better than any human doctor – generalist or specialist. Given also that biomedicine effectively treats the human body as no more than a biological machine, much like a car, that may be in need of repair, it comes as no surprise to read the following arguments for a new ‘Automated Medical Diagnosis System’ – the aim of which is to eliminate “human bias” of any sort – even in using current forms of ‘Computer Assisted Diagnosis’:
“Cars can be plugged in at the mechanics for electronic diagnosis, customer issues logged in enterprise support systems receive immediate potential solutions to their issue prior to a customer service representative looking at it, and computers send error reports when an application crashes. In industries across the world automated diagnostics becomes more and more prevalent leveraging continually advancing algorithms that become increasingly intelligent in identifying solutions to known problems. Yet in the health care industry Doctors have outdated and limited access to potential solutions… Enter symptom, disease type, test name or code requests one physician diagnosis database. As with any human search that begins with keywords chosen by the user, bias inherently influences the results. If a Doctor has an assumed diagnosis, they will immediately begin searching for further evidence that their assumption can be validated. And if it isn’t, then they will have missed other potential diagnoses. Additionally, if the Doctor begins searching by symptoms, while these may be accurate, the order or weight given to any one symptom will give a bias toward related diagnosis when in fact, there may be a symptom not given any credit and thus not included in the search. Regardless of whether you consider today’s databases or the older process of researching in books, the results are always influenced by the bias of the researchers’ initial assumptions. What is needed instead is an approach that minimizes human bias and considers all relevant and irrelevant data in determining a diagnosis. Computer software does this well.”
“With an automated medical diagnosis system, Doctors could be presented with multiple potential diagnoses based on all of the patient’s current and past details. Such a system could be designed for automated medical diagnosis that is based on probability, utility and decision theory.
Essentially, the computer software could be fed human observations of symptoms, test results, and any machine data collected such as blood pressure, heart rate, oxygen levels, etc. The software would then compare these observations with a database of potential diseases and external agents (e.g. viruses, bacteria) to determine the most probable diagnosis. These results would then be presented back to the doctor along with a probability rating indicating which ones are likely most relevant or accurate. Each diagnosis could also then be presented with additional direction to the doctor to further explore for additional symptoms and/or order an additional test. These additional observations and/or test results would again then be fed into the system where it could re-evaluate the probable diagnoses cancelling out some while raising the probability of others. In addition to immediate interactions with the software, Intensive Care Unit’s machine observation data (e.g., oxygen levels, heart monitors) could be constantly fed into the system to allow the software to be looking for patterns that match other known diagnosis that would never be able to be caught by a human as it would take too much time to evaluate the data.”
What we are presented with here is indeed a futuristic image – albeit a dystopic one. Already hospitals and large clinical surgeries with multiple doctors have become, as Dr David Zigmond notes, more like airports than the so-called ‘old-fashioned’ surgeries run by family doctors – who knew their patients and their lives intimately. In contrast, in our clinical ‘airports’ you check in, go through a gate to see to see a doctor and check out with a prescription or referral for a further test of some sort or a consultation with a specialist.
For decades now, employment in manufacturing industries such as car-making has fallen through the introduction of robots that are pre-programmed to do the job required of them more precisely than any human worker could. Now however, we are confronted with the prospect of human beings, all seen as anonymous body-machines to be processed in automated high-tech hospital ‘repair stations’, and, as in some futuristic science fiction movie – conveyed on a factory-like medical conveyor belt. Stop one on the belt: patients’ bodies are CCTV’d and perhaps even scanned in different ways while what they look like and say is digitally recorded to be searched for diagnostic signs, keywords and patterns. Stop 2: they are sent on a second conveyor line where blood tests or further scans are conducted automatically. Stop 3: they are either discharged from this fully automated hi-tech hospital ‘garage’ – where they are given any necessary drugs, a dose of radiotherapy, are either then conveyed to a stationary ‘cubicle’ for further processing – or else to an operating theatre ‘manned’ entirely by robots. And all this with the whole technological process merely supervised by a handful of technicians and actual human doctors. Finally, Stop 4: either a crematorium or a bill to be paid – as in coming to the exit barrier of an airport car park.
Not only is this science fantasy prospect a conceivable one – it is also an entirely rational one in the framework of biomedicine. Which only goes to show how totally irrational medical ‘rationality’ can be. For what this picture essentially lacks is what is most essential, not just to healing (as opposed to mere ‘medicine’) but to human health as such – namely the care and care-giving of other human beings – not to mention truly human insight, observation, empathy, as well as human life experience and life understanding. On the other hand, it is no less conceivable that the development and refinement of ‘automated medical diagnosis’ could serve precisely to free doctors of the future from their current role as human computers, allowing them instead to devote most of their time and awareness to their human role as healer, care-giver or ‘life doctor’ – there to explore the patient’s experience of illness and its meaning in the context of their lives and relationships – something no computer software or database will ever be able to do. In this way biomedical knowledge would find its true place as a tool subordinate to the art of healing – rather than becoming a substitute for that art. And since the terminology of biomedical science itself is as rich in metaphor as in ‘fact’, more precise and accurate biomedical diagnoses would also allow for more accurate and penetrating analyses of their own symbolic dimensions of meaning.
Until we reach this point however, next time you see a doctor bear in mind the question posed at the start – what is actually going on in the doctor’s mind and what is he or she actually there for? For it will make a world of difference to your health whether the doctor is only there for a specific ‘what’ (for example, to go through a quasi-automated mental-diagnostic process and then refer you on for further medical processing) or whether the doctor is there for a very specific human being or ‘who’ – for you.