Tuesday, October 30, 2012

Thomas Sydenham 1624-1689


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I give a 1.5 hour lecture next week on the history of medicine. I am not a historian. I got into this while in medical school at the University of Michigan when I was elected to the Victor Vaughan Society, a medical history group that met once a month and in turn presented papers on some person or subject of historic interest. It was truly an elegant gathering; the experiance stuck with me.
I think my most interesting character for next week, outside of Hippocrates himself -- 2,000 years earlier, will be Thomas Sydenham. His father was a gentleman of property, Thomas was born in Dorset, educated at Oxford, A Saxon, Sydenham fought for the Parliament during England’s. Civil War as a cavalry officer. He taught the Hippocratic method: inductive reasoning, virtue, credible signs and symptoms, and differential diagnosis with meticulus attention to the patient.

Sydenham had the gout. Famously, he proclaimed, “gout attacked the rich more often than the poor, and it rarely attacked fools." ---“Those who may choose, may accept the present writer.” -- “If you drink wine, you have the gout…If you do not, the gout has you.”

Sydenham defined many disease entities with their signs and symptoms: Sydenham’s chorea for example. He described the association of scarlatina and erysipelas with chorea and may well have made the association of rheumatism and valvular heart disease.



 

Sunday, October 21, 2012

The Future of Medical Diagnosis


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Medicine, the profession struggles with its identity. Will we be physicians in the likes of the great scientist philosophers and humanists since Hippocrates? Or, will we succumb to the trend of commodifying the profession?

Health and Human Services (HHS), National Institution of Health (NIH), Centers for Medicaid and Medicare Services (CMS), Insurance companies, regional Health Information Exchanges (HIE) will mandate certain quality metrics in the Electronic Health Record (HER) and the uniform claims submission process for reimbursement. Programers will likely build these metrics into the software developed by various venders of the EHR. Doctors are familiar with Best Evidence and some of those treatment standards are already appearing in EHRs. A new feature will be Clinical Decision Support (CDS). Best Evidence largely deals with treatment protocols. CDC will deal mostly with diagnosis. What follows is a discussion about how the later, CDS, deals with differential diagnosis, diagnosis and the problem list.

The review of systems (ROS) and the differential diagnosis lie at the heart of the matter and how electronic medical records interface with these two intellectual processes. Each item in the ROS, signs and symptoms related by the patient, becomes critical data in the process to follow. The negative response is as significant as the positive -- maybe more. Each positive response, when confirmed by further questioning, evokes a list. The list is critical as well and might as well be indelibly imprinted behind each data point or on the mind of the physician.

When completing the ROS, one then has a number of responses, each with its list of etiological possibilities. One or more diagnostic possibilities appearing on separate lists tend to point to the underlying problem and contribute to the establishment of a differential diagnosis.

Here is where statistics comes into play. The more often a diagnosis appears on multiple lists and the more completely the signs and symptoms on the ROS fulfill the attributes of a diagnosis, the more likely you are on the right track. However, all overlapping signs and symptoms are not equal and many illnesses have similar symptoms. Furthermore, individual patients seem to have a limited range of symptoms to account for a wide range of possible illnesses. Ongoing and realtime statistical analysis of the differential diagnosis with apparent outcomes and the coupling together of patient data with the vast store of medical information greatly assists in the interpretation. Database mining can provide statistics that the mind cannot grasp. The human mind, however, does far better at final interpretation.

The mindful and highly experienced physician sees the above analysis and assembles a differential diagnosis with a scanning logic. Other physicians have another sort of mind that rather than scanning has a concrete way of thinking. The later demands clear cut answers. Both approaches work but with the same human limitations. Most physicians navigate a differential diagnosis quite well but the process demands a high degree of commitment to the art -- and still is subject to error. There are in fact many missed and wrong diagnoses. Misses are almost inevitably due to omitting the ROS or ignoring one or two of the responses when they do not fit the assumption. Larry Weed[1], the inventor of the problem oriented record (POMR), insists that any positive, not accounted for by the diagnosis, belongs on the active problem list.

Our mind thinks and makes individualized judgments that the computer cannot. The computer on the other hand remembers and does statistics. We do not remember so well and we do not manage statistics well on a large database. We do need to take into account the computer’s future capabilities, however. So far the computer does not think, but IBM's Watkins comes close.

Statistics are limited to the relevant population. Do you depend on statistics developed on a national scale, an international scale or limited to a local population that might be more relative to the patient at hand? I say might be because each patient is a one of a kind individual. The only statistics that matter might very well be the patient's own genomics. The individual genome, despite the nail biting, is falling in price and will soon be ubiquitous. We need to be sure the tests are not sold like snake oil by bathers, naturopaths, charlatans and opportunists.

Arguably, we should do the thinking and follow a strategy in which the computer remembers the data, the lists and analyses statistically on a realtime basis, genomics included. Let the computer couple your precise clinical data with the vast store of medical terminology, nosology, and the salient features of each. The value here is in not missing something and not getting stuck in a wrong assumption. The analysis should present to the physician a credible preliminary differential. With or without assisted memory and coupling to the vast store of medical knowledge, the ROS and of course subsequently accumulated data are the key to patient safety and care. The ROS would of course be only the beginning. The rest of the history and physical examination-- hopefully you did a physical -- would yield further support to one or another of the hypothetical problems suggested by the ROS and your own pattern recognition. From this point on the human brain takes over the thinking with the advantage of the computer's perfect memory and superior statistical skill. The patient remains an individual, however, and will often defy the best of statistics. The physician's thinking combined with an intimate connection with the patient remains essential.

Some would advocate a process in which the computer and pre defined procedures defined by best evidence as written by so called experts take the prime role and relegate the physician to insuring the validity of the data points. The rationale to this approach lies in the frequency of diagnostic error and the never ending expansion of diagnostic and treatment procedures that do more harm than good costing more and more.

Others would say, we need to go back to the physician as the humanist and scientist of old with vast experience and ongoing medical education in a professionally structured society, dedicated to excellence. Today we are at a cross roads. The road to subordination, however, may have already been taken. Whichever path we follow, patient safety, access and consistent in depth handling of the data are primary. The differential diagnosis is critical to achieving anything like the health metrics of the rest of the industrial world.

Summary and Conclusion
 
Physicians and Medical Schools struggle with a conflict between physicians in the classic role of science, art, diagnosis and a newly proposed role in which the physician practices in a role subordinate to the computer, algorithms, protocols, check lists and the authors of Best Evidence.
At the heart of the conflict lies the complex process of diagnosis and the choice of individual treatment. To meaningfully apply the dictate of Best Evidence, one needs the right diagnosis. We suggest that the best application of computers, statistics will be achieved when the computer applies its faultless memory and capacity for data with dynamic real-time statistical analysis not on mass populations but on the internal data at hand. This strategy provides data more relevant to the individual patient. The strategy also leaves the physician and the patient with the choices, the judgment and the mindfulness of that data. The physician thinks, the patient participates, the computer remembers.

Arguably, the critical focal point for achieving the right diagnosis or at least having the right diagnosis in the differential rests with the review of systems, ROS and subsequent physical and laboratory findings. If this data is not complete, including negatives, the diagnostic process is compromised.

When the differential diagnosis depends on the physician’s memory, missed diagnosis often results from initial assumptions. Omission of the ROS, ignoring positive or negative responses and findings when they do not fit the assumption often leads to a wrong diagnosis. An inability to mindfully apply valid associations to literally thousands of diagnostic possibilities lessens the accuracy as well. When the best evidence, derives from mass-population statistical analysis, that analysis may be all wrong for the individual patient.

The direction medical schools point new physicians over the next generation or two will greatly affect the health of our Nation and the outcome for our individual patients. Reducing physicians to mindless gatherers of data and surgical robots leaves the judgment in the hands of a few of necessarily national experts. It stifles scientific advancement. Once you fix procedures and protocols and define best evidence, you have a one shoe fits all situation that may not apply to the individual. You have a static routine devoid of the variety and experimentation that defines the core of the scientific method. The unintended consequences of computer directed diagnosis, best evidence and a unified standard may turn out to be ulterior motives of political, religious, or economic entities driven by greed. Government, the courts, drug companies, insurance companies or the association of hospitals in which we work may inject subtle deviations for their own benefit.

Our further plea is for a continuation of classical medical education with bedside teaching and advancement to even higher levels of medical training. The honor should be limited to those worthy of the privilege in the tradition of the great physicians and surgeons of the past. Further advancement might require all to graduate as PhDs with core competence in genomics and database management. The genomics seems obvious. Medical schools must renew their covenant with patients and local providers serving both in exchange for teaching material, autopsies and CME. There are too many providers and peripheral merchants feeding at the healthcare trough. More physicians relative to population will not help. We have far too many specialists. Less well trained providers will not improve outcomes or meet the needs of our future.

Will we unionize and become nine to five Feldshers who follow algorithms and protocols? Will those dictums of best evidence be out of date or self serving? Will professional behavior be dictated and enforced by political and economic interests? Or, will a renewed pursuit of excellence and medical education put the patient first with the physician directing the tools of health information technology, translational medicine, biomolecular advances, research, science and genomics? The future is ours to grasp.
 

[1] Medicine in Denial, Lawrence L. Weed and Lincoln Weed April 2011, Amazon

Thursday, October 11, 2012

Type Two Diabetes (T2D)


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Cell 150, 1223-1234, 2012
Domenico Accili at Columbia studying the mouse Foxo1 gene discovered that pancreatic Islet β cells do not die in type-two diabetes (T2D) but revert back to endocrine progenitor cells that are unable to make insulin. This opens the possibility of treating T2D by turning these dormant cells back to normal. Once more an exciting contribution from genomics.