|Year : 2019 | Volume
| Issue : 4 | Page : 273-274
Clinical skill versus technology
Department of Ophthalmology, Head of the Department, Sundaram Medical Foundation, Chennai, Tamil Nadu, India
|Date of Submission||01-Dec-2019|
|Date of Acceptance||02-Dec-2019|
|Date of Web Publication||26-Dec-2019|
Dr. Murali Ariga
Department of Ophthalmology, Head of the Department, Sundaram Medical Foundation, Chennai, Tamil Nadu
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Ariga M. Clinical skill versus technology. TNOA J Ophthalmic Sci Res 2019;57:273-4
“Medicine is learned by the bedside and not in the class room. Let not your conception of manifestations of disease come from the lecture room or read from a book: See and then research, compare and control. But see first.” - Sir William Osler
Stephen Hawking, the renowned physicist and cosmologist, and Elon Musk, a technology entrepreneur and CEO of Tesla, recently cautioned that the emergence of technology could mean an end to the human race. As health-care technology comes to play an increasingly prominent role in diagnostic decision-making and patient management, could it mean an end to human doctors? It has been observed that doctors are becoming more reliant on technology in making diagnoses and carrying out treatment. It is known that once such technologies have been introduced into routine practice, it is difficult to reduce their use, even in situ ations where they have been shown to be ineffective or no more effective than a less expensive alternative.
Considering the diagnosis of angle closure disease for instance, the subjectivity of gonioscopy, the requirement for training, and high variability among the clinicians have prompted research in alternative assessment techniques such as anterior segment optical coherence tomography (AS OCT). AS-OCT is being increasingly used by clinicians to screen for angle closure disease. The scleral spur (SS) is used as an anatomic landmark to classify a closed angle in OCT images, whereas trabecular meshwork (TM) is used for gonioscopy; therefore, it is possible that OCT may detect more closed angles (false positive) than gonioscopy because any short iridocorneal contact just anterior to the SS in OCT images was classified as a closed angle, which is defined as open by gonioscopy. Compression gonioscopy which is a clinical skill/technique cannot be performed by OCT and so also identifying TM pigmentation and visualization of new vessels cannot be done by OCT.
Can a machine detect/diagnose glaucomatous optic neuropathy (GON)? – while new devices with artificial intelligence do seem to be capable of effectively screening for diabetic retinopathy, is the same applicable to GON?. The dilated clinical fundus examination of the optic nerve head and retinal nerve fiber layer after mydriasis has been recommended as the gold standard for glaucoma diagnosis, given its advantage of offering a stereoscopic view of the optic disc with a 78D or 90D lens and using the optics of a slit lamp. A newly developed deep learning algorithm for the detection of referable GON from monoscopic color fundus photographs has recently been reported. Coexistence of high or pathologic myopia was the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results. In any such screening, false-positive results create unnecessary referral and burden to the health-care system and require further investigation by eye care professionals.
All clinicians are not created equal. We learn and prioritize our skills in different ways. But, if we are not taught to value and trust the physical examination, if we do not have the opportunity to see it influencing patient management in positive ways, we may eschew it and instead use easily available imaging technology, a more expensive and often misleading approach.
There is also a “patient” factor in disease management – we all encounter an occasional patient who is unwilling to undergo a subjective test like automated perimetry and instead prefers a quicker, objective test such as OCT imaging. The World Glaucoma Association consensus clearly states that both optic nerve structure and function should be evaluated for the detection of glaucomatous progression and that there is no specific test can be regarded as the perfect reference standard for the detection of glaucomatous structural and/or functional progression. Progression detected by functional means alone will not always be corroborated using structural tests and vice versa. This is due to the nature of testing analysis, individual variability, and the structure–function relationship.
The importance of good teachers cannot be over emphasized. In the words of Fred, we need more teachers who know and understand the pathophysiology, clinical features, and natural history of diseases; teachers who know what tests, if any, to order, when to order them, and how to interpret them; and teachers who use advanced technology to verify rather than to formulate their clinical impressions. We need teachers who first use the stethoscope, not an echocardiogram, to detect valvular heart disease, and teachers who first use the ophthalmoscope, not magnetic resonance imaging, to detect intracranial hypertension. The lack of clinical skills has been termed hyposkillia! The Oslerian dictum “listen to the patient, he is telling you the diagnosis” should be resurrected in today's bedside clinical skill teaching. The art of history taking and targeted clinical examination would go a long way to promote humanism, professionalism, and build better doctor–patient relationships.
As we look forward to ring in a new year, the new editorial team of TJOSR can look back in satisfaction over what has been achieved in the past year after the team took over in 2018. Six issues of the journal, which is now indexed and peer reviewed, have been compiled and mailed to TNOA members. The Go Green Initiative has been very well received and we look forward to more members opting for e-copies. A soft copy is now being E-mailed to all members whose E-mail is registered with TNOA. We invite all members to submit their scientific work in the form of review articles, original work, and case reports. Let's join hands to take TJOSR to greater heights – it is our journal!
| References|| |
Li Z, He Y, Keel S, Meng W, Chang RT, He M. Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs. Ophthalmology 2018;125:1199-206.
Weinreb RN, Garway-Heath DF, Leung C, Crowston JG, Medeiros FA, editors. Progression of Glaucoma. Kugler Publications, WGA Consensus; 2011.
Fred HL. Hyposkillia: Deficiency of clinical skills. Tex Heart Inst J 2005;32:255-7.
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