ACCIDENT & EMERGENCY Diagnostic errors
It is reported that in the United Kingdom every 60,000 cases of cardiac scan diagnosis, 12,000 were misdiagnosed, resulting in the cost of about £600 million. “Despite the best intentions of our diagnosing doctors, human error is both common place and inevitable,” Josh Hughes observed. “Not all diagnostic errors result in medical negligence claims. In fact, there is very high threshold that applies and one that is designed to protect both patients and the medical profession. A medical professional will be negligent only if it can be shown that the diagnostic error was such that no responsible body of medical opinion could have made such an error.”
How might AI benefit diagnosis?
Currently doctors rely on diagnostic tools such as X-rays, MRI and CT imaging which are then interpreted by the human eye. However, as AI develops, Hughes believes it will exceed the ability of doctors to identify anomalies in imaging and other pathological tests, allowing earlier diagnoses based on physiological relationships that otherwise may have been missed.
“Given the sheer volume of data it will be capable of processing, AI could identify complex patterns and use them to predict or treat illnesses far more efficiently than we can now,” said Hughes. “Moreover, machine learning will allow the processing of thousands and thousands of medical scenarios over time so that it can begin to predict the common conditions that tend to exist or co-exist when someone is ill or becomes unwell. Similarly, AI may assist doctors determine what treatments tend to result in the best outcomes given a particular set of conditions. “In this way, one can begin to see how AI has the potential to reduce the number of negligence claims and thus reduce the financial burden upon the NHS.”
When things go wrong
If AI is to succeed, it is vital that we know who is responsible when things go wrong. Under the current system, when something goes wrong a victim has the opportunity to put his/her allegations to the person(s) responsible for the misdiagnosis. Determining the identity of that person(s) is generally straightforward. However, the scenario whereby AI leads to harm is less clear. Hughes asserted: “Without further consultation as to how such situations might be managed, it is an unattractive prospect that any number of bodies involved in the design, production, maintenance and/or operation of AI could seek to deflect blame onto one another thus delaying the victim’s access to justice. “There must, therefore, remain a transparent process allowing compensation to be recovered from a single entity such as the NHS, regardless of the constituent parts involved in the use of AI.”
Digital diagnosis
In the healthcare sector, technology has already been used to update patient records, improve care delivery and streamline processes. Yet AI is increasingly being heralded as a technology to achieve further breakthroughs in the sector – including the recently published potential to detect cancer. OpenText research reveals that UK consumers, too, see the advantages of the technology. A quicker diagnosis was identified as the biggest benefit, with one in three (33%) UK consumers believing robots would reach a decision on their condition much faster. As well as faster diagnosis, one in four (25%) British consumers believe they would get a more accurate diagnosis from AI. A quarter of UK consumers (25%) said robot technology would mean they wouldn’t have to rely on booking an appointment with a GP, while 24% said the biggest benefit would be no longer having to take time off work to visit a doctor. Commenting on these findings, Mark Barrenechea, CEO at OpenText, said: “Thanks to parallel processing, big data, cloud technology, and advanced algorithms, Artificial Intelligence (AI) and machine learning are becoming more powerful. “The Digital Revolution will drive an increasing reliance on self-service technology, machine to machine (M2M) communication and AI, and there is no denying that every
At the University of Bradford, researchers have developed an AI tool that has been taught to detect certain types of cancers from images of tissues.
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job in every industry will be impacted. The opportunity for innovation and change is limitless.”
No matter the benefits, AI use cases will be limited if British patients are not comfortable with the technology. However, technological advances have led to a growing level of trust amongst British citizens when it comes to AI and healthcare. In one recent report, PwC revealed that more than a quarter of Brits would now trust robots over doctors with heart surgery. This belief in AI is mirrored across the healthcare sector at a much wider level – OpenText research also revealed that nearly two in five (38%) UK consumers would trust the medical diagnosis given by AI and just over 1 in 10 (11%) said they would trust the diagnosis of AI more – or just as much – as a doctor’s diagnosis.
Digital health technologies
As well as AI, digital health technologies have made strides forward in cardiovascular and metabolic disease (CVMD) indications. Key market players include developers like Merck, Novo Nordisk, Roche, and Sanofi which design web services and apps for people living with chronic diseases such as diabetes. Companies such as AliveCor and BioSig also bring technologies to serve people with heart arrhythmias, including atrial fibrillation (AF) and tachycardia. Edit Kovalcsik, a senior analyst at data and analytics firm, GlobalData, said: ‘‘Key developments in 2017 included wearable devices, apps, and text messaging capabilities across the space.’’
At the University of Bradford, researchers have developed an AI tool that has been taught to detect certain types of cancers from images of tissues, while Merck uses Amazon Web Services (AWS) to develop voice-enabled systems, to help improve the management of people living with chronic diseases like diabetes. This is achieved by using Amazon Lex, the same deep learning
JUNE 2018
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