Workers within the medical field have it very hard when it comes to implementing new technologies. Lisa Sanders explains in her book, “Every patient tells a story ,” what impact trying to implement diagnosis systems into hospitals could have on the doctors and nurses.
1. Firstly, if we were to think in terms of current technology, doctors, nurses or medics would require extra-time to access this database of diseases and their complementary treatments. They would have to dismiss the patient for 20 long minutes, so they can go across the room or into their office, to a computer where they input the data they have, and then apply a differential diagnosis to all the possible diseases that will show as results to the query.
Following this, one can further say that a doctor is as capable as the diagnosis system, and there’s no need for such a thing to consume their time.
“Things can shift very quickly in the emergency room,” Dr. Dhaliwal said. “One challenge of this, whether you use a computer or your brain, is deciding what’s signal and what’s noise.” Much of the time, it is his intuition that helps figure out which is which.
This argument is very powerful, and can dismiss the use of such technology in hospitals. It saves money, it saves time, and it also saves lives. Even though, say purely fictional, 5% of the patients will die undiagnosed the remaining 95% of patients will get diagnosed and then receive treatment. It is therefore not worth trying to diagnose the 5% at the cost of taking extra-time for 100% of the patients and risking complications.
N.B. There are already diagnosis systems that help in the diagnosis process, however they are not so widely used since the software is very expensive (circa 120 000$/computer), and because doctors believe that they don’t need such tools.
But these pieces of software are not here to complete or compete the doctors.
“You aren’t going to put anything on a list that you don’t think is relevant, or didn’t know to think of,” he said. “And that could limit your chances of getting a correct diagnosis.”
They are here to help doctors to construct a complete list of possible diagnosis. Humans are lazy and narrow minded, and this software solves the problem of laziness and broadens our spectrum.
Dr. Dhaliwal said: “You might think you’re in familiar territory, but the computer is here to remind you there are other things.”
We can all agree, more or less, that trying to get doctors used to such pieces of software is hardly possible. There is trouble in getting them used to, and then there is trouble after they get used to – i.e. becoming dependant on the software –
To summarize all this, the arguments above are pro and against the use of diagnosis systems in medicine. With the technology that is currently in use, the contra arguments have a majority over the pro arguments. But what would happen if we were to consider tomorrow-day technology?
2. Secondly, a diagnosis system may add a random error. Say, you name a few symptoms out of which one is not in connection with the rest of the symptoms (take one of Dr. House’s cases. He has a patient showing multiple symptoms, but only 90% of these apply to the disease that the patient has) – or is simply, as a doctor would hate to say, a coincidence. The computer will exclude some of the possibilities.
To put this in a different perspective, at the first point I said that:
They are here to help doctors to construct a complete list of possible diagnosis.
There is a narrow possibility that the so-called complete lists are not so complete, and that because of a random error we’re heading for a bad diagnosis. This would mean that out of the hypothetical 5%, about 0.1% would still receive a bad diagnosis or no diagnosis at all. Translated to number, this means 10 dead patients out of 1000.
This would be the result in case we use a highly reliable diagnosis system. But what if we were to use something other than a computer?
Try it yourself: Isabel Diagnosis System
Note: This is the first part of the article (1/2). I would like to challenge you to think for yourselves, and imagine the possibilities.
In part 2/2 I will summarize a few up-coming technologies (by 2020) that could solve these ‘extra-time’ and user approach problems.
2. Book “Every Patient Tells a Story” by Lisa Sanders
3. Book “A checklist manifesto” by Atul Gawande