osoz world
Trapped By Popularity Bias And Irrelevant Priorities A biased strategy and half-baked priorities are the biggest threats to sustainable digitization in healthcare. Old unsolved problems were forgotten and replaced with alternative subjects that sound attractive and distract attention from real challenges. Caught up in the interest bubble, we lose essential goals Popularity bias is a phenomenon caused by the popularity of a given topic and public interest in it. For example, when an increasing number of people are seeking medical help because they worry about specific symptoms, it does not necessarily mean that such symptoms are worsening in a large part of society. The real cause may be the fact that a given disease has been commonly discussed in the media or a famous person was diagnosed with it. It leads to a media spiral of interest, which in turn gives the impression that a particular topic is currently
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very important. Bias caused by the popularity of certain issues can also concern the digitization in healthcare, as a result of which discussions on goals and priorities often border on populism and the center of gravity shifts to less important but more emotional topics. Examples can be multiplied infinitively. Artificial intelligence, Big Data, smartwatches and bands that check health parameters, machine learning algorithms, mobile health applications, trends, and new products: all of this attracts attention. It is not surprising because it shows a vision of healthcare which we would all like to be our reality. These topics are
new and sound attractive. Since we are tired by longstanding and still unsolved problems, it is easier for us to focus on a utopian future with theoretical problems that are easier to accept. In the meantime, there is a lot of dirty work to be done. It is necessary to fix the things that do not work but are indispensable for our future healthcare vision to come to life. We must make it possible to exchange medical data, ensure cybernetic security and equip hospitals with adequate IT infrastructure. But these issues have been discussed many times and bore many people.
AI cannot replace doctors yet, but we like to talk about it The future is fascinating because it is undiscovered. We ask ourselves questions about the doctor’s role in a healthcare system based on artificial intelligence that can diagnose patients and make clinical decisions. We wonder how we could
