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Popularity bias means the admission of patients to some practices, institutions or procedures (surgery, autopsy) is influenced by the interest stirred up by the presenting condition and its possible causes (Sackett 1979)

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.

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 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 centre of gravity shifts to less important but more emotional topics.

Examples can be multiplied infinitive. 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 long-standing 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 program an autonomous car to make ethically justified decisions in critical situations. These challenges are merely exciting and provoke discussions. They are also needed because early innovators initiate essential changes that are then implemented on a mass scale.

Popularity bias is not a problem, but it may turn into one. It is not about regulating the public debate in any way or assessing the significance of information, but rather about being aware of this phenomenon’s existence. It should encourage us to review strategic challenges and, most importantly, think whether the priorities we accepted had been appropriately defined. One of the many adverse side effects of popularity bias is the adoption of irrelevant success criteria. An example may be mobile applications developed by public institutions, whose adaptation to the market is often measured with the number of downloads rather than health effects or their actual use by patients. In this case, we are dealing with vanity measures. They include eagerly published statistics with the number of users on websites that give access to electronic health records, with the aim to prove the success of the entity responsible for the implementation of a given IT solution. It is more challenging to determine what follows from this number of users and the results do not always support the rhetoric of success, which is adopted in advance.

The popularity and media presence of digitization has significantly increased in recent years, which means that it is at risk of being caught up in irrelevant topics, especially because we are still at its primary and the most difficult stage, i.e., laying the foundations.

Today, it is not crucial whether artificial intelligence will replace doctors, but rather whether regional hospitals have adequate financial resources to invest in IT systems and keep up with the leading university hospitals in terms of digitization; or whether a doctor treating patients in a small town has the resources required to offer their patients tools as modern as those used by doctors from private clinics. According to a study “Benchmarking Deployment of eHealth among General Practitioners,” conducted in 2018 and commissioned by the European Commission, fewer than 50% of general practitioners can exchange their patients’ medical data with other medical facilities (with significant differences between individual countries). Only 8% of doctors have access to this functionality when necessary, to send documentation to a facility in another country. 40% of patients can make appointments online, whereas 20% can check laboratory test results on the Internet.

In e-health, you need to take one step back to take two steps forward

When it comes to the digitization of healthcare systems, we should focus on the necessary infrastructure so that every doctor and every medical facility has access to the same digital capabilities. We do not need fireworks; it is enough to provide equal digital opportunities and a uniform base. To do that, we need to make substantial structural investments and spend billions on fast Internet, IT systems, data security systems, and staff training. The digitalization in healthcare needs to focus on the fundamental issues of interoperability, a well-thought-out legal framework supporting the development of innovation, and a safe and trusted information exchange system. It is necessary to provide equal opportunities in access to e-health benefits and make a shift to a standardized digital form of all the collected medical data. When the basic infrastructure is built, we can move on to other priorities.

Regarding the digitization of healthcare systems, we cannot jump from one stage to another without completing the previous one. Such unsustainable development is what we are witnessing now: we are thinking about the coordination of healthcare services and the personalization of treatment, even though data is still stored in the locations in which it was generated (silos), which means that it is impossible to create a list of interactions between drugs prescribed to a given patient by different doctors. Moreover, tests are still doubled, which means that financial resources are wasted, whereas care is scattered and far from coherent. Not to mention ambitious plans to move away from a healthcare system focused on treating patients in favour of a system that puts prevention at the centre of its attention. We cannot save on these priorities.

Laying the foundations of e-health is an ungrateful task, especially for politicians, who expect a quick return on their decisions, reflected by social popularity during their 4-year term of office. Europe and the Member States are developing artificial intelligence strategies. They have already started to outdo each other in plans, even though the idea of using AI in healthcare is still in its infancy. Instead of, or in parallel with, making daring plans that are far ahead, we should announce great plans for the provision of equal digital opportunities. This challenge does not sound attractive. It will not become trendy and praised. Still, today it is a question of responsibility for what the digitalization in healthcare will look like in a few years and what benefits it will offer us. Otherwise, we will be stuck in an alternative reality based on popularity bias.


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