With Amazon, there is no going back

Paco Miralles

A winter desert. The author discusses his post with friends: "The future of medicine is changing daily, but the point of no return will be when Amazon enters the healthcare market ..."

I noticed the smile on my friends' faces when I made these comments to them. I do not have enough scientific relevance to lavish myself in informative talks, so my remarks were in opinions of the same level as those referring to what Atletico will do if it does not qualify for the Champions League. They thought it was an exaggeration and that the medicine was indeed changing a lot, but no so much.

A few days ago, the CEOs of Amazon, J.P. Morgan and Berkshire Hathaway announced that they have already started their journey in the healthcare market with the creation of Haven. It was the culmination of an agreement that they closed in January 2018 to deal with the rising costs of healthcare. At the forefront of this project is Atul Gawande, a prestigious surgeon, author of books such as Being Mortal, a text that every doctor should read, especially if she is in her training period. Gawande has made an accurate statement of intent in his first words talking about the company's goal: "We want to change the way people experience health care to make it simpler, better, and lower cost." A good summary of what could be considered a medicine that adds value.

The bibliography that matches the future of medicine with the development of the sciences ending with the suffix "omics" has grown in recent years: genomics, metabolomics, metagenomics, proteomics, etc. It's all thanks to technological development in various fields. Such has been the growth of these subjects that wiki pages have emerged to collect information about them. The importance of these disciplines that combine biological knowledge with engineering in the coming times is undeniable. Still, I believe that the real revolution will come from "dataomics".

Some sectors have been visionaries in these matters, and this has given them a clear competitive advantage. Data management was the key to Obama's victory in the American elections. By using big data analysis, a group of experts locked in what was called "the cave" were able to raise more funds, predict participation and make predictive models for decision-making based on billions of data. The goal was met!

The implementation of big data analysis in the world of medicine is slower than in other sectors such as banking or commerce. Medicine has had a growth of knowledge based on its own body of doctrine. Physicians are reluctant - and sometimes obstructionist - to accept improvements from other areas. For example, some engineering models, despite having proven to optimise many organisations, we reject them arguing that ours is not a manufacturing company and that it is about fads. How can someone who is not a doctor teach us how to organise the health system!

This resistance, not only to leave our comfort zone but also to let strangers enter, what is it? A sign of self-sufficiency? Lack of intellectual humility? Defensive attitude towards the unknown? We should admit that, at best, we know very little because our theoretical field of knowledge is vast. It is difficult for us to learn an increasingly extensive science, where we must integrate scientific knowledge, technology and humanism.

Due to our training model and culture, it is difficult for us to accept that a car company like Toyota has designed a management model, Lean Healthcare, which, applied to healthcare, improves healthcare processes and patient satisfaction. It is difficult for us to admit that artificial intelligence systems are capable of reducing false positives by 11% (lesions classified as tumours) compared to six radiologists who are experts in lung cancer screening by CT, as recently published in Nature. We look with suspicion at virtual assistance models such as the KRISTINA Project, in which we have a multilingual social worker through a chatbot.

In recent years, most of the advances in medicine are related to the improvement in data collection and analysis, as Jordi Varela perfectly reflects in his post on machine learning. I often talk to fellow clinicians, who generate and manage thousands of data, their usefulness and the sense of loss of opportunity for not exploiting them. Everyone agrees. However, practically none of them support me when I propose their systematic study in order better to understand our behaviours and those of our patients. Deep down, they believe that this issue is more of managers. Many rely on the fact that their systematic and prospective collection is not lacking in any measure. It is not entirely true, and I think it corresponds to adverse effects of the culture of medicine based on evidence, which has already been overcome by different models of information extraction from clinical history, as the Savana project shows.

These and many other examples make me think that we are cheating on ourselves in solitaire. What we find difficult is not learning, but unlearning. Adapting to a change in the new healthcare paradigm forces us to erase part of our hard drive and accept procedures that hitherto belonged to others. We must get used to the emergence of new stakeholders in the healthcare environment and to the flexibility that the medical profession often lacks.

The emergence of an expert data management company, such as Amazon, supported by a practically inexhaustible financing capacity and by an insurance holding company, opens a new horizon in medicine. Amazon has not only changed the online market and retail, but it has changed the world economy. You have information about your clients that allows you to reach beyond their account details. You can find out how many children a given client has and how old they are; if they play sports, if they eat healthily, if they are obese and if they care about health, among other things. With the recent purchase of PillPacks, a pharmaceutical company in charge of packaging the buyer's drugs in a personalised way and taking them to their homes, they will begin to know data about our treatments, from the prescribing doctors, about the adherence rate of the patients, the possible drug interactions. It may be that a company without a health structure or hospitals (for now), ends up becoming the best knowledge system about our health and our disease models. Hopefully, it will be the final push to promote valuable medicine.

Who knows, maybe medicine will be studied by Amazon tomorrow. Set to be disruptive... 

Link to blog Doctor Miralles