Any time you read about efficiency in healthcare, you're also indirectly reading about how the lives of patients and people with chronic conditions are improving. Time is a currency today.

Chronic patients are often in a disadvantageous position compared to the healthy population. Their physical wellbeing can often be impaired, they spend a lot of time in the healthcare system and spend out of pocket money for therapies, deductibles, lost working hours, and other disease related expenses. This can turn into a vicious cycle - in the US, if you lose your health, you can quickly lose your job, and in your health insurance. 

AI has the potential to affect patients on many levels positively.

It can improve appointments scheduling and decrease waiting times. Imagine how the patient journey could be changed if technology could support patients as it helps customers. The US insurance company Anthem is looking at the development of a system where the individual would be matched with the best provider, based on his needs and characteristics. The patient could be triaged with a bot instead of a doctor and referred to the doctor only when needed. 

The idea of bot triaging has been appealing for years now, because of the promise that AI aided diagnostics would be more efficient and more accurate compared to doctors. After all, machines don't get tired. AI can digest unparalleled amounts of information compared to doctors.

When you think about it, doctor's are not a very popular species these days.

A study published in 2015 in The American Journal of Medicine showed second opinions resulted in changes in diagnosis 14.8% of the time and changes in treatment 37.4% of the time. 

Overconfidence of doctors in diagnosing is a known problem, and you might have heard that the third cause of death in the US is a medical error. Moreover, 90% of patients with poorly defined conditions remain undiagnosed. Over 7000 rare diseases exist in the world. In Europe, they are defined as disorders affecting less than 1 in 2000 citizens.

With precision medicine and big data, there is hope that diagnostics and treatments would improve.

The challenge of AI development is that it needs large quantities of data to train. Data quality is a huge issue in healthcare, also because of poorly designed IT systems, which turned doctors in burned-out highly paid data clerks. 

The Integrated Medical Information and Analytical System in Moscow connects more than 660 clinics and over 23.6 thousand medical practitioners in Moscow and was put in place with the aim of eliminating waiting times. Soon after the introduction, the system detected an outbreak of cholera. There was no medical crisis because the outbreak wasn't real, but a consequence of a poorly designed IT system, that did not allow doctors to leave any windows blank and the first diagnosis code on the drop-down menu was cholera. 

AI is already used for decision support systems. Decision support, not decision making.

AI will by no means replace doctors, at least not soon, because an essential part of the healing process is the human touch, empathy, and kindness. And AI can't offer that. 

Doctors hope that AI will help them diagnose patients better and faster and bring back time to talk to patients. Because of the workforce shortages, it is possible that technology would be used to put more pressure on doctors and their productivity. On the other hand, given that healthcare is transforming towards consumerism, technology might be used for better patient experience, not worsening of the doctor-patient relationship. 

The second reason it is worth believing in the helpfulness of AI is the fact that the needs for healthcare are increasing, but the numbers of doctors do not follow. 

 In most countries, doctors complain about workforce shortages and burnout. 

Healthcare and medicine are in dire need of technological help. Medical conditions are getting incredibly complex, with the same symptoms present in very different conditions. A repetitive headache can be just a headache, a migraine, meningitis, a stroke or brain tumor.

Digitization is creating new types of biomarkers, which supported by AI analysis, bring surprising discoveries. Facebook created algorithms to detect depression in users and contact their close contacts to address them. Researchers are experimenting with artificial intelligence (AI) software that is increasingly able to tell whether you have Parkinson's disease, schizophrenia, depression, or other types of mental disorders, from merely watching the way you type.

Human beings have an inner need not to be alone. There is a reason solitary confinement is among the harshest punishments. We are social creatures in need of company and diseases can take that away from us. 

When reading about how digital health and AI are improving disease management, waiting times in decision making healthcare, we don't only read about cost savings.

These novelties show how patients are becoming more and more equal to healthy people and how diseases are affecting the quality of lives less and less due to 

• less time spent in the healthcare systems, 

• faster diagnosis, 

• faster treatment and recovery.
  

Of course, this is not going to happen tomorrow, but when has any progress ever happened fast, especially in healthcare? Yes, AI applications are still in the early stages of this, algorithms and studies currently based on retrospective studies. But the trend is what it's crucial - the hype is annoying, but it attracts talent. And more people means more knowledge and faster advancements. In the end, technology is just technology. It's up to us how we're going to use it.