New technologies are at the service of improving people’s quality of life. This premise has never been more applicable than in the healthcare sector. This industry has accelerated its journey with the help of artificial intelligence (AI). According to market reports specialist, Statista, it was forecast that the global healthcare AI market would be worth almost 188 billion U.S. dollars by 2030, increasing at a compound annual growth rate of 37 percent from 2022.

The AI healthcare applications are almost infinite. This technology makes it possible to automate tedious and repetitive tasks (such as uploading documents and checking authorizations) intelligently, thus freeing up staff time that can be dedicated to providing better care. They are also useful for improving diagnosis accuracy, anticipating scenarios, or obtaining relevant data from patients or their health charts while minimizing search times, errors, and costs.

AI solutions must be fed with very large amounts of data to succeed. In this regard, the healthcare segment in the United States has a key ally: the EHR (electronic health record), regulated in that country, requires that all elements linked to a patient’s medical history (from medical visits to imaging studies, from recommended treatments to medicines purchased in pharmacies) be kept in a digital format.

From personalization to self-care

This means an enormous source of data that can be used for discovery tasks, pattern detection, complex findings, or the use of analytics and big data solutions to achieve unprecedented improvements in the healthcare system. We can count on highly personalized and highly accurate treatments – with better outcomes – or, even better, preventive medicine models, anticipating scenarios, encouraging self-care, and thus reducing the strain on a system that is always short of resources.

In its simplest format, the AI-supported EHR provides the physician with high-value-added diagnostic information based on a combination of listed symptoms, medical imaging analysis, laboratory test results, and generic data on different types of diseases, for example. It also makes it possible to prescribe the right medicine, considering any possible side effects based on the patient’s total characteristics or other medications he or she might be taking.

A challenge for the system

This is only the beginning. Access to clinical data by the different stakeholders in the healthcare system (physicians, laboratories, hospitals, pharmacies, private healthcare centers, and patients themselves) opens up many opportunities. It allows for the development of patient-centered strategies and care at unprecedented levels. It provides the health authorities with tools to make informed decisions on population health.

The path, although essential, is not a simple one. Some obstacles remain, starting with a technological issue that Making Sense is helping to resolve: standardization so that different providers can share and collaborate on EHR data consistently and securely. There are also cultural barriers, such as the intensive use of the fax machine in the North American healthcare industry to send documents -an issue we dealt with in a previous article, and regulatory challenges linked to data confidentiality around such a sensitive field as people’s health.

Still, a market analysis conducted by GlobalData characterized AI-assisted EHR as one of the most accelerated AI adoption cases in the medical devices industry, interactive surgery systems, 3D dental or blood vessel scanning, MRI image smoothing, or radiation dose optimizers, among many others. In this study, three other AI-driven medical innovations would have already reached a higher level of maturity: 3D endoscopies, computer-assisted surgeries, and athletic motion analysis.

The healthcare system and artificial intelligence: a partnership that will end up being redundant since it will produce more health and intelligence.