AI for acute care
AI for acute care. IT solutions to save life
One of the most interesting events we recently participated in online was the HIMSS. Everyone who works in the healthtech field knows that it's one of the top "must participate" events in the industry.

It's always great to meet new people, even though conservative networking in a lounge with coffee has been always better. But that's the way it is now, and we look forward to seeing the trends in healthcare digitalization; one of the most interesting is acute care – an area where we are developing our startup called "Brainor". We are currently in stealth mode and the pilot will be revealed in Q1 2021.

Recently, Philips, one of the leading contributors of healthcare applications in Europe and overseas, published a whitepaper fully dedicated to the digitalization of acute care. And here are some of the trends which we believe are going to shape the landscape in this field.

The first one is moving from local to global information systems. It sounds like just another globalization trend; however, we see it from the different angle. If we dwell for a moment on the matter of practicality, the major outcome is seamless integration within any healthtech ecosystem. It doesn't matter how good your stand-alone application is, if you can't integrate it into an existing IT infrastructure, you will not succeed. Because there is only one core thing that matters above all others and that is time. Time, which passes while different systems exchange vital information about the patient. Time, which is crucially important for doctors, when someone's life hinge on minutes. And here we see that a lot of startups in this sphere don't really understand the importance of integration, nor always estimate the development costs, thus reducing profitability and creating sales boundaries.

The second one is estimation of outcomes and possible improvement through better data utilization. Over 80% of medical data remains unstructured and hence totally useless. In acute care it becomes even more critical – you have no time to analyze a massive flow of information. It's about time… Again. We believe in big data development services becoming a vital part for healthcare providers. Be it in-house or outsourced vendors, but soon ETL will become a standard component of any medical information system, if we want to utilize all possible benefits of knowledge and improve patient outcomes.

The third one is research based on data and matching different types of data in order to create a real patient-centric approach. For example, acute care in stroke treatment requires assessment of many different clinical points and adverse events to arrive at the best possible patient outcome. Furthermore, this data is required to choose the optimal rehabilitation plan and, most importantly, balanced out-patient care. To keep the process smooth, we need to have a patient-centric platform which stores structured data about each patient available for different types of multi-disciplinary care.

We believe that an integrated approach will help with utilizing available data in the most efficient way and shape the landscape of the healthcare ecosystem, creating smooth information flows between different levels of care. Another important aspect of building the ecosystem is better training of doctors, which means fewer errors, better outcomes and lower costs.

This point is also proved in the Philips report, which states that 75% of physicians believe digitalization of patient data could help them to improve quality of care.

Stay tuned, we are preparing interesting material about using AI for stroke diagnostics in the acute phase.

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