The Data Driven Approach in Current Medicine

Out of nowhere began the cough and a severe sore throat. A few minutes later, the first hint of elevated temperature. This was enough to activate her smartwatch and send an alert to the hospital. Minutes later the paramedics arrived for him and they already had the vital signs data: blood pressure, heart rate, blood type, oxygen saturation and as a bonus the availability of beds in hospitals within 5 kilometres.



What joy it would be to be able to say that the previous assumption is a real case but until now it is still part fiction but we are not very far from achieving it.

Today more than ever, data is generating insights to improve and modernize the world of medicine. In fact, the data-driven or data-based approach is driving innovations in the health industry such as robotics, remote diagnosis or, as is now clear, combating a pandemic with real-time access to global information that allows make decisions on time.

A very clear example of the application of the data driven approach is Miami Children’s Hospital. It has isolated booths that measure temperature, vital signs and even X-rays, so that doctors have the option of offering a remote consultation linked to a playful activity, explaining to small simple games what their treatment and/or convalescence will consist of in Hospital.

Other companies such as Siemens have already put into practice the term ” smartbeds ” that have intelligent monitoring, being able to identify when the patient sleeps, gets up, stays in bed or is unoccupied. They also have an automatic adjustment to level the type of support that the patient needs, pressure or posture, without the need to call the nurse every 5 seconds.

Automating care with Machine Learning with a data driven approach

Companies and patients have realized the importance of having adequate repositories of medical information and their respective interrelation in a digital ecosystem. According to IDC forecasts, by 2025 there will be 41.6 billion devices connected to the Internet of Things (IoT) that will generate 79.4 Zettabytes of data. The key question at this time is how can we manage that information? The answer to this is that only through the use of Machine learning and Blockchain can efficient management and security in the handling of this data be guaranteed.

Let’s think of a bot as an example of Machine Learning. These “bots” feed on the information provided by the user and can provide “basic” guidance derived from the information that is shared. For example, instead of using a “screen” to detect SARS-Cov2, an app could be used that diagnoses the patient’s condition and, depending on the severity, calls an ambulance or shows the closest hospitals, clearly recording the data. for statistical and monitoring information.

Another example is a smartwatch that records information on a specific condition and the bot based on this extracted data will give certain notifications that allow interaction. It can be anything from reminding the user to take medication or scheduling medical appointments. Any of this information would be stored in the cloud and its subsequent analysis is optimized with a reduction in the process of admission to hospitals or search of files.

Blockchain application in the medical world

Blockchain is literally defined as a chain of blocks and is usually associated with cryptocurrency issues, when this is just one of its applications. The crux of this topic is that each block must store a specific number of valid records; information inherent to that block and especially a link that communicates it with the previous block and the next block. It is a kind of unique ID or signature for each block.

These chains are already being exploited by medical specialists and we have brilliant examples of this. Few know but FLETA in South Korea developed such a robust blockchain platform that it was key in controlling the first hint of the outbreak during this pandemic. With unique data management intertwined to determine cases, infections by contact and geographical area, it helped the government take measures to monitor and assist those infected by the virus in a timely manner. The best thing about this platform is that its data is decentralized and freely accessible to researchers, doctors, public bodies or anyone who needs to use it.

Mexico did the same with a platform called “Prescrypto” that allows connections to be used to create medical files, patient history, prepare medical prescriptions and, in particular, remotely control the evolution of the patient from anywhere.

Currently we think that temperature, headache and throat are clear signs of the beginning of an ugly disease, leading us to search incessantly for an efficient remedy. Applying Data Driven to this same case, the message is unquestionable: you will be preventing BEFORE that disease worsens. Why? Because we will know in advance what has to be changed so that it does not happen and if it happens, we will have all the information in a matter of seconds to assign a bed, make diagnoses, generate personalized treatments and improve survival rates.

Currently the medical world and the sea of ​​data that it generates every day, lack analysis and its adequate repository. The priority of technology companies, authorities and private entities should be to give order and structure to the information that we have available and then link it to wearables and have a complete picture. Let’s not make the mistake of viewing this need as a long-term project, this should be seen as an immediate action capable of being carried out as quickly as possible since the pandemic has shown us how unprepared we are.

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