We live at a time when the medical profession is more tested than ever. It is working hard to save lives, and effective medical assessment is an essential part of it. Digital technology is vital for making medical work easier, and a major digital innovation on the rise in diagnostics is predictive medical assessment.
Predictive medical assessment is the type of diagnostic assessment that we are developing here at MESI Ltd. It will be based on the diagnostic measurements obtained through our MESI mTABLET system. In a few years’ time, we aim to create a big enough diagnostic data pool to be able to compare the diagnostic measurements of a certain patient not only to the measurements from his or her own history, but also (in line with all applicable data protection legislation) to anonymised diagnostic measurement results of other patients.
By means of tools like AI, our aim is to be able to make predictions on the future development of various conditions. In this way, we wish to offer another helpful resource to the medical professional that could not only help save precious time, but also more lives with timely intervention.
In this blog, you will learn:
- What is predictive medical assessment?
- Why predictive medical assessment?
- What does predictive medical assessment consist of?
- How will predictive medical assessment help the medical professional?
- How could predictive medical assessment change the perspective of the patient?
What is predictive medical assessment?
Medical science has a fantastic history of progress. Today, doctors can not only find what kind of condition a patient has (i.e. what happened), but also why. This is an important advantage of the diagnostic medical age. The advent of digitalization and artificial intelligence, however, has opened another important chapter in medicine – that of predictive analytics.
In predictive medical assessment, every diagnostic measurement is stored into a digital system where it can be easily accessed and compared with other measurements. (In this, of course, full data protection must be provided in accordance with the legislation.) With enough data, all the patient’s diagnostic results can become part of a bigger picture. Ultimately, we aim to predict the development of certain medical problems and/or discover them very early on.
Why predictive medical assessment?
AI and machine learning are already used in a number of medical fields. Although their use is at an early stage, it is something that it is worth exploring.
Challenges like COVID-19 revealed the problems of the diagnostic medical age: diagnostic medical assessment is made with different, fully separate instruments that provide a single measurement result which is not stored in a patient record. The same process is usually repeated at separate doctor visits, at separate specialists, in separate formats, and at separate locations.
For all these reasons, it takes time to put the diagnostic picture together, and many conditions can remain undiagnosed, some of them fatal. Digitalisation of the healthcare system, including diagnostics, is an answer to many of these problems. And effective comprehensive digital solutions are already there.
An example is the MESI mTABLET, which provides all necessary diagnostic measurement at one place, enables automatic result storing in the patient history, allows immediate consultation and provides decision making support with smart applications.
And finally, the big amount of data collected in the measurement records will ultimately enable that last feature – machine learning and therefore artificial intelligent algorithms to provide predictive medical assessment. In this way, the MESI mTABLET could also become a platform for predictive medical assessment and offer one more useful tool to its users.
What does predictive medical assessment consist of?
Predictive medical assessment will combine two types of analysis. On the one hand, it will consider the diachronic factor – the individual diagnostic history of each patient. On the other hand, it will be able to learn from synchronic conclusions made by comparing anonymised data, for example, from patients of the same age, of the same sex and with the same conditions.
We aim to be able to anticipate certain outcomes on this basis. This will help detect various conditions in early stages, predict future results based on patient history and recommend actions to assist medical professionals.
How will predictive medical assessment help the medical professional?
What does every patient want from a doctor? Actually, it is always the same thing. An answer what their current problem is and a prediction of what could happen to them in the future. This is a challenging demand – as if doctor had a magic crystal ball.
In reality, giving that answer is not easy and takes time. It is based on scientific fact established through diagnostic tests, a medical examination, and in consultation with specialists. At MESI, we offer a solution with which the answer for the patient can come faster. That magic crystal ball, or at least a very helpful acceleration, is the MESI mTABLET.
With the MESI mTaBLET, medical assessments are faster and more efficient, and can constantly be advanced with additional modules and apps. The MESI mTABLET is becoming smarter and smarter every day with more data created and every new software release, which will ultimately lead to a platform for predictive medical assessment.
How could predictive medical assessment change the perspective of the patient?
The MESI mTABLET is a system of modular solutions that make traditionally specialised diagnostic procedures like ABI, TBI and ECG part of the GP routine. In this way, we can already help set early diagnoses and monitor the patient in a comprehensive way. By means of AI, we will also be able to help make predictions for further treatment of the patient.
On the basis of such comprehensive information, the patients, too, can be a lot more aware that their past, current and future choices always count. They will be able to see very precisely how their health has started deteriorating after years of that stressful job, or improved since they stopped smoking or took up exercise. Hopefully, this will also transform how they view the role of the medical professional. Not just as someone who is there to solve their current problem, but as a person who helps monitor and impact their health and well-being long-term.
The predictive medical age is emerging as we speak. And we must not miss the opportunities it offers. Through the trends and patterns discovered with AI in medicine, we can improve treatment and care, and save more lives.