A key focus of Medaffcon is its work with real world evidence (RWE). This information, such as medical reports, is obtained from everyday health practices. The data gathered needs to be converted into a structured format so that it can be processed by computer systems. The question is how to evaluate this text electronically. Which data is important? Which key terms should text mining tools search for? Do they need to recognise laboratory values or data about weight, height, and lifestyle?
In one of the current projects, biostatistician Iiro Toppila is trying to determine how to improve the systems used by patients who monitor their own health, for example, by measuring their temperature, blood sugar or blood pressure. In the future, these systems are expected to be smart enough to detect a patient’s risk of complications when certain measured values change. This type of artificial intelligence is trained using the data from biobanks, clinics and, the Finnish central registry.
Maija Wolf, Head of Development, explains that this method of analysis can also be used to help identify people with rare diseases whose symptoms may change or indicate other illnesses. By analysing large volumes of data, key symptoms can be detected, arguing the case for a specific diagnosis. Maija Wolf believes data-driven decisions are one of the most important healthcare instruments of the future. “We need this type of resource to ensure that we can provide more effective and sustainable healthcare that is tailored to the needs of the individual.” This is how Medaffcon intends to continue helping customers in the future.