Big Data has changed the world of medicine and healthcare. This innovation has provided incentives to improve the quality of care and to reduce costs.
Visualize & Analyze It
By Igor Yeryomin on bl.ocks.org
In addition, it helps to reduce the so-called effect of information overload, where clinicians, medical administrators, researchers, and even patients are faced with huge amounts of different and sometimes contradictory information.
Our ambition is to understand how technology in the health industry can aid in the visualization and analysis of medical data. There are various challenges which we will address in our goal to ensure and empower healthcare professionals.
Visual, Not Casual
Remember when all drawings, even if they were unrelated to data, were called infographics? Today we all know the difference — figures on a picture and infographics are two separate categories.
The same with visualization, especially with medical ones. There are different types of well-designed postings, MRI pictures, time-lapse videos with graphs, and even some apps that are related to visualization. But to be called medically visualized they miss two main things: analytical and prognostication components.
These two components are made by tech — AI, ML, Predictive Algorithms, Data Mining, Data Visualization, etc.
So, what does medical data visualization & analytics mean? In Vareger we explain it as a set of tools that transforms data into visual assets helping to study and analyze data correlations in the healthcare industry.
In other words, this is analytics, prediction, and visualization — three in one. This is about how you collect huge amounts of data, combine it in sets, analyze these sets, and build prediction models and scenarios. This toolset helps to study and to analyze data correlations allowing for matching data from different datasets that have nothing in common at first sight.
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VISUALYTICS PROJECT?
read more about our Visual & Analytics Components Solution here
Prepare, scale, repeat
There are numerous challenges here. And almost in each problem stated by the professionals, we see one common thing: such systems are too complicated for the medics. It may take years to learn how to analyze the medical data in the right way. Uncertainty of data and incomplete entries are the effects of this complexity.
The second problem is the lack of time. Healthcare professionals are overloaded with daily tasks. They need to get short previews of the collected and analyzed data.
Data structuring is another challenge. The data shared among the colleagues need to be presented in a simple way. That allows healthcare professionals to switch from individual decision-making to teamwork. For sure, the system needs to be user-friendly, i.e. — designed in a way that excludes even a minimal chance for mistakes.
The scope of the problems and challenges in this area is huge, so we rather focus on three main problems healthtech can address already (and you can find a successful example of how we made it here).
Reminds AI? It's not. Those are ganglion cells expressing fluorescent proteins in a mouse retina, magnified 40x. By Dr Keunyoung Kim on The Guardian
Thorough data preparation is a must. Data preparation helps to cope with missing values, duplicated records, incorrect data entry, and patient name entity resolution as well as proper data-timestamps. But, why is it important for healthcare professionals?Apart from usability and visibility, the healthcare professional can clearly understand large data.
They can predict patterns and ensure optimal methods of success while reducing waiting time. Visual strategies can highlight flow patterns and ensure patients are receiving the right amount of medication. The visualizations & analytics system can help with this and ensure that the outcome of visualization is accurate and represents the situation adequately.
"When it comes to preparing data I would say "take your time". It's vital to do everything right, especially when you deal with a massive array of unstructured data. But you'll be rewarded in the end. As it will help to reduce the time for research, diagnostics, or manual data processing", says Vareger's CEO Oleg Pun.
Scaling visualization — a technique that helps to filter and dynamically form the aggregated values — is already available due to technology. It also helps millions of healthcare professionals to compare data from billions of records in a twinkle of an eye and to build trends and prognosis for different groups of patients.
Flexible updating, that means independent processes initiated by the visual and analytics system is right at the moment when new data is to be added to research. These processes depend only on technology and need no human interference. In other words, the system by itself monitors changes like new information added, structures this data, and adds it to all possible outputs. That helps healthcare professionals to make in-depth retrospective analysis without fear of new information being lost in previously collected data sets.
HealthTech can fix problems associated with a lack of compiled and unorganized data while helping to create better systems and understand the analytics of patients. It’s more important than ever to take action quickly while still being informed. With an abundance of information, it is important to have a clear understanding, and with stressful lives and an influx of data, visual analytics helps put data where it needs to be.
Want to discuss your
VISUALYTICS PROJECT?
read more about our Visual & Analytics Components Solution here