The fact that data and data visualization are everywhere in today's world, makes me wonder how data visualization impacts medical applications and what's their role within patients' diagnoses? Undoubtedly, patients trust their wellness on healthcare professionals' criteria and decisions but what do doctors, nurses, practitioners, and other healthcare professionals base their judgment and decisions on?
The experience factor indeed drives medical decisions but when talking about complex medical diagnoses, healthcare professionals need to base their decisions and judgments on accurate information coming from different sources such as laboratory analyses made by experts (e.g., medical technologists) who are constantly involved in working with medical observations, samples, data, test results, researches, etc.
For professionals working in the health sector and treating hundreds of patients a year, it is key to trust reliable and accurate data, but how does data visualization impact the medical sector?
Table of Contents
- Why is Data Visualization Important in MedTech and Healthcare?
- What is Medical Data Visualization?
- Data Analytics & Data Visualization Applications in Healthcare
- Charts & Graphs Used in Healthcare Visualization
- 5 Companies Innovating in Healthcare & Medical Visualization
- Why Does Performance Matter in MedTech & Healthcare Data Visualization Applications?
Why is Data Visualization Important in MedTech and Healthcare?
We've all seen at least one popular TV show or movie that showcases an example of a medical application that monitors a patient's e.g., heart rate, that looks like this:
So, even for non-medical readers, it becomes more intuitive to get the idea of a heartbeat visualization. But what would happen if you'd have to visualize the (sample) dataset instead? Let's take a look at a sample dataset of a heart rate contained in a spreadsheet:
The image above is a sample dataset containing hundreds of data points that at the bare eye, is tedious to understand even for medical professionals. In that case, how is data visualization used in healthcare? Data visualization helps in the process of transforming and visually displaying medical data points that simplify and synthesize the analysis of complex and large datasets into visualizations that are easier to process, visualize, and understand.
With that being said, data visualization and healthcare imaging offer another way how to understand data even for non-technical readers. Nowadays, medical applications that help users to track basic medical information are more common and can be found on people's smartphones and smartwatches.
So, it wouldn't be useful for users to visualize spreadsheets on their smart devices but rather translate complex data into simpler visualizations. After this concept, it is easier to understand why medical visualization plays a key role in the medical sector.
According to Statista, the amount of healthcare data generated in 2013 was 153 exabytes (where 1 exabyte equivalents to 1 billion gigabytes) and by the end of 2020, it had already increased to the colossal amount of 2,314 exabytes.
With the upward trend of the development of more medical monitoring applications for organizations and individuals, the amount of data that will need to be visualized, analyzed, and explored will indeed continue to grow rapidly in the upcoming years.
The continuous growth of medical data is a key driver for health organizations that are trying to provide a better and more personal patient-centric health service. As a consequence of this, data analytics, big data, and data visualization are becoming important subjects in healthcare that are helping to prevent and predict diseases.
The analysis of data represents a tremendous opportunity for health specialists to make data-driven decisions based on historical information that is later presented in state-of-the-art applications featuring the most advanced data visualization technology.
Preventive & Predictive Medical Visualization
While the future cannot be predicted, certain branches of data analytics in medical technology are present in the healthcare sector in order to convey different analyses that help professionals to work with past and future diagnoses. That is the case of descriptive analytics that takes a look into the performance of historical data and its behavior and relevance in the matter, e.g, in diagnoses.
The diagnostic analysis aims to understand why certain diseases occur and to explain their root causes whereas predictive analysis aims to forecast and anticipate future diagnoses and diseases which, therefore, acts as a method of prevention. Finally, the prescriptive analysis aims to test multiple scenarios to anticipate the outcomes before a final decision is made by a health professional.
The importance of data-related subjects such as data visualization is not only for health monitoring but also helps medical professionals to step ahead into possible future diseases and explain the triggers of past illnesses and harmful conditions.
Here's an example of a 3D volume rendering visualization of a skull that involves thousands of data points and is commonly used for studies in anatomy, traumatology, implants design, craniofacial reconstruction, or surgery analysis and planning, among other applications.
What is Medical Data Visualization?
As earlier mentioned, the volumes of data are steadily increasing in the healthcare sector and more medical professionals continue to experience difficulties when trying to make sense of patients' health information.
Within the different areas of data, data visualization specializes in transforming complex healthcare data and analyses into visual formats that help medical decision-making professionals to formulate diagnoses and treatments for patients in order to deliver effective medical care.
High-quality visualizations have been determined to be key in improving how health professionals perform decision-making processes and identify patients' health trends to understand future conditions (predictive analysis) and diseases.
Technically, medical data visualization refers to increasing the efficiency and accuracy when reviewing and observing data for instance when visualizing organs, bone elements, or diseases processes. So, the process of medical or advanced data visualization helps to merge information from multiple sources that would otherwise stand alone and could not be related.
An excellent example of this was made by researchers Jonathan Wanderer, Jesse Ehrenfeld, and Soojin Park who stated:
"A visualization made for evaluating a kidney injury could merge multiple data from sources such as urine, urine electrolytes, serum creatinine, and blood pressure allowing doctors to quickly review and predict a change in the normal functions of the kidney."
Such visualization can be later used to understand and explore the disease, discuss the condition with other medical experts, and present the diagnoses to the patient's family.
Data Analytics & Data Visualization Applications in Healthcare
Almost all the areas of healthcare and medicine can apply data analytics including data visualization. Today, modern medicine continuously uses data to provide a patient-centered approach and a more customized healthcare service. Moreover, data visualization in health IT is driving professionals to better decision-making processes.
Several areas of medicine have been improved and benefited from 3D models, e.g., x-rays, MRIs, or 3D volume renderings. High-performance visualizations are used within, if not all, the most demanding applications in healthcare, for instance, telesurgery, monitoring, surgical planning, or genomic analyses.
In molecular analysis, Omics data refers to data sources from molecular fields where data is used with the aiming of understanding how diseases develop and how to improve the diagnoses of medical treatments.
Common visualizations used in this field are so-called N-body simulations that simulate the behavior of particles within environments, e.g., the human body system.
Genomics refers to the study of genes and their functionalities which is key for researchers and medical experts when studying the prevention and cure of certain diseases. Visualizing data is key for observing and analyzing the correlation and trends that exist within large data sets that would otherwise be more complicated to analyze.
Medical Device Development
Data visualizations are commonly and widely adopted in medical devices for, e.g., cardiac rhythm monitoring, cardiovascular devices, diabetes monitoring, and prevention, etc.
Charts & Graphs Used in Healthcare Visualization
Charts and graphs plot the data with respect to different axes creating specific forms or visualizations. As mentioned before, the amount of healthcare data is enormous and continuously growing thus demanding visualizations to be able to render a great number of data points at high-performance characteristics.
The requirements of the visualizations will be driven by the clinical needs but some of the characteristics of the highest performing visualizations would include:
- Rendering performance. Not all libraries are meant to handle advanced medical and healthcare data sources. Open-source libraries experience this problem as they are limited in resources and performance. Commercial libraries are there to solve those issues and can render billions of data points in real-time without performance issues.
- Resources optimization. Is the healthcare sector prepared to visualize all its data? Certainly, it is preparing for and GPU-accelerated libraries are using the PCs' power to deliver higher-quality visualizations at faster rendering and response times.
Here are 3 examples of advanced visualizations that can be later integrated into medical applications:
1. Medical Dashboard
- Electrocardiogram (ECG/EKG)
- Non-invasive blood pressure measurement (NIBP)
- Blood flow volume (BFV)
- Blood oxygen saturation (Sp02)
2. 3D Volume Rendering of a Skeleton
This is a .NET medical visualization which samples a WPF 3D volume rendering of a human skeleton.
5 Companies Innovating in Healthcare & Medical Visualization
Medtronic is a world-leading diagnostic and health care company with products and services around the world. With operations in 150 countries, Medtronic products treat 70 health conditions and include cardiac devices, cranial and spine robotics, insulin pumps, surgical tools, patient monitoring systems, and more.
Within Medtronic's vast variety of healthcare solutions, they have developed the CardioInsight Workstation that is a dedicated workstation for ECG signals monitoring capable of rendering 3D cardiac maps.
The workstation works together with their product CardioInsight Mapping Vest which transmits the data to the CardioInsight Workstation and translates it into real-time high-performance data visualizations using LightningChart data visualization library.
Here's a practical case of the CardioInsight Workstation together with the CardioInsight Vest being used to analyze and treat a patient's arrhythmia. The case took place in one of the Northwell Health network hospitals.
2. MGC Diagnostics
Headquartered in Minnesota, US, MCG Diagnostics was founded in 1977 and today is one of the world leaders in the development of cardiorespiratory health solutions. They have a great scope of devices for the healthcare sector including devices for detection, classification, and management of cardiorespiratory diseases.
MCG Diagnostics is implementing high-performance data visualization solutions and features LightningChart data visualization charts and graphs in their Ultima™ CardiO2® gas exchange analysis system. This novelty device is an easy-to-use metabolic stress testing system with high-performance features including oxygen and carbon dioxide sensors to collect data from patients breathing, continuous data processing and analysis, and data visualization in real-time.
Biosense Webster specializes in the development of world-class medical devices for 3D navigation. They are innovators in the field of electrophysiology and have developed their novel CARTO™ 3D mapping technology used for signal monitoring and diagnoses that are improving the lives of patients with cardiac arrhythmias condition.
Biosense Webster relies on implementing powerful data visualization libraries capable to process signal data in real-time that helps healthcare experts to analyze a patient's conditions and provide a better diagnosis. Some of the visualizations used in the CARTO™ 3D mapping implement LightningChart .NET 3D volumetric rendering.
Here's a detailed demonstration of a real-time ablation medical procedure made with the Carto system where abnormal tissues are removed.
4. Digicare Biomedical Technology
Is a family-owned and innovative company that provides devices solutions for medical monitoring and measurement. Digicare Biomedical Technology has implemented LightningChart Data Visualization Solutions in their novel telemetry monitoring system CentralVue CV10 that features different line series and XY charts that support millions of data points processing in real-time.
The CentralVue CV10 is a medical multi-channel monitoring system that supports up to 32 different monitors with features including patient management and remote controlling.
5. Cerebra Sleep Scoring
As world-class innovators in the field of sleep research, Cerebra has studied, researched, and developed different solutions to improve the way how patients develop a better quality of life by enhancing their sleeping conditions.
Their Cerebra Sleep System directly analyzes the Electroencephalogram signal to observe the brain activity of patients and develop effective diagnoses that can improve the physical, mental, and emotional health of patients.
Within their system, Cerebra implements LightningChart XY and line series data visualizations for different monitoring of patients' sleeping signals coming from brain activity.
Why Does Performance Matter in MedTech and Healthcare Data Visualization Applications?
When vendors in the MedTech and healthcare industry are evaluating charting products for processing their data, analysis, and visualizations, their top priority is high-performing charting components or data visualization solutions.
In the medicine field, data visualization is part of a bigger process where data needs to be processed at top performance with high accuracy avoiding downgrading techniques like downsampling.
End-users are health professionals who are experts in analyzing the information and translating it to their patients. Health professionals need to rely on fast and accurate tools provided by the best-performing medical devices that feature high-performance components.
The importance of high-performance in MedTech and Healthcare fits within the ability to transform millions and even billions of data points into high-performing visualizations that support the healthcare experts' decision-making processes.
High-performance data visualization is therefore crucial for MedTech applications to present data either on desktop, web, or mobile devices. Charts, graphs, and dashboards need to be able to handle millions of data points in real-time, to enable doctors and research professionals to have complete visibility and control over their instruments and MedTech applications to provide better healthcare services.
LightningChart® Data Visualization Components for MedTech & Healthcare Application Development
Some of LightningChart's key points that support high-performance and large datasets visualization are:
- MedTech cross-platform application compatibility. LightningChart data visualization library supports app development for desktop, mobile, and web applications.
- Line series are commonly used in MedTech applications. LightningChart line series support visualizing up to 500 million data points.
- Guarantees the best performance for MedTech apps. Integrating LightningChart library to your MedTech application guarantees only the fastest response times, best hardware acceleration, and GPU-accelerated visualizations. E.g., LightningChart line charts are up to 516,600 times more efficient when rendering healthcare data.
When it comes to visualizing healthcare data, LightningChart charting components support the world's fastest and largest rendering technologies that leverage the way how healthcare experts and end-users visualize and understand the data allowing more accurate diagnoses and decision-making processes.