Key Takeaways
- Healthcare provider can make use of data visualization to assess past and present medical history, to improve patient care and outcome.
- Data visualization in healthcare helps to prevent medical errors and frauds, and if they are undetected it can lead to fatalities, transaction frauds, and incorrect treatment.
- Data visualization tools include widgets, interactive dashboards, motion graphics, infographics, and interactive apps.
A study states that 50 percent of the brain is active in visual processing. Hence, data visualization in healthcare plays a key role in determining medical conditions of patients. It also helps to improve treatment plans and detect errors if any.
Data visualization is a collection of information that is represented graphically. Elements such as charts, bar graphs, maps, infographics, and much more are used for data visualization. These elements helps to understand trends and patterns.
Healthcare data visualization is the graphical representation of the medical data obtained from various sources such as EHR/EMR, wearables, biometrics, patient portals, e-prescription software, and so on.
This data is analyzed by healthcare providers to gain in-depth insights on patients’ health and well-being, based on which they can predict future course of treatment and diagnosis.
How Data Visualization is Transforming the Healthcare Sector?
1. Improved Patient Care
Data visualization in healthcare provides better insights on patients’ medical condition. By studying this data, healthcare providers determine steps to be taken to improve patient care and outcome.
If a patient is suffering from hypertension, then a healthcare provider can make use of data visualization to assess past and present medical history. Thus, determine the reasons for hypertension, future possibilities, and how well can it be treated.
Charts and graphical representations of healthcare data eliminates the need to manually sketch them out and understand medical conditions. Further, data visualization prevents practitioners from missing out on vital information during diagnosis. Moreover, visualization offers real-time data insights, which are useful during emergency cases or drug intolerance conditions.
2. Medical Error and Fraud Recognition
According to the study published in the Journal of the American Medical Association, one-fifth of the patients who have access to ambulatory noted of finding a mistake and out of those, 40 percent reported the mistake to be serious. Medical errors results in deaths, hospitalization, and wrong treatment. Hence, it’s necessary to keep medical errors in check and to identify those errors to prevent any mishaps.
Data visualization in healthcare is a plausible solution to detect errors and avoid them. A complete picture of patients’ health data helps to identify mismatched readings and information that seems to be out of place. It also points out to incomplete information, so providers can gather data for accurate treatment and medication.
Furthermore, in the healthcare sector, frauds and data breaches can occur. Hence, to prevent this data visualization is integrated with AI and ML technologies for fraud detection and prevention. Machine learning analyzes and processes data to extract patterns in no time. AI in healthcare is created to detect fraudulent transactions. These algorithms recognize hidden patterns and predict responses.
3. Medical Data Representation
Pictures or any form of visual representations are captured by the human eyes instantly, hence data visualization is an effective technique to grasp vast medical data instantly. Through graphical representations, data visualization offers to create effortless and interactive dashboards for analysis.
Medical data is represented using charts and graphs to understand written reports. Visual representation can be shown to patients and educate them about their medical conditions. Patients are able to grasp their health conditions better through visual data.
Furthermore, data visualization in healthcare helps to find correlation between varied test results, treatment, and medication. This in turn helps to make informed decisions about care and wellness.
4. Pattern and Trends Recognition
Making sense of values and comparing them in a common practice adopted in data visualization technique. Healthcare providers and clinicians can identify disease patterns of a region or a state, based on which they can predict future health of a population. Hence, maintaining population health of a region.
Bar charts are useful for recognizing upcoming trends in medical field, also to spot which type of diseases are rising significantly (or decreased). Providers can add charts of different hospitals or regions to compare health statuses of population.
Trend and pattern recognition can be automated with the help of machine learning tools. ML algorithms can easily give inputs on patient issues, medications, treatment, and diagnosis at real-time.
5. Predictive Analytics
According to a study from the Duke University, predictive modelling can capture around 5,000 patient no-show data with accuracy, to forecast patient patterns. Healthcare providers can use this data to send reminders to patients frequently to lower the risk of no-shows.
Data visualization helps to understand patterns and to determine which patients don’t show-up. Thus, making it easy to send reminders. Predictive analysis has the potential to manage chronic diseases and guide providers to produce therapies for better outcomes.
Additionally, with data visualization, hospitals and clinics can identify patients who are likely to be readmitted. Prior estimates of readmission allows providers to design strategies such as remote care to prevent unnecessary readmissions.
Graphs and Charts Used in Healthcare Data Visualization
1. Widgets, Apps, and Websites
Interactive widgets, apps, and websites are useful when healthcare providers need specific or limited information. It’s easy to build a fast, neat, and focused website, app or widget with minimum settings.
Interactivity improves patient engagement and enhances experience. It automates tasks and displays dynamic data without the need to manually input information. Providers can get latest updates, which helps in better decision making. These can be customized as per preferences and requirements of providers.
2. Interactive Dashboard
Interactive dashboards digs deeper in healthcare data and filter it in several ways. It creates clear figures, which allows providers to make data-driven decisions. Simple headlines on dashboard helps users to understand what the data includes.
Also, dashboards can be shared with patients, and multiple healthcare providers, so they can access the data during emergencies. This data is made HIPAA compliant as it contains vital ePHI and failure to do so can lead to adverse effects.
3. Infographics and Motion Graphics
Infographics and motion graphics are powerful tools that work best with a large audience. Providers can easily represent medical information with the help of infographics, so people can understand it better.
Animated videos are easy to understand and have the potential to catch the attention of patients quickly. Moreover, infographics can be best used to educate the public on healthcare and wellness.
To know more about data visualization in healthcare or to get custom healthcare software developed for your organization, get in touch with Arkenea. With over 10 years of experience in the healthcare software development sector, our team of experts is trained to offer cutting-edge healthcare software for your organization.