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Healthcare data visualization: benefits, examples, and tools
The healthcare industry is awash in data. From patient records and clinical trials to operational metrics and public health trends, the sheer volume of information can be overwhelming. Data visualization helps make complex medical data easily digestible with visual formats like charts, graphs, and interactive dashboards. This allows healthcare professionals to quickly obtain the required insights, make decisions with more confidence, and ultimately improve patient care.
Importance of data visualization in healthcare
The importance of data visualization in the healthcare sector is driven by digitalization trends, increasing data volumes, and the pursuit of improved performance.
$167 billion — expected global healthcare analytics market volume by 2030
30% — global data volume generated by the healthcare industry
65% — less time spent on data analysis using electronic health record (EHR) visualization
Data visualization in healthcare isn’t a one-and-done solution–it’s a living, breathing process that must evolve with our understanding of patient needs and clinical workflows. Through continuous evaluation and refinement, we can make the most out of raw data—actionable insights that change healthcare for the better.
Alexey Kozlovsky
Delivery Manager
Benefits of data visualization in healthcare
Data visualization presents complex information in formats that are easy-to-digest for various audiences, creating an array of advantages for healthcare organizations.
Better choices, faster
Visualizations make complex data crystal clear, so healthcare professionals can make smart decisions quickly. Beyond simply clarifying complex information, visualizations reveal outliers that might be missed in traditional tabular data display. It’s widely acknowledged that presenting data visually reduces the cognitive load required to process information, leading to faster comprehension and quicker decisions. This is particularly valuable in time-sensitive healthcare situations.
Getting everyone on the same page
Visuals are a universal language in healthcare, helping diverse teams grasp medical data and collaborate successfully. Effective communication is crucial in healthcare, as breakdowns in communication are a leading cause of medical errors. Visualizations can bridge communication gaps between specialists, nurses, and patients, creating a foundation for a shared understanding of diagnosis and treatment plans.
Improved efficiency in hospital operations
Visual dashboards provide significant insight into how your hospital is running, facilitating data-driven decisions to improve efficiency and maximize resources. Using visuals to monitor key performance indicators (KPIs) like patient flow, bed occupancy rates, staff utilization, and resource allocation improves resource management and reduces costs. Real-time visibility into equipment usage can help identify bottlenecks and improve scheduling while monitoring supply levels can prevent stock-outs and reduce waste.
Clear data presentation for patients
Data visualization can translate complex medical jargon into clear, accessible formats, empowering patients to understand their health and actively participate in their care. Engaged patients are more likely to adhere to treatment plans and experience better health outcomes. Data visualization also supports informed consent by presenting treatment options and potential risks and benefits in a clear, visual manner, fostering stronger patient–physician relationships.
Data Visualization Services
Explore our expertiseHealthcare data visualization use cases
Healthcare data visualization has many forms and facilitates various healthcare aspects and processes. Here’s an overview of its applications:
Real-time patient monitoring
Visualizations in dashboard form give clinicians quick access to important patient data, like vital signs, lab results, medication adherence, and other key metrics. In addition, customizable alerts for critical values immediately notify healthcare providers when something is wrong, allowing them to take action quickly. Dashboards can be tailored for specific clinical settings, like intensive care units, emergency departments, or even remote patient monitoring programs.
Predictive analytics visualizations
These visualizations are becoming more prevalent, fueled by the growth of machine learning (ML) and data analytics in healthcare. However, the accuracy and reliability of these tools depend heavily on the quality of the data and the sophistication of the algorithms used. These tools show promising results in areas like predicting hospital readmissions and identifying patients at high risk for developing chronic conditions (e.g., research on using ML for risk stratification in heart failure patients).
Operational efficiency tracking
Healthcare organizations often use data visualization tools to track KPIs related to hospital operations, including patient flow, bed occupancy rates, emergency room wait times, operating room utilization, staffing levels, and supply chain management indicators. Using data dashboards to optimize workflows can lead to improvements in efficiency, such as reduced patient wait times and improved resource allocation. Dashboards, whether basic reporting tools or advanced integrated systems, aim to provide actionable insights that enhance operational performance.
Financial performance and analytics
Interactive dashboards can display key financial metrics, such as revenue cycle time, payer mix, cost per patient, and profitability by department. These visualizations help monitor and analyze financial performance, track revenue and expenses, identify cost-saving opportunities, and improve financial planning. Visualization of these data helps reveal areas of financial strength and weakness, inform strategic decision-making, and contribute to the long-term financial sustainability of healthcare operations. For example, visualizing the revenue cycle can pinpoint bottlenecks in billing and collections, leading to process improvements and faster reimbursement.
The healthcare industry is generating an increasing amount of data from different sources and in various formats. Healthcare data management systems help medical organizations handle all this information, facilitating patient care and decision-making. However, healthcare clinics must be prepared for the challenges they may encounter when implementing these systems.
Data visualization tools in healthcare
The market offers a wide range of data visualization tools. Below is a comparison of the most prominent ones:
| Tableau | Domo | Microsoft Power BI | Qlik | Looker | |
|---|---|---|---|---|---|
| Price | Tableau Desktop, offering limited features, is available for free. Tableau Viewer is priced at $15 per user per month, Tableau Explorer is $42 per user per month, and Tableau Creator costs $75 per user per month. | Pricing is arranged individually with the platform. Domo operates on a credit-based model; instead of paying for each feature individually, users purchase credits, which are depleted based on the amount of data handled and the frequency of data refreshes. | Power BI Desktop, with limited functionality, is free. Power BI Pro is available for $10 per user per month, while Power BI Premium costs $20 per user per month. | Qlik pricing starts at $825 per month for 20 users under its Standard plan. The Premium plan is priced at $2,500 per month for 20 users, while pricing for the Enterprise plan is discussed individually. | Looker offers Standard, Enterprise, and Embed plans, with pricing discussed individually. |
| Ease of learning | Offers a drag-and-drop interface with calculations similar to other software like Microsoft Excel or SQL, making it easy to learn. | The drag-and-drop interface allows users to create visualizations, dashboards, and reports without writing code. Pre-built connectors to common data sources simplifies the data import process. | Its similarity to Microsoft Excel makes it relatively easy to learn. However, users may require some training to navigate its more challenging features, like DAX. | Can be more challenging than other tools due to its data modeling complexity and its proprietary scripting language for data transformations and ETL. | Provides a user-friendly interface and intuitive dashboarding; however, it requires SQL/LookML knowledge for setup and customization, which can be challenging for nontechnical specialists. |
| Unique features | Unique VizQL engine enables an intuitive analytics experience. | Social elements like sharing, comments, and mentions enhance teamwork. | Offers intelligent narratives and anomaly detection features. As part of the Microsoft Cloud for Healthcare platform, it is tailored to the healthcare industry by default. | Allows multi cloud and on-premises installations without restricting users to any specific cloud. | The modeling language, LookML, enables data teams to define and centralize data logic, metrics, and calculations, ensuring consistent analytics without requiring individual users to write SQL. |
| Limitations | Not suited for large datasets. | Limited customization capabilities. | Azure-only deployment. | Limited visualization capabilities compared to other BI tools. | Can be expensive, making it inaccessible to smaller organizations. |
Data visualization challenges
The complexity of medical data and the related nuances can pose certain challenges that must be addressed to ensure successful data visualization initiatives.
Fragmented data
Healthcare data is highly sensitive and subject to strict privacy regulations, such as HIPAA in the US and GDPR in Europe. Visualizations must be designed with privacy in mind, incorporating de-identification techniques, access controls, and security measures to protect patient confidentiality. Balancing actionable insights with patient privacy requires careful planning and adherence to regulatory requirements. Techniques like differential privacy can help provide aggregate insights while preserving individual privacy.
Data privacy preservation
Healthcare data is highly sensitive and subject to strict privacy regulations, such as HIPAA in the United States, GDPR in Europe. Visualizations must be designed with privacy in mind, incorporating de-identification techniques, access controls, and security measures to protect patient confidentiality. Balancing the need for actionable insights with the need to safeguard patient privacy requires careful planning and adherence to regulatory requirements. Techniques like differential privacy can help provide aggregate insights while preserving individual privacy.
The balance between clarity and descriptiveness
Creating data visualization tools that are both informative and easy to understand can be a challenging task. Overly complex graphics and terminology can lead to misinterpretation, while simplistic presentations may fail to capture the intricacies of the data. The optimal approach depends on the specific audience and the goals of the visualization. For clinicians, detailed visualizations might be appropriate, while for patients, simpler and more intuitive displays are often preferred. User-centered design principles, including usability testing and iterative design, are essential for creating effective visualizations that meet the needs of diverse stakeholders.
Very clean, right to the point, and delivered as promised
Please accept my gratitude for the team’s hard work, good, working software developed, and today’s nice demo! Very clean, right to the point, and delivered as promised! From my current position I’ll still be trying to positively influence further progress and extensions of the project, expressing my positive view on our company’s cooperation and outlining future paths. The Intelon-SaaS has been ‘my baby’ from the commencement so I hope to be involved on future technical paths and aspects of the project.
Oleg Yakimovich
Sr. Director of Software Engineering
Intelon Optics
Could not have asked for a better team
Our dedicated team had impeccable management. Each request was clearly outlined with detailed scope and schedule. Deliverables were always on time and of very high quality. Could not have asked for a better team. Our dedicated team had impeccable management. Each request was clearly outlined with detailed scope and schedule. Deliverables were always on time and of very high quality. Could not have asked for a better team.
Rob Carthel
Business Analyst
MY DR NOW
Our approach to data visualization in healthcare
Discovery and needs assessment
We begin by engaging with stakeholders to thoroughly understand their data visualization goals, target audience, available data sources, and technical constraints. This involves conducting interviews, reviewing existing documentation, and analyzing sample data to understand the project context.
Collaborative design and prototyping
We work with clients to design and develop interactive prototypes of the visualization solution. This iterative process allows us to gather feedback early and often to ensure the final product meets the needs of all stakeholders. We adhere to user-centered design principles focused on usability, accessibility, and adherence to healthcare-specific design guidelines.
Data integration and preparation
We develop data pipelines to integrate data from diverse sources and guarantee data quality, consistency, and accuracy. We use industry-standard interoperability standards, such as FHIR, and employ data cleaning and transformation techniques to prepare the data for visualization.
Technology selection and development
We carefully select the most appropriate technologies, frameworks, and tools for each project to maximize security and performance. Our development process follows Agile methodologies, with continuous testing and integration to ensure high quality and rapid iteration.
Deployment and training
We deploy the visualization solution and provide training and documentation to help users effectively integrate the tools into their workflows. We offer ongoing support and maintenance to ensure the long-term success of the project.
Evaluation and refinement
We believe data visualization is an ongoing process. We work with clients to evaluate the effectiveness of the solution and identify areas for further improvement or advancement. Supported by data, we refine visualizations to ensure they continue to meet the evolving needs of the healthcare organization.
Healthcare data visualization examples
For many years, we’ve been collaborating with healthcare companies, creating powerful data visualization solutions.
KPI development and visualization for a healthcare provider
Our experts created an analytics platform and identified relevant KPIs to help a leading US healthcare provider with a vast network of clinics across the country obtain data-driven insights. Our team of business analysts conducted an in-depth study of the clinics’ operations to identify four KPI categories. Leveraging Power BI, we developed a custom dashboard to facilitate effective monitoring of the selected KPIs. We integrated the dashboard into the existing data warehouse infrastructure to enable real-time KPI visualization. The dashboard displays metrics over various periods in the form of a table, helping analyze trends and track progress.-
Effective system for urgent care operations management
EffectiveSoft developed a comprehensive system for managing the daily operations of an expanding US-based urgent care operator. According to the client’s requirements, our team incorporated scheduling functionality for medical staff and developed a robust reporting system with data visualization capabilities and support for exporting PDF and CSV files. Additionally, we integrated CPT/ICD data into the application’s database of medical codes and enhanced the notifications system with new features to improve the patient experience.
Final word
Healthcare data visualization is changing the way we understand and use medical information, from clinical decision making to patient care planning. While the opportunities for integration are great, success requires overcoming complex challenges such as data fragmentation and privacy requirements. With the right expertise, these hurdles become stepping stones to impactful insights that drive better healthcare outcomes. Are you ready to unlock the potential of your healthcare data? Let’s connect and explore how we can help you achieve your visualization goals.
F.A.Q. about healthcare data visualization
Data visualization in healthcare is the graphical representation of complex medical data in charts, graphs, tables, dashboards, and other formats that allow users to quickly obtain meaningful insights and make decisions.
The cost of health data visualization varies depending on the specifics of the project and the tools used for data analysis and visualization. Since data visualization encompasses a range of solutions, you have numerous options when determining which tool best meets your requirements. Contact us for an estimate on your healthcare data visualization project.
Medical data visualization enables healthcare professionals to quickly evaluate vast amounts of data, allowing them to prescribe necessary therapies and care in the shortest possible time. This efficiency expedites recovery while minimizing the risk of complication.
Yes! Data visualization tools can integrate with EHR systems, significantly enhancing how healthcare providers interpret and use patient data. Data visualization facilitates data centralization, supports clinical decision-making, enables patient outcome forecasting, improves patient engagement, and more.
We envision the future of healthcare data visualization as closely linked to the latest technologies.
Artificial intelligence (AI) and ML techniques enable automated insights and predictions, allowing doctors to uncover hidden patterns in vast datasets, resulting in more accurate diagnoses and treatment plans.
Virtual and augmented reality (VR and AR) facilitate immersive and interactive experiences in data analysis. Healthcare professionals can use VR to better understand and make decisions about complex anatomical systems, medical procedures, and treatment outcomes.
Real-time data streaming allows healthcare practitioners to view and analyze data as it is created, resulting in proactive and timely treatments.
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