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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.
healthcare data visualization
healthcare data visualization

    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.

    1. $167 billion — expected global healthcare analytics market volume by 2030
    2. 30% — global data volume generated by the healthcare industry
    3. 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

    Data Visualization Services

    Explore our expertise

    Healthcare data visualization use cases

    Healthcare data visualization has many forms and facilitates various healthcare aspects and processes. Here’s an overview of its applications:

    1. 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.
    2. 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).
    3. 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.
    4. 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.

    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.

    Our approach to data visualization in healthcare

    1. 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.

    2. 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.

    3. 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.

    4. 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.

    5. 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.

    6. 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.

    1. 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.
    2. 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.
    Examples of healthcare data visualization
    Examples of healthcare data visualization
    Examples of healthcare data visualization

    Final word

    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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