Bringing the Lab to Life: How Immersive Data Visualization is Changing Healthcare

The vast amount of data available today presents a significant opportunity for researchers to find ways for humans to interact with it effectively. The ability to comprehend the complexities of data visualization goes beyond just interpreting the data, it involves examining it from different angles to inform effective actions. As technology for creating data visualizations improves, it becomes increasingly important to critically consider how to create and interpret these visualizations as the way data is presented can have a significant impact on society.

Data is as important as software.

Immersive data visualization is a powerful tool that can be used to help pharmaceutical companies better understand and analyze large sets of data. By using technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), pharmaceutical companies can create immersive data visualizations that allow users to interact with and explore information in a more engaging and intuitive manner. One of the key benefits of immersive data visualization is that it allows us to gain a better understanding of complex data sets, such as clinical trial results, to interact with and explore the information in a more natural and intuitive way. This can be especially useful for large data sets or for data that is difficult to represent in traditional visualization methods. Pharmaceutical companies actively use immersive data visualization in various aspects of their business such as drug development, clinical trial design, and market research.

1. Clinical Trials - The way data is presented, can have an impact on society

The design of a clinical trial is a complex process that requires careful consideration of several key factors such as the patient population, trial design, sample size, and methods to minimize bias. Immersive data visualization can be used to visualize patient data in a more holistic way and increase the chances of a successful outcome and ultimately bring new drugs to market. For example, VR and AR can be used to create immersive visualizations of patient anatomy and physiology, allowing them to better understand patient populations and identify potential trial sites. VR/AR has already been used to treat patients, during interventions in rehabilitation programs and in immobilized intensive care patients.

Presenting an overall picture of adverse events can reduce bias.

In clinical trials, adverse events are commonly reported by simply tallying the number of individuals who experienced them. However, this approach of reporting frequencies alone neglects other important dimensions of the data that are significant for stakeholders, such as intensity, gravity, rate of recurrence, timing, and groups of correlated harms. Furthermore, the application of selection criteria to harms often results in most of them going unreported. Utilizing data visualization techniques could enhance the communication of multidimensional data.

According to the Epidemiologic Reviews study on "Visualization Methods for Communicating Harms in Clinical Trials Data", presenting an overall picture of adverse events can reduce bias in reporting and be more comprehensive than current methods. Data on multiple dimensions for adverse events should be visualized by clinical trialists.

The concept of creating standards through a common data model is recognized as good data management and stewardship practice. In the context of immersive data visualization, this allows for the creation of interactive visualizations that allow users to explore and understand the results in a more intuitive way. According to Nature Portfolio 's journal on "Rethinking clinical study data" the approach can be applied in the medical field to improve patient diagnosis, support clinical decision-making, and aid in the development of new treatments.

2. Education in Practice - Make mistakes while maintaining patient safety

Using simulated virtual patient models in a clinical setting, immersive data visualization can be used to test and improve critical reasoning skills. Physicians can practice and improve diagnostic and treatment planning skills in a safe and controlled environment using these virtual models, which replicate real-life scenarios. Although digital applications and immersive data visualization may be useful to physicians, it is important to keep in mind that these tools are not meant to replace a physician's focus on the real patient, but rather to assist the physician in their decision-making process and improve patient care.

As an illustration, through Project Polaris , 微软 has partnered with NUS Yong Loo Lin School of Medicine to give medical and nursing students the ability to have a more visual understanding of actual clinical scenarios in practice.

It is also possible to train medical students and residents with virtual patient models in a clinical setting, as immersive data visualization can provide students with a more engaging way to practice clinical skills and improve their ability to diagnose and treat patients in a real-world environment. Moreover, virtual patient models can also be used for research to gain insight into the diagnostic and treatment decision-making process. The researchers can identify patterns and trends in the interactions between physicians and virtual patients, which can inform the development of new diagnostic and treatment guidelines.

3. Tools - The goal is to establish a platform-based model for turning data from its origin into valuable information

Data Visualization closes the loop in the modern data platform architecture. Users can employ Power BI to surface insights—be it customer insights in a call center, medical insight about patients in a clinic, data from medical devices or robotics, employee churn predictive analytics, or qualification data. Insights like these drive end-user actions within apps, give context to users and increase their ability to act at the time of data collection.

Establishing a platform-based model for turning data from its origin into valuable information is a key step in leveraging data to drive business decisions and improve operations. This model involves creating a centralized, unified platform that can collect, store, and process data from various sources, integrating it for a unified view of the data, implementing data governance policies and procedures for managing the data, creating visual representations of the data that can be easily understood by business users and using statistical and mathematical techniques to analyze the data and gain insights.

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4. Storytelling - Exploring the Latest Trends in Immersive Data Visualization for Effective Communication

There are two types of data visualization to consider when presenting data: explanatory and exploratory. Explanatory visuals are used to convey specific aspects or the entire story to the audience, while exploratory visuals are used when the questions that need to be answered with the data are not yet known. Data visualization allows for the telling of a story by connecting correlations, recognizing trends and drawing conclusions. It's important to note that data analytics presented without contextual storytelling can lead to prolonged decision-making, incorrect conclusions, or confusion.

By incorporating the principles of inclusion, interactivity, and immersive experiences in data visualization, we can create a more inclusive, interactive and engaging experience for users, that allows for deeper understanding and interaction with the data.

Immersive data visualization holds the potential to change the way healthcare technology is designed and used.

In conclusion, the increasing prevalence of data and data visualization in today's world highlights the potential for immersive data visualization in changing the way medical applications are designed and used. By offering a more intuitive way to interact with and understand data, immersive data visualization has the potential to greatly improve patient diagnosis and outcomes.