Different views of personal information helps patients understand probabilities
When it comes to conversations with patients, there are many ways for healthcare providers to give information about managing cardiovascular disease. A provider might share probabilities about the success rates of different interventions, or perhaps anecdotal experiences based on empirical observations.
Better yet, researchers at Ohio State are now expanding a translational data analytics project that presents providers and patients with individually customized visualizations that integrate a patient’s choices, probable outcomes of those choices, and personal data from electronic health records.
Why a visualization? “Visualizations are easier to interpret,” explains TDA@OhioState affiliate and Faculty Advisory Board member Albert Lai, PhD. “Even highly educated people can have a difficult time when it comes to managing multiple probabilities and statistics. A different view is a benefit to the provider and the patient.”
Lai, an assistant professor of bioinformatics in the College of Medicine, compares his work in the project to that of a plumber—helping to build pipelines of information from patient health records to create visualizations that ultimately enhance communication between healthcare providers and patients.
The original model for the endeavor is a web-based application developed by an Ohio State team led by Randi Foraker, PhD, assistant professor of biomedical informatics and of epidemiology in the College of Public Health. The application is called SPHERE, an acronym for Stroke Prevention in Healthcare Delivery EnviRonmEnts. While the name of the SPHERE project is stroke-specific, the researchers see SPHERE as a model for prevention tools for other diseases, such as diabetes or even cancer.
The visualization created by SPHERE is more than just a static graphic representation: Foraker says the visual information can adjust as healthcare providers and patients consider lifestyle and treatment alterations. “It takes all the values from electronic health records and brings them to life at the point of care,” she says. “The visualization takes into consideration modifiable factors than can be manipulated, so providers can take data and see adjustments in real time.”
Of course, not every risk factor for disease can be manipulated; factors such as age are beyond a patient’s control. But the visualizations will provide patients a graphic representation of the impacts of choices such as decreasing body mass index or increasing physical activity.
As Foraker points out, with the World Health Organization ranking cardiovascular disease as the most common cause of death worldwide, there is a bigger picture, too. Creating a system that gives patients a more vivid understanding of the epidemiology of disease and modifiable outcomes has the potential to impact population health on nothing less than a global scale.