As the world grapples with the COVID-19 crisis, RTI’s experts in public health economics are exploring ways that existing models can help efforts to plan for the post-pandemic future.
We sat down with Amanda Honeycutt and Ben Yarnoff to discuss PRISM, a predictive modeling tool designed by RTI in collaboration with the Centers for Disease Control and Prevention (CDC). Health authorities and policymakers can use PRISM to estimate what would happen in their communities if chronic disease risk factors were to change. These risk factors include management of chronic conditions, like diabetes and high blood pressure, or access to healthy foods, tobacco cessation services, or care for psychological distress.
Tell us about PRISM. What does it do, and who can use it?
Amanda Honeycutt: The Prevention Impacts Simulation Model, or PRISM, is a web-based tool that estimates the likely impact on population health of 32 chronic disease prevention and management strategies. PRISM includes strategies to address smoking, air pollution, diet, physical activity, and management of chronic conditions, including diabetes, hypertension, high cholesterol, and psychological distress. PRISM applies evidence from the scientific literature to mathematically model the impact of changes in the strategies on disease prevalence, mortality, and costs.
PRISM is publicly available. Anyone can create an account for free and then use PRISM to examine the impact of one or more changes in the 32 chronic disease strategies. Public health and health care planners at local, state, and national levels can use PRISM to support planning for future efforts and to evaluate the impacts of past investments.
RTI worked with CDC and NIH over 15 years to develop and apply PRISM to support strategic planning for chronic disease prevention throughout the US, including in the Mississippi Delta; Austin, Texas; and several communities with Communities Putting Prevention to Work (CPPW) awards. We also used PRISM to estimate the potential long-term impacts of changes implemented by communities funded by CDC through CPPW and the Community Transformation Grants programs.
PRISM can be used to address a variety of policy questions, such as how many lives could be saved and the return on investment if 80 percent of adults with hypertension had their blood pressure under control? The Los Angeles County Health Department used PRISM to answer the question of how their CPPW grant efforts were likely to impact deaths and hospital costs over the ensuing 30 years. The Mississippi Delta and city of Austin used PRISM to answer “What evidence-based chronic disease prevention and control strategies would have the greatest impact on deaths if implemented in our communities”?
COVID-19 is a new phenomenon. How can PRISM be used to model the impact of COVID-19 in a community?
Ben Yarnoff: Although COVID-19 is not modeled directly in PRISM, the current pandemic may nonetheless affect many of the chronic disease risk factors modeled in PRISM. For example, as health care systems are stressed with the impact of testing for and treating COVID-19, they may face challenges in providing quality care for their patients with chronic illnesses, such as diabetes, hypertension, and high cholesterol. And, because recent evidence suggests that these underlying chronic conditions are associated with COVID-19 severity, understanding the impact of reduced care for these conditions could help with predictions of severe COVID-19 complications in a population. Patients with these conditions or who experience a cardiovascular disease event may also be reluctant to seek clinical care and refill prescription medicines because of fears of being exposed to the virus. Further, patients with psychological distress may struggle to obtain the care they need, especially if they lack access to virtual care providers.
Although we typically use PRISM to explore the impact of implementing strategies to improve chronic disease management, we can also use PRISM to analyze the impacts of declines in the management and care of cardiovascular disease and its risk factors. In fact, using PRISM, we estimated that the 2020 U.S. adult death rate from these risk factors could increase from 5.0 per 1,000 adults to 6.1 per 1,000 with even modest declines in the use of quality care for diabetes, hypertension, high cholesterol, psychological distress, and cardiovascular disease events. That’s a 21 percent increase in deaths from these conditions – roughly equivalent to the long-term effects of doubling the number of smokers, increasing air pollution by 150 percent, and increasing adult sodium consumption by one-third.