Challenge: Midlife mortality rates are rising in the United States (US), while in many other nations, mortality rates are decreasing. For example, Stein et al. (2017) found that “Deaths of Despair” due to suicide and substance abuse have increased dramatically among white males between the ages of 25-64 particularly in rural America. The MortalityMinder (MM) app’s goal is to enable healthcare researchers, providers, payers, and policy makers to gain actionable insights into how, where, and why midlife mortality rates are rising in the US.System
Description and Purpose: Using county-level data on mortality rates from CDC WONDER, MM explores mortality trends for adults ages 25-64 in the US from 2000 to 2017. Using county-level surveillance data from County Health Rankings, MM identifies social and economic factors associated with mortality trends at the county level for the US and individual states. The user selects the region (specific state or US) and the cause of death (All Causes,Cancer, Cardiovascular, or Deaths of Despair). MM divides counties into mortality risk groups using clustering and then finds statistical associations between groups and putative risk factors. MM dynamically creates three analysis and visualization infographics, each addressing a different question:
- What are the trends in midlife mortality rates for a selected cause of death across the United States and in a selected State?
- How do midlife mortality rates fora selected cause of death vary by county across the selected state and why? and
- How are county-level social and economic factors associated with midlife mortality rates for a selected cause of death in a selected State?
Innovation and Deployment: MM’s rigorous analysis of potential community-level determinants of mortality enables users to find unmet community needs that can lead to development of programs and policies to improve longevity. MortalityMinder was the third-place winner in the 2019 AHRQ “Social Determinants of Health Visualization Challenge”. MM dramatically illustrates recently reported mortality rate increases, while providing greater insights into state-level variations and their associated factors to help determine remedies. The MM app, http://mortalityminder.idea.rpi.edu, is an open source project implemented in R and JavaScript available via Github. We encourage code contributions from the community to help make MM an ongoing evolving resource for health providers, payers, and decision makers to find actionable insights into the social determinants of health. We also use the MM framework to understand disparities and social determinants of COVID-19 mortality, https://covidminder.idea.rpi.edu/.
Acknowledgments: MortalityMinder was created by students in the Rensselaer Data INCITE Lab with support from the United Health Foundation and the Rensselaer Institute for Data Exploration and Applications (IDEA).