AcademyHealth announced Mathematica as one of three winners of the AcademyHealth 2022 Health Equity DataJam, an effort to harness the power of data to answer pressing questions about health and health care disparities.
Mathematica’s winning entry, Community Connector, is a free, open-source tool that uses data sources in an innovative way to address health care disparities in Colorado. The interactive tool integrates federal, state, and local data sources relevant to social determinants of health (SDoH). The resulting data set and visualizations can be used to identify communities that have had success in addressing social needs and improving health and well-being. The tool helps users understand and explore community differences and similarities and provides more resources and opportunities for communities to use SDoH data when identifying intervention opportunities. In addition to expanding nationally and across health care outcomes, the Community Connector could potentially enable localities to customize their search for similar counties by uploading their own county-level data to the tool.
“Data sharing and collaboration are happening at a faster pace than ever before,” said AcademyHealth President and CEO Dr. Lisa Simpson. “The 2022 Health Equity DataJam winners demonstrate the myriad ways that making government data open to the public, easily discoverable, and machine-readable helps fuel new business models, scientific advancements, and collaborative innovation.”
“We designed this open-source tool to support the decision making of public and private groups, enabling them to visualize the associations and intersections between social determinants of health and obesity, diabetes, and kidney disease,” said Alex Bohl, director of data innovation at Mathematica. “We are honored by AcademyHealth’s recognition of Community Connector as a tool that can bridge gaps between data, technology, and policy decision makers and help us reach a more equitable, value-based health care system.”
Designed to be used by local government and public health officials, health care payers, researchers, and individual community members, Community Connector uses county-level health data sources and provides objective, county-level scores for various SDoHs. Using a machine learning algorithm, the tool enables users to identify counties most similar to theirs on measures such as demographics and nonmodifiable social needs characteristics relevant to obesity, diabetes, and kidney disease. The app displays the distribution of health outcomes for all counties and the 20 counties most similar to a particular user’s county for comparison. In 2020, Community Connector was also named the grand prizewinner of the Agency for Healthcare Research and Quality’s Visualization Resources of Community-Level Social Determinants of Health Challenge.