The UDS Mapper is designed to help inform users about the current geographic extent of U.S. federal Health Center Program grantees and look-alikes. The information available in the UDS Mapper includes estimates of the collective service area of these health centers by ZCTA, including the ratio of HCP grantee and look-alike patients reported in the Uniform Data System (UDS) to the target population, the change in the number of those reported patients over time, and an estimate of those in the target population that remain unserved by HCP grantees and look-alikes reporting data to the UDS.
The AMA Health Workforce Mapper is interactive tool that illustrates the geographic locations of the health care workforce in each state, including health professional shortage areas, hospital locations, as well as other related workforce data. The tool is designed to highlight areas where the number of health care professionals could be expanded to enhance patient access to timely, quality care. The mapper was built by the Robert Graham Center for Policy Studies and HealthLandscape under contract to the American Medical Association and its Scope of Practice Partnership
The School-Based Health Alliance's Children's Health & Education Assessment Tool is a resource for those seeking to address the chronic inequities that persist among low-income children and adolescents in health care access and utilization. The tool allows users to map child and adolescent-specific data across multiple dimensions of need in order to identify high need areas and target locations of new health centers and services nationwide. Public school and School-Based Health Center locations, as well as other healthcare facilities, can be mapped and filtered.
Place matters to personal and population health. The social determinants of health have begun to shape public health and policy interventions. Neighborhood socioeconomic and demographic characteristics play significant roles in influencing health outcomes. People coming from economically disadvantaged neighborhoods and minority groups are at higher risk for a number of health conditions, particularly chronic conditions such as Diabetes. The Population Health Mapper includes the majority of the Health Outcome and Health Determinant Metrics identified in the report at the county level.
The Medicare Data Portal engages users with data from the Centers for Medicare & Medicaid Geographic Variation database and the Chronic Conditions Warehouse. Users can visualize health outcome, cost, and demographic data for the Medicare population using maps, graphs, and trend charts. Users can also examine the relationship between two indicators with side-by-side maps and a percentile comparison tool. The ACO Explorer allows for statistical analyses for exploring relationships between ACO quality measures and population health indicators. Together, they offer researchers tools for understanding complex datasets and developing new research questions.
The Appalachia Data Portal provides multiple methods for exploring population indicator disparities throughout the Appalachian region, and is a helpful tool for identifying health disparities and bright spots within the region. The tool allows users to visualize economic, demographic, and other types of data for the Appalachian region using maps, graphs, and trend charts. Users also have the ability to examine the relationship between two indicators (for example, Diabetes and Poverty) with side-by-side maps and a comparison tool that uses percentiles to visualize the relationship between variables.
The World Health Data Portal includes a number of indicators from the World Development Indicators Catalog produced by the World Bank and OECD Health Statistics produced by the Organization for Economic Co-operation and Development. The World Development Indicators Catalog is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.
Integrating social determinants of health data into patient level data yields a broader view of the environmental and social risks specific to each patient, by indicating whether patient lives in the presence of factors such as poverty, healthy food sources, walkable streets and parks, social capital, and much more. We present the HealthLandscape Geoenrichment API, a HIPAA-compliant DaaS solution that appends multiple geographic identifiers and small-area community characteristics to individual data.