Health Forecasting (UCLA)

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Founded in 2002, Health Forecasting (UCLA) is headquartered at the UCLA Fielding School of Public Health and works in collaboration with the Los Angeles County Department of Public Health and the California Department of Public Health.

Health Forecasting was established to provide decision-makers and health advocates prospective analysis of the public health landscape through the development and communication of evidence-based forecasts. The health forecasts include historical and future health trends and incorporate policy and programmatic interventions aimed at improving population health. The data and graphs generated are informative resources and analytic tools available for health advocates in their efforts to anticipate, prepare, and plan for healthier communities.

Central to this work is the Health Forecasting Tool, an interactive statistical model and web-based interface developed by researchers at UCLA. The tool is accessible online and allows anyone, from high-level government officials to members of the community, to create a health profile for populations within a given region and gauge the future health impacts of changes in programs and policies. Users can access population-level health information and outcomes of current and future populations and subgroups by race, ethnicity, age, gender, and geography. The tool also accounts for socio-economic factors, behavioral characteristics, and demographic shifts in population. The tool was modeled after a statistical model created by Statistics Canada and operates using continuous-time microsimulation. The Health Forecasting Tool combines known historical data derived from various resources, such as the Census, Center for Disease Control and Prevention, California Department of Education and Department of Finance among other definitive sources. These figures are then integrated with evidence-based population health trends and expected future population shifts to project health outcomes at the population-level.

Reports are customizable to suit the needs of a unique population by allowing the user to specify geographic boundaries and distributions of race, ethnicity, age, and gender. Results are displayed in easy-to-read graphic charts and reports.

There are three types of reports available according to degree of specificity:

Quick Reports- Pre-made graphs and analysis on select topics primarily drawn from Health Forecasting issue briefs

Basic Reports- Quick, click-and-point custom charts for a given population for all Health Forecasting studies. Graphs drawn from each study focus on one topic, such as total medical expenditures, and one category, which include Census year, demographic and health characteristics.

Advanced Reporting- Users can create custom, multilayer graphs and compare charts across one category. It provides detail specific data for each study. For example, the California Obesity study graph can be created by topic, such as an examination of mortality, then by a particular ethnic group (Latinos), and by Body-Mass- Index filtered to include only obese Latinos.

Studies currently available, include: a) Smoking Cessation b) Obesity c) Coronary Heart Disease d) Diabetes e) Population Projections (California and Los Angeles County) f) Placer Air Quality g) The California Endowment Building Healthy Communities Air Quality

Health Forecasting is funded with grants from the following:

The California Endowment- Expanding the capabilities of the Health Forecasting Tool by incorporating additional variables and focusing on interventions relevant to underserved individuals and communities in California

Kaiser Foundation- Efficiently combining multiple sources of survey data to improve local area estimates of health and forecasting outcomes for Los Angeles County.

The National Institute of Environmental Health Sciences- Examining drivers of health and longevity among Latinos in California and understanding the effects of interventions focusing on diabetes and cardiovascular disease

The National Institutes of Health- Forecasting and improving Latino health by examining the role of acculturation and physical activity to account for health disparities among the Latino population

Robert Wood Johnson Foundation- Incorporating additional risk factors and disease outcomes into the forecasting model and applying the model to other states, beginning with Arkansas and Wisconsin

The UniHealth Foundation- Supporting hospitals in assessing current and future characteristics of populations they serve and identifying long-term planning needs of local communities. Providing information on future health and health disparities among subpopulations in the absence of additional effective health promotion and disease prevention efforts


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