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Cost of chronic disease in California: estimates at the county level
Paul M Brown1, Mariaelena Gonzalez, Ritem Sandhu Dhaul
1Health Sciences Research Institute, University of California, Merced.
Context:
An estimated 39% of people in California suffer from at least one chronic condition or disease. While the increased coverage provided by the Affordable Care Act will result in greater access to primary health care, coordinated strategies are needed to prevent chronic conditions. To identify cost-effective strategies, local health departments and other agencies need accurate information on the costs of chronic conditions in their region.
Objective:
To present a methodology for estimating the cost of chronic conditions for counties.
Methods:
Estimates of the attributable cost of 6 chronic conditions-arthritis, asthma, cancer, cardiovascular disease, diabetes, and depression-from the Centers for Disease Control and Prevention's Chronic Disease Cost Calculator were combined with prevalence rates from the various sources and census data for California counties to estimate the number of cases and costs of each condition. The estimates were adjusted for differences in prices using Medicare geographical adjusters.
Results:
An estimated $98 billion is currently spent on treating chronic conditions in California. There is significant variation between counties in the percentage of total health care expenditure due to chronic conditions and county size, ranging from a low 32% to a high of 63%. The variations between counties result from differing rates of chronic conditions across age, ethnicity, and gender.
Conclusions:
Information on the cost of chronic conditions is important for planning prevention and control efforts. This study demonstrates a method for providing local health departments with estimates of the scope of the problems in their region. Combining the cost estimates with information on current prevention strategies can identify gaps in prevention activities and the prevention measures that promise the greatest return on investment for each county.
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