The Boomers Are Coming: A Total Cost of Care Model of the Impact of Population Aging on Health Care Costs in the United States by Major Practice Category
| Autor: | George Isham, Tammie Lindquist, E. Mary Martini, Nancy Garrett |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2007 |
| Předmět: |
Adult
Male Economic growth Population ageing Aging Adolescent Total cost Population Sex Factors Health care Per capita Economics Fees Pharmaceutical Humans education Child health care economics and organizations Health policy Aged Aged 80 and over education.field_of_study business.industry Health Policy Health services research Age Factors Infant Newborn Infant Health Care Costs Middle Aged United States Economics Medical Aging in the American workforce Child Preschool Medicine Demographic economics Female Treatment and Costs Health Services Research business Specialization |
| Popis: | Our work models the impact of population aging on health care costs in the United States over the next five decades, at an aggregate and clinical level. In the context of many years of increasing health care costs, future cost concerns have centered on the Baby Boom generation: the cohort of 74 million people born in the years 1946–1964 after World War II. The impact of population aging on these costs has become a frequently cited concern in the literature and popular media (Halvorson 2004; Kotlikoff and Burnes 2004; Worldwide Watson Wyatt 1996). While studies have discounted population aging as a factor to explain recent health care cost increases, the baby boom generation ranges from ages 42 to 60 in 2006, well before age-specific costs increase dramatically (Heffler et al. 2003; Meara, White, and Cutler 2004). Whether the total projected cost increase due to aging applies evenly across body systems, or whether and to what extent aging will have an impact on some body systems more than others, has been unknown. Understanding the differential impact of aging at a disaggregated clinically related level is critical to key stakeholders of the complex U.S. health care “system” such as providers, hospitals, health plans, training organizations, governments, drug companies, device manufacturers, and policy makers, as they plan to meet future age-related health care demands (Cooper 2004). Several studies of the impact of aging on total health care costs in different populations have similar overall findings. The Australian population's changing age structure is projected to account for a 0.6 percent annual increase in total health spending from 1995 to 2051 (Richardson and Robertson 1999). In a 1992 study of projected U.S. health care costs to 2030, population aging accounts for a 0.5 percent annual increase in costs (Burner, Waldo, and McKusick 1992). A more recent U.S. study projected per capita health care costs from 2000 to 2030 will increase 20 percent due to aging, or 0.6 percent/year (Alemayehu and Warner 2004). For Americans under age 65, the projected impact of aging is less than 1 percent annual cost growth from 2000 to 2010 (Strunk and Ginsburg 2002). A projection of aggregate personal health spending from 1990 to 2030 shows age-gender factors accounting for 5 percent of total personal health spending in 2030 (Burner et al. 1992; Reinhardt 2002). For the Medicare population only, the projected annual increase in costs per capita due to aging from 1992 to 2050 is 0.14 percent (Cutler and Sheiner 1998b). The present study extends the upper range of age- and gender-specific cost rates to ages 100 and above, which is beyond the more commonly reported upper age ranges of 75+ or 85+ (Cutler and Sheiner 1998b; Richardson and Robertson 1999; Alemayehu and Warner 2004; Meara et al. 2004). Our finer disaggregation increases precision to both the overall and detailed cost projections by reflecting variability in per capita cost rates by age and gender. We also extend others' work by examining the impact of aging on medical costs using the entire age range of the population, as opposed to only the working or senior populations used in some studies. Our model incorporates a commercially available, reputable, and replicable categorization methodology, which we use to decompose the total projected per capita cost increases into clinically related categories. Projected costs reflect a societal view for all health plan services and thus represent a broad view of the total cost of medical care. |
| Databáze: | OpenAIRE |
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