The boomers are coming: a total cost of care model of the impact of population aging on the cost of chronic conditions in the United States.

The purpose of this study is to estimate the impact of population aging on medical costs over the next five decades in the United States. Specifically, we focus on the impact of aging on the chronic and/or expensive conditions most often included in disease management programs: coronary artery disease (CAD), congestive heart failure (CHF), diabetes, asthma, pregnancy, psychiatry, and chemical dependency. We apply estimated age-, gender-, and condition-specific annualized costs to the projected US population in each age and gender group for future years, through 2050, to provide an estimate of future healthcare costs. The primary data sources are pooled claims and membership for 2002 and 2003 for HealthPartners, a large midwestern health plan. Secondary sources are US annualized medical costs for 2003 and US Census Bureau demographic projections for the next five decades. Using the Episodes Treatment Group (ETG) grouper from Symmetry, we grouped HealthPartners data into 574 clinically meaningful episodes of care units. We then aggregate selected ETGs into the conditions reported in this study. Using data for all types of health services, we find that aging will have a greater impact on per capita costs for diseases where the ratio of costs for older versus younger ages is greater, such as CHF, CAD, and diabetes. In addition, we project that aging of the US population will actually reduce per capita costs for pregnancy and infertility, chemical dependency, and psychiatric conditions. Aging will have more of an impact on care for specific chronic diseases. These projections can inform health policy and planning as providers of health care, health plans, disease management vendors, and the government anticipate meeting future US healthcare needs.

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.

OBJECTIVE: To project the impact of population aging on total U.S. health care per capita costs from 2000 to 2050 and for the range of clinical areas defined by Major Practice Categories (MPCs). DATA SOURCES: Secondary data: HealthPartners health plan administrative data; U.S. Census Bureau population projections 2000-2050; and MEPS 2001 health care annual per capita costs. STUDY DESIGN: We calculate MPC-specific age and gender per capita cost rates using cross-sectional data for 2002-2003 and project U.S. changes by MPC due to aging from 2000 to 2050. DATA COLLECTION METHODS: HealthPartners data were grouped using purchased software. We developed and validated a method to include pharmacy costs for the uncovered. PRINCIPAL FINDINGS: While total U.S. per capita costs due to aging from 2000 to 2050 are projected to increase 18 percent (0.3 percent annually), the impact by MPC ranges from a 55 percent increase in kidney disorders to a 12 percent decrease in pregnancy and infertility care. Over 80 percent of the increase in total per capita cost will result from just seven of the 22 total MPCs. CONCLUSIONS: Understanding the differential impact of aging on costs at clinically specific levels is important for resource planning, to effectively address future medical needs of the aging U.S. population.

Paying for quality improvement: compliance with tobacco cessation guidelines.

BACKGROUND: Identification and treatment of routine tobacco use in medical practice is an effective intervention but is not used consistently. A study was conducted at HealthPartners, a large network-model health plan in Minnesota, to determine the effect of an outcomes recognition strategy that involved bonus funds and the rates at which network physicians document that tobacco users are identified and advised to quit. METHODS: Audits of 14,489 ambulatory patient records from 19-20 medical groups were conducted to determine the proportion of charts from each medical group that demonstrated identification of smoking status and counseling to encourage quitting at the most recent office visit in each year. RESULTS: Overall mean tobacco use identification increased from 49% +/- 7% (95% confidence interval [CI]) in 1996 to 73% +/- 7% in 1999 (p < .001), while advice to quit increased from 32% +/- 10% in 1996 to 53% +/- 10% CI in 1999 (p < .005). The number of medical groups with tobacco status identified at > 80% of visits and > 80% of tobacco users advised to quit increased from 0 in 1996 to 8 in 1999. DISCUSSION: Data feedback combined with a financial incentive appear to be an effective way for a health plan to improve physician compliance with the tobacco treatment guideline. Other health plans might consider similar reporting and incentive approaches to effectively engage medical group leadership and to improve the health of their members who use tobacco.