The effect of different public health interventions on longevity, morbidity, and years of healthy life.

BACKGROUND: Choosing cost-effective strategies for improving the health of the public is difficult because the relative effects of different types of interventions are not well understood. The benefits of one-shot interventions may be different from the benefits of interventions that permanently change the probability of getting sick, recovering, or dying. Here, we compare the benefits of such types of public health interventions. METHODS: We used multi-state life table methods to estimate the impact of five types of interventions on mortality, morbidity (years of life in fair or poor health), and years of healthy life (years in excellent, very good, or good health). RESULTS: A one-shot intervention that makes all the sick persons healthy at baseline would increase life expectancy by 3 months and increase years of healthy life by 6 months, in a cohort beginning at age 65. An equivalent amount of improvement can be obtained from an intervention that either decreases the probability of getting sick each year by 12%, increases the probability of a sick person recovering by 16%, decreases the probability that a sick person dies by 15%, or decreases the probability that a healthy person dies by 14%. Interventions aimed at keeping persons healthy increased longevity and years of healthy life, while decreasing morbidity and medical expenditures. Interventions focused on preventing mortality had a greater effect on longevity, but had higher future morbidity and medical expenditures. Results differed for older and younger cohorts and depended on the value to society of an additional year of sick life. CONCLUSION: Interventions that promote health and prevent disease performed well, but other types of intervention were sometimes better. The value to society of interventions that increase longevity but also increase morbidity needs further research. More comprehensive screening and treatment of new Medicare enrollees might improve their health and longevity without increasing future medical expenditures.

Synchrony of change in depressive symptoms, health status, and quality of life in persons with clinical depression.

BACKGROUND: Little is known about longitudinal associations among measures of depression, mental and physical health, and quality of life (QOL). We followed 982 clinically depressed persons to determine which measures changed and whether the change was synchronous with change in depressive symptoms. METHODS: Data were from the Longitudinal Investigation of Depression Outcomes (LIDO). Depressive symptoms, physical and mental health, and quality of life were measured at baseline, 6 weeks, 3 months, and 9 months. Change in the measures was examined over time and for persons with different levels of change in depressive symptoms. RESULTS: On average, all of the measures improved significantly over time, and most were synchronous with change in depressive symptoms. Measures of mental health changed the most, and physical health the least. The measures of change in QOL were intermediate. The 6-week change in QOL could be explained completely by change in depressive symptoms. The instruments varied in sensitivity to changes in depressive symptoms. CONCLUSION: In clinically depressed persons, measures of physical health, mental health, and quality of life showed consistent longitudinal associations with measures of depressive symptoms.

The performance of administrative and self-reported measures for risk adjustment of Veterans Affairs expenditures.

OBJECTIVE: To evaluate the performance of different prospective risk adjustment models of outpatient, inpatient, and total expenditures of veterans who regularly use Veterans Affairs (VA) primary care. DATA SOURCES: We utilized administrative, survey and expenditure data on 14,449 VA patients enrolled in a randomized trial that gave providers regular patient health assessments. STUDY DESIGN: This cohort study compared five administrative data-based, two self-report risk adjusters, and base year expenditures in prospective models. DATA EXTRACTION METHODS: VA outpatient care and nonacute inpatient care expenditures were based on unit expenditures and utilization, while VA expenditures for acute inpatient care were calculated from a Medicare-based inpatient cost function. Risk adjusters for this sample were constructed from diagnosis, medication and self-report data collected during a clinical trial. Model performance was compared using adjusted R2 and predictive ratios. PRINCIPAL FINDINGS: In all expenditure models, administrative-based measures performed better than self-reported measures, which performed better than age and gender. The Diagnosis Cost Groups (DCG) model explained total expenditure variation (R2=7.2 percent) better than other models. Prior outpatient expenditures predicted outpatient expenditures best by far (R2=42 percent). Models with multiple measures improved overall prediction, reduced over-prediction of low expenditure quintiles, and reduced under-prediction in the highest quintile of expenditures. CONCLUSIONS: Prediction of VA total expenditures was poor because expenditure variation reflected utilization variation, but not patient severity. Base year expenditures were the best predictor of outpatient expenditures and nearly the best for total expenditures. Models that combined two or more risk adjusters predicted expenditures better than single-measure models, but are more difficult and expensive to apply.

Ethnic differences in satisfaction and quality of life in veterans with ischemic heart disease.

OBJECTIVE: To assess differences in self-reported health status and satisfaction between African-American and caucasian veterans with ischemic heart disease (IHD). DATA SOURCES/STUDY SETTING: African-American and caucasian patients enrolled in General Internal Medicine clinics at six Veteran Affairs Medical Centers. STUDY DESIGN: We conducted a cross-sectional analysis of baseline survey data from the Ambulatory Care Quality Improvement Project (ACQUIP). Patients who responded to an initial health-screening questionnaire were sent follow-up surveys, which included the Medical Outcomes Study 36-item Health Survey (SF-36), the Seattle Outpatient Satisfaction Questionnaire (SOSQ), and the Seattle Angina Questionnaire (SAQ). PRINCIPAL FINDINGS: Of the 44,965 patients approached, 27,977 (62%) returned the baseline survey, of which 10,385 patients reported IHD and were sent the SAQ. Of those, 7,985 patients (84% caucasian, 16% African-American) responded. Caucasian respondents tended to be older, married, nonsmokers, with annual incomes over dollar 10,000, and had higher educational attainment than African Americans. African-American patients reported significantly fewer cardiac procedures (33% vs. 52%, p < 0.001) but were more likely to have diabetes (37% vs. 28%, p < 0.001) and hypertension (81% vs. 68%, p < 0.001). After adjustment for demographic characteristics, comorbid conditions, clinic site, and site-ethnicity interactions, SF-36 scores for physical function, role physical, bodily pain, and vitality were greater for African Americans than caucasians, while adjusted scores were significantly lower for role emotional. However, because of the site-ethnicity interaction, scores varied significantly by site. For the SAQ, overall adjusted physical function summary scores and disease stability scores were significantly greater for African Americans than caucasians. Adjusted summary satisfaction scores for provider satisfaction were not significantly lower for African Americans overall but were significant at two of six sites. Similarly, on the SAQ, adjusted treatment satisfaction scores were significantly lower for African Americans at half of the sites and minimally but not clinically significant overall. CONCLUSIONS: Despite a higher prevalence of cardiac risk factors, African-American patients with CAD who were treated in the VA system appeared to have a greater level of physical functioning, vitality, and angina stability. After adjustment for confounding demographic variables, however, these differences were not consistently significant at all geographic locations. This suggests that many other sociodemographic variables, in addition to ethnicity, influence apparent discrepancies in quality of life, satisfaction, and angina.

Age-specific prevalence and years of healthy life in a system with three health states.

Consider a 3-state system with one absorbing state, such as Healthy, Sick, and Dead. Over time, the prevalence of the Healthy state will approach an 'equilibrium' value that is independent of the initial conditions. We derived this equilibrium prevalence (Prev:Equil) as a function of the local transition probabilities. We then used Prev:Equil to estimate the expected number of years spent in the healthy state over time. This estimate is similar to the one calculated by multi-state life table methods, and has the advantage of having an associated standard error. In longitudinal data for older adults, the standard error was accurate when a valid survival table was known from other sources, or when the available data set was sufficient to estimate survival accurately. Performance was better with fewer waves of data. If validated in other situations, these estimates of prevalence and years of healthy life (YHL) and their standard errors may be useful when the goal is to compare YHL for different populations.