Abstract

OBJECTIVE:

Concerns about the safety and efficacy of over-the-counter cold medications have led to a recent US Food and Drug Administration public health advisory against their use in children <2 years of age. Our goal was to examine caregiver understanding of the age indication of over-the-counter cold medication labels and identify factors, associated with caregiver understanding.

METHODS:

Caregivers of infant children (< or =1 year old) were recruited from clinics at 3 institutions. Questions were administered regarding the use of 4 previously common "infant" over-the-counter cold and cough medicines labeled to consult a physician if used in children <2 years of age. Literacy and numeracy skills were assessed with validated instruments.

RESULTS:

A total of 182 caregivers were recruited; 87% were the infants' mothers. Mean education level was 12.5 years, and 99% had adequate literacy skills, but only 17% had >9th-grade numeracy skills. When examining the front of the product label, 86% of the time parents thought these products were appropriate for use in children <2 years of age. More than 50% of the time, parents stated they would give these over-the-counter products to a 13-month-old child with cold symptoms. Common factors that influenced parental decisions included label saying "infant," graphics (eg, infants, teddy bears, droppers), and dosing directions. Caregivers were influenced by the dosing directions only 47% of the time. Caregivers with lower numeracy skills were more likely to provide inappropriate reasons for giving an over-the-counter medication.

CONCLUSIONS:

Misunderstanding of over-the-counter cold products is common and could result in harm if medications are given inappropriately. Label language and graphics seem to influence inappropriate interpretation of over-the-counter product age indications. Poorer parental numeracy skills may increase the misinterpretation of these products. Opportunities exist for the Food and Drug Administration and manufacturers to revise existing labels to improve parental comprehension and enhance child safety.

Background: The pandemic potential of influenza A (H5N1) virus is a prominent public health concern of the 21st century.

Objective: To estimate the effectiveness and cost-effectiveness of alternative pandemic (H5N1) mitigation and response strategies.

Design: Compartmental epidemic model in conjunction with a Markov model of disease progression.

Data Sources: Literature and expert opinion.

Target Population: Residents of a U.S. metropolitan city with a population of 8.3 million.

Time Horizon: Lifetime.

Perspective: Societal.

Interventions: 3 scenarios: 1) vaccination and antiviral pharmacotherapy in quantities similar to those currently available in the U.S. stockpile (stockpiled strategy), 2) stockpiled strategy but with expanded distribution of antiviral agents (expanded prophylaxis strategy), and 3) stockpiled strategy but with adjuvanted vaccine (expanded vaccination strategy). All scenarios assumed standard nonpharmaceutical interventions.

Outcome Measures: Infections and deaths averted, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness.

Results of Base-Case Analysis: Expanded vaccination was the most effective and cost-effective of the 3 strategies, averting 68% of infections and deaths and gaining 404 030 QALYs at $10 844 per QALY gained relative to the stockpiled strategy.

Results of Sensitivity Analysis: Expanded vaccination remained incrementally cost-effective over a wide range of assumptions.

Limitations: The model assumed homogenous mixing of cases and contacts; heterogeneous mixing would result in faster initial spread, followed by slower spread. We did not model interventions for children or older adults; the model is not designed to target interventions to specific groups.

Conclusion: Expanded adjuvanted vaccination is an effective and cost-effective mitigation strategy for an influenza A (H5N1) pandemic. Expanded antiviral prophylaxis can help delay the pandemic while additional strategies are implemented.

Primary Funding Source: National Institutes of Health and Agency for Healthcare Research and Quality.

As academic fields and professions go, health services research is relatively young. Whether one dates the beginning of this field to the first National Institutes of Health study section on health services research in 1960, the passage of Medicare and Medicaid in 1965 and the accompanying drive to develop the conceptual and analytic tools to manage them, or the founding of this journal by the Health Research and Educational Trust with a grant from the U.S. Public Health Service in 1966, its history is much shorter than that of many other disciplines. The field gained its own professional organization only as recently as 1981 with the establishment of the Association of Health Services Research (now called AcademyHealth).

This study examined whether externally rated job demand and control were associated with depression diagnosis claims in a heavy industrial cohort. The retrospective cohort sample consisted of 7,566 hourly workers aged 18-64 years who were actively employed at 11 US plants between January 1, 1996, and December 31, 2003, and free of depression diagnosis claims during an initial 2-year run-in period. Logistic regression analysis was used to model the effect of tertiles of demand and control exposure on depression diagnosis claims. Demand had a significant positive association with depression diagnosis claims in bivariate models and models adjusted for demographic (age, gender, race, education, job grade, tenure) and lifestyle (smoking status, body mass index, cholesterol level) variables (high demand odds ratio = 1.39, 95% confidence interval: 1.04, 1.86). Control was associated with greater risk of depression diagnosis at moderate levels in unadjusted models only (odds ratio = 1.47, 95% confidence interval: 1.12, 1.93), while low control, contrary to expectation, was not associated with depression. The effects of the externally rated demand exposure were lost with adjustment for location. This may reflect differences in measurement or classification of exposure, differences in depression diagnosis by location, or other location-specific factors.

The Child-Adolescent Mental Health Services (CAMHS) system confronts clinically complex youth with high rates of behavior problems, diverse mental health disorders, substance abuse, criminal behavior, and other "at risk" behaviors (e.g. school truancy, family conflict, etc.). Because of the complexity of the youth, the system has serious difficulties helping them to successfully overcome the myriad of problems they confront. This group proposes that a public health approach would help solve many of the inadequacies of the current system.

Abstract

Objectives. We assessed the potential health and economic benefits of reducing common risk factors in older Americans.
Methods. A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project their health and medical spending in prevention scenarios for diabetes, hypertension, obesity, and smoking.
Results. The gain in life span from successful treatment of a person aged 51 or 52 years for obesity would be 0.85 years; for hypertension, 2.05 years; and for diabetes, 3.17 years. A 51- or 52-year-old person who quit smoking would gain 3.44 years. Despite living longer, those successfully treated for obesity, hypertension, or diabetes would have lower lifetime medical spending, exclusive of prevention costs. Smoking cessation would lead to increased lifetime spending. We used traditional valuations for a life-year to calculate that successful treatments would be worth, per capita, $198018 (diabetes), $137964 (hypertension), $118946 (smoking), and $51750 (obesity).
Conclusions. Effective prevention could substantially improve the health of older Americans, and—despite increases in longevity—such benefits could be achieved with little or no additional lifetime medical spending.

BACKGROUND: The burden of hypertension and related health care needs among Mexican Americans will likely increase substantially in the near future.

OBJECTIVES: In a nationally representative sample of U.S. Mexican American adults we examined: 1) the full range of blood pressure categories, from normal to severe; 2) predictors of hypertension awareness, treatment and control and; 3) prevalence of comorbidities among those with hypertension.

DESIGN: Cross-sectional analysis of pooled data from the National Health and Nutrition Examination Surveys (NHANES), 1999-2004. PARTICIPANTS: The group of participants encompassed 1,359 Mexican American women and 1,421 Mexican American men, aged 25-84 years, who underwent a standardized physical examination.

MEASUREMENTS: Physiologic measures of blood pressure, body mass index, and diabetes. Questionnaire assessment of blood pressure awareness and treatment.

RESULTS: Prevalence of Stage 1 hypertension was low and similar between women and men ( approximately 10%). Among hypertensives, awareness and treatment were suboptimal, particularly among younger adults (65% unaware, 71% untreated) and those without health insurance (51% unaware, 62% untreated). Among treated hypertensives, control was suboptimal for 56%; of these, 23% had stage >/=2 hypertension. Clustering of CVD risk factors was common; among hypertensive adults, 51% of women and 55% of men were also overweight or obese; 24% of women and 23% of men had all three chronic conditions-hypertension, overweight/obesity and diabetes.

CONCLUSION: Management of hypertension in Mexican American adults fails at multiple critical points along an optimal treatment pathway. Tailored strategies to improve hypertension awareness, treatment and control rates must be a public health priority.

Purpose. Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models.

Methods. The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making.

Results. The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models.

Conclusions. Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.