Effect of personal characteristics on individual support for indoor smoke-free air laws, Indiana, 2008.

INTRODUCTION: Policy makers should understand the attitudes and beliefs of their constituents regarding smoke-free air legislation. The purpose of this study was to evaluate the effect of selected personal characteristics on attitudes and beliefs about secondhand smoke in Indiana and on support for smoke-free air laws. METHODS: Data were obtained from the 2008 Indiana Adult Tobacco Survey of 2,140 adults and included 11 sociodemographic variables. Chi-square and multiple logistic regression analyses were used to test for significant associations between sociodemographic characteristics and support for statewide or community smoke-free air legislation. RESULTS: Most respondents (72.3%) indicated that they supported laws making work places smoke-free. After adjusting for the effects of the other variables, 3 were found to be significant predictors of support: being a never or former smoker, being female, and being aware of the health hazards of secondhand smoke. Age, race/ethnicity, income, urban or rural county of residence, employment status, and having children in the household were not significant when adjusting for the other characteristics. CONCLUSION: Most Indiana residents support smoke-free air legislation for workplaces. The support was constant among most groups across the state, suggesting policy makers would have the backing of their constituents to pass such legislation. The results of this study suggest that efforts to gain support for smoke-free air laws should focus on men, people unaware of the health hazards from secondhand smoke, and smokers and former smokers.

On the measurement of health and its effect on the measurement of health inequality.

We examine the extent to which self-reported health measures suffer from income-related reporting heterogeneity and then characterize how this reporting heterogeneity affects the estimation of income-related health inequality. We run a comprehensive set of tests of reporting heterogeneity using several self-reported health measures and several clinical measures of health from the National Health and Nutritional Examination Surveys. We propose the use of a multidimensional measure using clinical indicators of health in the context of measuring income-related health inequality, and we examine the extent of income-related health inequality, as measured by the concentration index, using both self-reported measures of health and the multidimensional clinical measure. Our results confirm the existence of significant, positive, income-related reporting heterogeneity and also suggest that higher income individuals react more strongly to a change in clinical health measures. Using self-assessed health suggests that income-related health inequality is about three times larger than when using more objective, self-reported health measures and ten times larger than when using the multidimensional clinical measure of health.

The effects of employment on influenza rates.

The seasonal influenza virus afflicts millions of people in the U.S. population each year, imposing significant costs on those who fall ill, their families, employers, and the health care system. The flu is transmitted via droplet spread or close contact, and certain environments, such as schools or offices, promote transmission. In this paper, we examine whether increases in employment are associated with increased incidence of the flu. We use state-level data on the prevalence of the flu from the Centers for Disease Control and Prevention. In our preferred specification, we find that a one percentage point increase in the employment rate increases the number of influenza related outpatient health care visits by 19%, and these effects are highly pronounced in the retail sector and healthcare sector, the sectors with the highest levels of interpersonal contact.

Improving research and policy interactions requires a better understanding of what works in different contexts.

There is keen interest in many jurisdictions in finding ways to improve the way that research evidence informs policy. One possible mechanism for this is to embed academics within government agencies either as advisers or full staff members. Our commentary argues that, in addition to considering the role of academics in government as proposed by Glied and colleagues, we need to understand better how research and policy interactions function across policy sectors. We believe more comparative research is needed to understand if and why academics from certain disciplines are more likely to be recruited to work in some policy sectors rather than others. We caution against treating government as monolithic by advocating the same model for collaborative interaction between academics and government. Lastly, we contend that contextualized research is needed to illuminate important drivers of research and policy interactions before we can recommend what is likely to be more and less effective in different policy sectors.

An information theory based framework for the measurement of population health.

This paper proposes a new framework for the measurement of population health and the ranking of the health of different geographies. Since population health is a latent variable, studies which measure and rank the health of different geographies must aggregate observable health attributes into one summary measure. We show that the methods used in nearly all the literature to date implicitly assume that all attributes are infinitely substitutable. Our method, based on the measurement of multidimensional welfare and inequality, minimizes the entropic distance between the summary measure of population health and the distribution of the underlying attributes. This summary function coincides with the constant elasticity of substitution and Cobb-Douglas production functions and naturally allows different assumptions regarding attribute substitutability or complementarity. To compare methodologies, we examine a well-known ranking of the population health of U.S. states, America's Health Rankings. We find that states' rankings are somewhat sensitive to changes in the weight given to each attribute, but very sensitive to changes in aggregation methodology. Our results have broad implications for well-known health rankings such as the 2000 World Health Report, as well as other measurements of population and individual health levels and the measurement and decomposition of health inequality.

Accessibility, usability, and usefulness of a Web-based clinical decision support tool to enhance provider-patient communication around Self-management TO Prevent (STOP) Stroke.

This article reports redesign strategies identified to create a Web-based user-interface for the Self-management TO Prevent (STOP) Stroke Tool. Members of a Stroke Quality Improvement Network (N = 12) viewed a visualization video of a proposed prototype and provided feedback on implementation barriers/facilitators. Stroke-care providers (N = 10) tested the Web-based prototype in think-aloud sessions of simulated clinic visits. Participants' dialogues were coded into themes. Access to comprehensive information and the automated features/systematized processes were the primary accessibility and usability facilitator themes. The need for training, time to complete the tool, and computer-centric care were identified as possible usability barriers. Patient accountability, reminders for best practice, goal-focused care, and communication/counseling themes indicate that the STOP Stroke Tool supports the paradigm of patient-centered care. The STOP Stroke Tool was found to prompt clinicians on secondary stroke-prevention clinical-practice guidelines, facilitate comprehensive documentation of evidence-based care, and support clinicians in providing patient-centered care through the shared decision-making process that occurred while using the action-planning/goal-setting feature of the tool.