Social determinants of health significantly impact morbidity and mortality; however, physicians lack ready access to this information in patient care and population management. Just as traditional vital signs give providers a biometric assessment of any patient, "community vital signs" (Community VS) can provide an aggregated overview of the social and environmental factors impacting patient health. Knowing Community VS could inform clinical recommendations for individual patients, facilitate referrals to community services, and expand understanding of factors impacting treatment adherence and health outcomes. This information could also help care teams target disease prevention initiatives and other health improvement efforts for clinic panels and populations. Given the proliferation of big data, geospatial technologies, and democratization of data, the time has come to integrate Community VS into the electronic health record (EHR). Here, the authors describe (i) historical precedent for this concept, (ii) opportunities to expand upon these historical foundations, and (iii) a novel approach to EHR integration.
Integrating public health and medicine to address social determinants of health is essential to achieving the Triple Aim of lower costs, improved care, and population health. There is intense interest in the United States in using social determinants of health to direct clinical and community health interventions, and to adjust quality measures and payments. The United Kingdom and New Zealand use data representing aspects of material and social deprivation from their censuses or from administrative data sets to construct indices designed to measure socioeconomic variation across communities, assess community needs, inform research, adjust clinical funding, allocate community resources, and determine policy impact. Indices provide these countries with comparable data and serve as a universal language and tool set to define organizing principles for population health. In this article we examine how these countries develop, validate, and operationalize their indices; explore their use in policy; and propose the development of a similar deprivation index for the United States.
Research indicates that women remain less financially prepared for retirement than are men. Little research has examined the gender difference in use of retirement plans. The present research assessed the gender difference in use of employer-sponsored and private retirement plans, and sought to account for this difference. Social status and human capital factors, occupation and industry of employment, and sense of financial self-efficacy were expected to account for gender differences. Findings indicated gender has no relationship with use of private retirement plans. However, females were found to be less likely to use an employer-sponsored plan, and this was largely accounted for by gender differences in occupation.
As home visitation programs go to scale, numerous challenges are faced in implementation and quality assurance. This article describes the origins and implementation of Every Child Succeeds, a multisite home visitation program in southwestern Ohio and Northern Kentucky. In order to optimize quality assurance and generate new learning for the field, a Web-based system (eECS) was designed to systematically collect and use data. Continuous quality assurance procedures derived from business and industry have been established. Findings from data collection have documented outcomes, and have identified clinical needs that potentially undermine the impact of home visitation. An augmented module approach has been used to address these needs, and a program to treat maternal depression is described as an example of this approach. Challenges encountered are also discussed.
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