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Perinatal mental health problems, experienced by 15-20% of women, are a significant public health issue associated with adverse effects among childbearing women; yet only 20-25% receive adequate treatment. There has been a recent proliferation of intensive perinatal day treatment programs in the United States. To meet this need in the greater Philadelphia area, we introduce Mother Baby Connections (MBC), an innovative interdisciplinary, attachment-focused, intensive, outpatient perinatal mental health program recently launched at Drexel University. The purpose of this paper is to (1) present an overview of MBC, its theoretical framework for services, and its evidence-based components, highlighting the unique factors that differentiate this program from traditional outpatient treatment, and (2) present clinical outcome data utilizing scores from reliable and valid scales, including enrollment to discharge outcomes from 20 months of MBC operation. In sum, outcomes for 20 predominantly minority women with complete measures showed significant improvements in maternal depression symptom severity, maternal functioning, birth trauma symptoms, perceived stress, parenting stress, and emotional regulation. Effect sizes were medium to large (i.e., 0.42-2.00). We conclude that MBC is a viable model for tailored intensive outpatient treatment to foster maternal mental health and functioning during the perinatal period. [ABSTRACT FROM AUTHOR]

Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings--a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community. [ABSTRACT FROM AUTHOR]

This paper extends and further validates the quality-of-life/ community-healthcare model and measures developed by Rahtz and Sirgy (2000). The quality of life (QOL) model is based on the theoretical notion that community residents' satisfaction with healthcare services available within their community affects community quality of life and life satisfaction. This study extends the model and, in keeping with past research, posits that the bottom-up spillover from community QOL to life satisfaction is greater for those individuals with low personal health satisfaction, lower income, and old age. Data were collected from 1094 community residents in the East-Coast area of the United States. The results provide good support of the new model. Managerial implications and applications for the new model are discussed. [ABSTRACT FROM AUTHOR]