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Background: Hospital investments in care coordination services and innovative delivery models represent an important source for improving care efficiency and population health. Objective: The aim of this study was to explore variation of hospital-initiated care coordination services and participation in Accountable Care Organizations (ACOs) by community characteristics within an organizational theory framework. Methods: Our main data sets included the 2015 American Hospital Association Annual Survey, Survey of Care Systems and Payment, American Community Survey, and Area Health Resource File. Two main outcomes were (a) hospital reported initiation of care coordination practices (such as chronic disease management, post-hospital discharge continuity of care, and predictive analytics) and (b) participation in ACO models. State fixed-effects models were used to test the association between the adoption of care coordination practices and hospital characteristics, community level sociodemographic characteristics, and health policies. Results: Hospitals with large bed size, located in urban areas, and/or with high volume of operations were more likely to adopt care coordination practices and participate in the ACO models. Hospitals serving communities with high uninsurance rates and/or poverty rates were significantly less likely to provide care coordination practices. More stringent Community Benefit Laws (CBLs) were positively associated with the implementation of care coordination practices suggesting strong normative impacts of CBLs. Conclusion: Greater hospital-initiated care coordination practices and innovative ACO models were available in well-resourced areas. Policymakers may consider increasing resources for care coordination practices in rural, underserved, and high-poverty--high-uninsured areas to ensure that vulnerable populations can benefit from these services. [ABSTRACT FROM AUTHOR]

This study compared physiological data from an elite collegiate soccer player to those of his teammates over 2 seasons. The player of special interest (player A) was the winner of the MAC Hermann Trophy and was therefore considered the top player in National Collegiate Athletic Association (NCAA) division I soccer for each of the 2 seasons in which data were collected. Maximal oxygen consumption (...o2max) was measured during preseasons and heart rate (HR) was recorded during competitive matches. Polar Training Loads (PTL) were calculated using the Polar Team2 Pro (Polar USA) system based on time spent in HR zones. Player A had a lower than the team average in 2012 (56 vs. 61.5 ± 4.3 ml⋅kg-1⋅min-1) and a similar value in 2013 (54 vs. 56.9 ± 5.1 ml⋅kg-1⋅min-1). During matches, player A showed consistent significant differences from the team in percentage of time spent at 70-79% maximal heart rate (HRmax) (12.8 ± 5.5% vs. 10.1 ± 4.0%), 80-89% HRmax (54.3 ± 11.5% vs. 29.3 ± 6.8%), and 90-100% HRmax (23.1 ± 10.6% vs. 45.4 ± 8.5%). This led to a consistently lower PTL per minute accumulated by player A compared with his teammates (3.6 ± 0.4 vs. 4.4 ± 0.3), which may be beneficial over a season and may be related to his success. Thus, the ability to regulate moments of maximal exertion is useful in reducing training load and may be a characteristic of elite players, although whether our findings relate to differences in the playing style, position, or aerobic capacity of player A are unknown. [ABSTRACT FROM AUTHOR]

Background: Older women are considered at risk for hip fracture; fracture rates are highest in the southern region of the United States. The purpose of this study was to develop a predictive model for osteoporotic hip fracture among a national sample of southern women aged 50 years and older.Methods: Subjects were participants in the Third National Health and Nutritional Examination Survey, Phase 1. Data were collected by the National Center for Health Statistics. Predictors examined included age, race, heredity, body mass index, physical activity, smoking status, alcohol use, and dairy product use.Results: The sample consisted of 953 women aged 50 years and older. The predictive model included older age, black race, Hispanic race, and low body mass index.Conclusions: Recommendations emphasize weight gain for underweight women and promotion of healthy body weights for women of all ages. [ABSTRACT FROM AUTHOR]

Background: Hospital investments in care coordination services and innovative delivery models represent an important source for improving care efficiency and population health., Objective: The aim of this study was to explore variation of hospital-initiated care coordination services and participation in Accountable Care Organizations (ACOs) by community characteristics within an organizational theory framework., Methods: Our main data sets included the 2015 American Hospital Association Annual Survey, Survey of Care Systems and Payment, American Community Survey, and Area Health Resource File. Two main outcomes were (a) hospital-reported initiation of care coordination practices (such as chronic disease management, post-hospital discharge continuity of care, and predictive analytics) and (b) participation in ACO models. State fixed-effects models were used to test the association between the adoption of care coordination practices and hospital characteristics, community-level sociodemographic characteristics, and health policies., Results: Hospitals with large bed size, located in urban areas, and/or with high volume of operations were more likely to adopt care coordination practices and participate in the ACO models. Hospitals serving communities with high uninsurance rates and/or poverty rates were significantly less likely to provide care coordination practices. More stringent Community Benefit Laws (CBLs) were positively associated with the implementation of care coordination practices suggesting strong normative impacts of CBLs., Conclusion: Greater hospital-initiated care coordination practices and innovative ACO models were available in well-resourced areas. Policymakers may consider increasing resources for care coordination practices in rural, underserved, and high-poverty-high-uninsured areas to ensure that vulnerable populations can benefit from these services.