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This revised and expanded third edition text utilizes a public health framework and the latest epidemiological, treatment, and service systems research to promote a comprehensive understanding of the organization, financing, and delivery of mental health and substance abuse services in the United States. Written by national experts in the field, this timely work will provide policymakers, administrators, clinicians, and public health and behavioral health graduate students with the knowledge base needed to manage and transform mental health service systems, both nationally and locally. The boo

The government often uses the Federal Employees Health Benefits (FEHB) Program as a model for both public and private health policy choices. In 2001, the U.S. Office of Personnel Management (OPM) implemented full parity, requiring that FEHB carriers offer mental health and substance abuse benefits equal to general medical benefits. OPM instructed carriers to alter their benefit design but permitted them to determine whether they would manage care and what structures or processes they would use. This article reports on the experience of 156 carriers and the government-wide BlueCross and BlueShield Service Benefit Plan. Carriers dropped cost-restraining benefit limits. A smaller percentage also changed the management of the benefit, but these changes affected the care of many enrollees, making the overall parity effect noteworthy.

Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020). ; This research has been supported by the Spanish National Plan for Scientific and Technical Research and Innovation (project PID2019-111481RB-I00 and María de Maeztu excellence programme projects MdM-2017-0765 and MdM-2017-0714), FCT MCTES financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020), and the Basque Government BERC 2018–2021 programme. ; Peer reviewed

Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages).We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020). ; This research has been supported by the Spanish National Plan for Scientific and Technical Research and Innovation (project PID2019-111481RB-I00 and María de Maeztu excellence programme projects MdM-2017-0765 and MdM-2017-0714), FCT MCTES financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020), and the Basque Government BERC 2018–2021 programme