Contracting for Coordination of Behavioral Health Services in Privatized Child Welfare and Medicaid Managed Care

This study examined coordination between privatized child welfare initiatives and Medicaid managed care systems for the delivery of behavioral health care services for children and families in the child welfare system. Specific objectives: 1) to assess how states expectations as embodied in their contract documents are actually happening during program implementation; and 2) to identify promising approaches for delivery of coordinated behavioral health care services and contracting that can be shared with other stakeholders. The goal was to highlight the real world experiences and lessons learned that others may draw upon when designing and implementing similar contracts for systems of care

Marriott International: A Managerial Strategic Audit

A strategic management audit of the public firm, Marriott International, was conducted to identify various factors and managerial strategies that affect Marriott and the global hotels and tourism industry. At the industry level, we conducted a PESTEL and Five Forces analysis, researched the competitive landscape, and assessed the total value potential. We found that the industry experienced a major decline during the COVID-19 pandemic but saw recovery as international travel opened up again. On the company level, we conducted an internal analysis, identified Marriott’s management structure, and identified the firm’s structure and strategies through a SWOT analysis and other relevant research. We assessed the makeup leadership team and Board of Directors and how it has influenced the corporate governance, organizational structures, and controls of the firm. Finally, we analyzed firm structure by looking at Marriott’s business-level, corporate-level, and merger and acquisition strategies. Marriott’s successful mergers and acquisitions have allowed it to grow to be the largest firm in the industry. By employing a broad differentiation strategy with its 30-brand portfolio, it has been able to occupy nearly every segment of the market and maintain its competitive position through its consistent customer service, brand recognition, and customer loyalty through its Marriott Bonvoy program. The Marriott family has maintained influence through their presence on the Board and Executive team, which can be seen through recent voting decisions and compensation

Using hysteresis analysis of high-resolution water quality monitoring data, including uncertainty, to infer controls on nutrient and sediment transfer in catchments

A large proportion of nutrients and sediment is mobilised in catchments during storm events. Therefore understanding a catchment's hydrological behaviour during storms and how this acts to mobilise and transport nutrients and sediment to nearby watercourses is extremely important for effective catchment management. The expansion of available in-situ sensors is allowing a wider range of water quality parameters to be monitored and at higher temporal resolution, meaning that the investigation of hydrochemical behaviours during storms is increasingly feasible. Studying the relationship between discharge and water quality parameters in storm events can provide a valuable research tool to infer the likely source areas and flow pathways contributing to nutrient and sediment transport. Therefore, this paper uses 2years of high temporal resolution (15/30min) discharge and water quality (nitrate-N, total phosphorus (TP) and turbidity) data to examine hysteretic behaviour during storm events in two contrasting catchments, in the Hampshire Avon catchment, UK. This paper provides one of the first examples of a study which comprehensively examines storm behaviours for up to 76 storm events and three water quality parameters. It also examines the observational uncertainties using a non-parametric approach. A range of metrics was used, such as loop direction, loop area and a hysteresis index (HI) to characterise and quantify the storm behaviour. With two years of high resolution information it was possible to see how transport mechanisms varied between parameters and through time. This study has also clearly shown the different transport regimes operating between a groundwater dominated chalk catchment versus a surface-water dominated clay catchment. This information, set within an uncertainty framework, means that confidence can be derived that the patterns and relationships thus identified are statistically robust. These insights can thus be used to provide information regarding transport processes and biogeochemical processing within river catchments

What's good for the goose is good for the gander: Implementing the SIOP model into an urban elementary classroom of African American students

Research points to many factors that contribute to the achievement gap between white and minority students however; one important issue that is often overlooked is the academic language status of the student. Knowing that lack of familiarity and proficiency in academic English severely limits an individual’s chances at academic success (Mace- Matluck, Alexander-Kasparik, & Queen, 1998), purposefully teaching the skills associated with academic English proficiency is of the utmost importance. While the use of the Sheltered Instruction Observation Protocol (SIOP) has shown to positively impact the academic English language proficiency levels of English language learners, little research exists as to its impact on the proficiency levels of urban students who are not fully proficient in academic English. Employing an action research methodology, this study examined the journey experienced by a teacher and her students when the Sheltered Instruction Observation Protocol (SIOP) was implemented into an urban classroom of academic English language learners (AELL). The main findings of this qualitative study are: 1) The implementation of the SIOP model in any classroom should be accompanied by thorough training and on- going support; 2) The SIOP model has a positive effect on student interactions in the classroom; 3) For the implementation of the SIOP model to be successful issues of ‘control’ must be addressed; 4) There was a positive impact of the SIOP model on the academic language skills of students

Analysis of CareFirst\u27s Performance as a Charitable Not-for-Profit Health Insurance Company in the National Capital Area

The George Washington University School of Public Health and Health Services ( GWU ) and the Georgetown University Institute for Health Care Research and Policy ( GU )conducted this analysis on behalf of the DC Appleseed Center for Law and Justice in order to examine whether, in its operations and business practices, CareFirst BlueCross BlueShield ( CareFirst ) appears to be fulfilling its chartered mission for the National Capital Area. The study began as an analysis of the coverage and access implications for the region of a proposal made by CareFirst and WellPoint Health Networks, Inc. ( WellPoint ) to convert CareFirst to for-profit status and permit its acquisition by WellPoint for a price of $1.3 billion. Maryland\u27s Commissioner of Insurance rejected the proposal in March 2003. Upon the request of CareFirst and WellPoint, the insurance commissioners in the District of Columbia and Delaware suspended their review of the transaction

Evaluating survey methods for bat roost detection in ecological impact assessment

International audienceThe disturbance, damage and destruction of roosts are key drivers of bat population declines worldwide. In countries where bats are protected by law, bat roost surveys are often required to inform ecological impact assessments. Yet, evidence-based information on survey methodology to detect bat roosts is crucially lacking, and failing to detect a roost can lead to serious errors during decision-making processes. Here, we assess the efficacy of bat roost surveys in buildings as implemented in the UK. These consist of a daytime inspection of buildings, followed by a series of acoustic surveys at dusk/dawn if during the daytime inspection evidence of bats is found, or if the absence of bats cannot be verified. We reviewed 155 ecological consultants’ reports to (1) compare survey outcome between daytime inspection and acoustic surveys and (2) determine the minimum sampling effort required during acoustic surveys to be confident that no bats are roosting within a building. We focused on two genera of bats most frequently found in buildings in Europe – Pipistrellus (crevice roosting species with high-intensity echolocation calls that can be easily detected by ultrasound detectors) and Plecotus (species that roost in open spaces and which emit faint echolocation calls that are difficult to detect). Daytime inspections were efficient in detecting open-roosting species such as Plecotus species but were likely to miss the presence of crevice-dwelling ones (here Pipistrellus species) which may lead to erroneous conclusions if no acoustic surveys are subsequently prescribed to confirm their absence. A minimum of three and four acoustic surveys are required to be 95% confident that a building does not host a roost of Pipistrellus species and Plecotus species, respectively, thus exceeding current recommendations. Overall, we demonstrated that reports submitted as part of an ecological impact assessment provide suitable data to test and improve survey methods

Exploring Voice as Integration: A Direction for Assessing Student Work in Learning Communities with Composition

Kennesaw State University’s team of interdisciplinary scholars qualitatively assessed student learning within theme-based learning communities to determine whether content from one discipline was evident in student work produced within another discipline. Faculty concluded that they were likely expecting more disciplinary integration than first-semester college students were capable of providing, and that they were likely not asking for the integration they were expecting. By examining student work as evidence, the researchers became more acutely aware of the assignment instructions, prompting them to work more closely with colleagues in their future learning communities to develop interdisciplinary assignments with explicit expectations for integration

BioVerbNet: a large semantic-syntactic classification of verbs in biomedicine.

BackgroundRecent advances in representation learning have enabled large strides in natural language understanding; However, verbal reasoning remains a challenge for state-of-the-art systems. External sources of structured, expert-curated verb-related knowledge have been shown to boost model performance in different Natural Language Processing (NLP) tasks where accurate handling of verb meaning and behaviour is critical. The costliness and time required for manual lexicon construction has been a major obstacle to porting the benefits of such resources to NLP in specialised domains, such as biomedicine. To address this issue, we combine a neural classification method with expert annotation to create BioVerbNet. This new resource comprises 693 verbs assigned to 22 top-level and 117 fine-grained semantic-syntactic verb classes. We make this resource available complete with semantic roles and VerbNet-style syntactic frames.ResultsWe demonstrate the utility of the new resource in boosting model performance in document- and sentence-level classification in biomedicine. We apply an established retrofitting method to harness the verb class membership knowledge from BioVerbNet and transform a pretrained word embedding space by pulling together verbs belonging to the same semantic-syntactic class. The BioVerbNet knowledge-aware embeddings surpass the non-specialised baseline by a significant margin on both tasks.ConclusionThis work introduces the first large, annotated semantic-syntactic classification of biomedical verbs, providing a detailed account of the annotation process, the key differences in verb behaviour between the general and biomedical domain, and the design choices made to accurately capture the meaning and properties of verbs used in biomedical texts. The demonstrated benefits of leveraging BioVerbNet in text classification suggest the resource could help systems better tackle challenging NLP tasks in biomedicine