OBJECTIVES/SPECIFIC AIMS: To create a searchable public registry of all Quality Improvement (QI) projects. To incentivize the medical professionals at UF Health to initiate quality improvement projects by reducing startup burden and providing a path to publishing results. To reduce the review effort performed by the internal review board on projects that are quality improvement Versus research. To foster publication of completed quality improvement projects. To assist the UF Health Sebastian Ferrero Office of Clinical Quality & Patient Safety in managing quality improvement across the hospital system. METHODS/STUDY POPULATION: This project used a variant of the spiral software development model and principles from the ADDIE instructional design process for the creation of a registry that is web based. To understand the current registration process and management of quality projects in the UF Health system a needs assessment was performed with the UF Health Sebastian Ferrero Office of Clinical Quality & Patient Safety to gather project requirements. Biweekly meetings were held between the Quality Improvement office and the Clinical and Translational Science – Informatics and Technology teams during the entire project. Our primary goal was to collect just enough information to answer the basic questions of who is doing which QI project, what department are they from, what are the most basic details about the type of project and who is involved. We also wanted to create incentive in the user group to try to find an existing project to join or to commit the details of their proposed new project to a data registry for others to find to reduce the amount of duplicate QI projects. We created a series of design templates for further customization and feature discovery. We then proceed with the development of the registry using a Python web development framework called Django, which is a technology that powers Pinterest and the Washington Post Web sites. The application is broken down into 2 main components (i) data input, where information is collected from clinical staff, Nurses, Pharmacists, Residents, and Doctors on what quality improvement projects they intend to complete and (ii) project registry, where completed or “registered” projects can be viewed and searched publicly. The registry consists of a quality investigator profile that lists contact information, expertise, and areas of interest. A dashboard allows for the creation and review of quality improvement projects. A search function enables certain quality project details to be publicly accessible to encourage collaboration. We developed the Registry Matching Algorithm which is based on the Jaccard similarity coefficient that uses quality project features to find similar quality projects. The algorithm allows for quality investigators to find existing or previous quality improvement projects to encourage collaboration and to reduce repeat projects. We also developed the QIPR Approver Algorithm that guides the investigator through a series of questions that allows an appropriate quality project to get approved to start without the need for human intervention. RESULTS/ANTICIPATED RESULTS: A product of this project is an open source software package that is freely available on GitHub for distribution to other health systems under the Apache 2.0 open source license. Adoption of the Quality Improvement Project Registry and promotion of it to the intended audience are important factors for the success of this registry. Thanks goes to the UW-Madison and their QI/Program Evaluation Self-Certification Tool (https://uwmadison.co1.qualtrics.com/SE/?SID=SV_3lVeNuKe8FhKc73) used as example and inspiration for this project. DISCUSSION/SIGNIFICANCE OF IMPACT: This registry was created to help understand the impact of improved management of quality projects in a hospital system. The ultimate result will be to reduce time to approve quality improvement projects, increase collaboration across the UF Health Hospital system, reduce redundancy of quality improvement projects and translate more projects into publications.

The articles in this symposium reflect on Richard Simeon's article, “Studying Public Policy,” published forty years ago in this journal. In this introduction, we review these articles’ contribution to three themes in “Studying Public Policy”: first, the goal of the study of public policy should be policy analysis and explanation, not policy prescription; second, the analysis of public policy outcomes requires a holistic and contextually situated analytical framework; and third, building theory requires methods of comparative analysis, not single case studies. We also propose items for a future policy studies agenda.

Clinical differentiation of Lewy body disease (LBD) from Alzheimer disease (AD) is still problematic. Many persons with LBD lack the cardinal features of visual hallucinations, fluctuations in cognition, and mild Parkinsonism proposed by McKeith et al. (2005). Some studies suggest that history or presence of depression may help distinguish LBD from AD, but this is confounded because many clinically diagnosed LBD patients have significant co-morbid AD pathology and vice versa (Ranginwala et al., 2008). We aimed to clarify whether history or symptoms of depression differentiate LBD from AD, in autopsy-confirmed patients, excluding patients with mixed AD and LBD pathology.

Abstract. This article examines whether current shifts in government spending on early childhood education and care (ECEC) and maternal employment-promoting policies such as maternity and parental leave reveal a paradigm shift toward a social investment strategy in liberal welfare states. It finds that while governments in liberal welfare states increasingly adhere to the rhetoric of social investment focused on lifelong learning and labour activation, their policies and programs exhibit so much variation in goals, instruments and settings related to the family, maternal employment and the child that it is difficult to claim that any new policy approach has taken hold that is indicative of a social investment “paradigm.” Instead, liberal welfare states appear to be becoming even more liberal—in terms of reliance on markets for delivery of social investment goals—at the same time as spending is increasing.

Résumé. Cet article examine si les changements actuels des dépenses de gouvernement sur la première éducation d'enfance et le soin (ECEC) et les politiques promouvant emploi maternelles comme la maternité et le congé parental révèlent un changement de paradigme vers une stratégie sociale d'investissement dans les Etats-providences libéraux. Il constate que pendant que les gouvernements dans les Etats-providences libéraux adhèrent de plus en plus à la rhétorique d'investissement social s'est concentré sur l'apprentissage de toute une vie et l'activation de la main-d'œuvre, leurs politiques et programmes exposent tant de variation dans les buts, les instruments et les cadres rattachés à la famille, l'emploi maternel et l'enfant qu'il est difficile de réclamer que n'importe quelle nouvelle approche de politique a attrapé qui est indicatif “d'un paradigme” social d'investissement. Au lieu de cela les Etats-providences libéraux ont l'air de devenir encore plus libéraux – du point de vue de la dépendance aux marchés pour la livraison de buts sociaux d'investissement – en même temps comme les dépenses augmentent.

The science of extra-solar planets is one of the most rapidly changing areas of astrophysics and since 1995 the number of planets known has increased by almost two orders of magnitude. A combination of ground-based surveys and dedicated space missions has resulted in 560-plus planets being detected, and over 1200 that await confirmation. NASA's Kepler mission has opened up the possibility of discovering Earth-like planets in the habitable zone around some of the 100,000 stars it is surveying during its 3 to 4-year lifetime. The new ESA's Gaia mission is expected to discover thousands of new planets around stars within 200 parsecs of the Sun. The key challenge now is moving on from discovery, important though that remains, to characterisation: what are these planets actually like, and why are they as they are?

In the past ten years, we have learned how to obtain the first spectra of exoplanets using transit transmission and emission spectroscopy. With the high stability of Spitzer, Hubble, and large ground-based telescopes the spectra of bright close-in massive planets can be obtained and species like water vapour, methane, carbon monoxide and dioxide have been detected. With transit science came the first tangible remote sensing of these planetary bodies and so one can start to extrapolate from what has been learnt from Solar System probes to what one might plan to learn about their faraway siblings. As we learn more about the atmospheres, surfaces and near-surfaces of these remote bodies, we will begin to build up a clearer picture of their construction, history and suitability for life.

The Exoplanet Characterisation Observatory, EChO, will be the first dedicated mission to investigate the physics and chemistry of Exoplanetary Atmospheres. By characterising spectroscopically more bodies in different environments we will take detailed planetology out of the Solar System and into the Galaxy as a whole.

EChO has now been selected by the European Space Agency to be assessed as one of four M3 mission candidates.