Boomers' Retirement Income Prospects

Examines how changing demographics and patterns in lifetime earnings, pension participation, and wealth accumulation among Americans born between 1946 and 1964 will shape baby boomers' economic well-being at age 70

Indexing the Event Calculus with Kd-trees to Monitor Diabetes

Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. A patient affected by a chronic disease can generate large amounts of events. Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitoring) to 288 per day when wearing a continuous glucose monitor (CGM) that samples the blood every 5 minutes for several days. This is a large number of events to monitor for medical doctors, in particular when considering that they may have to take decisions concerning adjusting the treatment, which may impact the life of the patients for a long time. Given the need to analyse such a large stream of data, doctors need a simple approach towards physiological time series that allows them to promptly transfer their knowledge into queries to identify interesting patterns in the data. Achieving this with current technology is not an easy task, as on one hand it cannot be expected that medical doctors have the technical knowledge to query databases and on the other hand these time series include thousands of events, which requires to re-think the way data is indexed. In order to tackle the knowledge representation and efficiency problem, this contribution presents the kd-tree cached event calculus (\ceckd) an event calculus extension for knowledge engineering of temporal rules capable to handle many thousands events produced by a diabetic patient. \ceckd\ is built as a support to a graphical interface to represent monitoring rules for diabetes type 1. In addition, the paper evaluates the \ceckd\ with respect to the cached event calculus (CEC) to show how indexing events using kd-trees improves scalability with respect to the current state of the art.Comment: 24 pages, preliminary results calculated on an implementation of CECKD, precursor to Journal paper being submitted in 2017, with further indexing and results possibilities, put here for reference and chronological purposes to remember how the idea evolve

An Intelligent Data Mining System to Detect Health Care Fraud

The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice

Electronic medical records concepts and data management

Healthcare information (Clinical Data) is associated with every individual, young or old, rich or poor, belonging to any country. Clinical data is very extensive. Everyday some new diseases and new symptoms are being seen and the human race is struggling to find cures. There are many diseases whose diagnosis, symptoms, and possible treatment are known but unfortunately that rare knowledge is not available to every individual in the world. This initiates all the vision behind presenting a paper on EMR/ EHR and its Data Management. The thesis reviews the concept of EMR/ EHR thus explaining its concepts, importance, market need etc. Thesis will also explain privacy and security related to clinical data in electronic format which is a very important as any electronic data is prone to hacks and data loss. To manage and utilize such amount of data, there is need of extensive data management and so the thesis explains the concepts of Datawarehouse, its importance, ETL, Schemas etc. As part of explaining these concepts a mini EMR/EHR Datawarehouse is designed which explains various subject areas possible in any EMR Datawarehouse. Last but not the least, the thesis comments on the Future of EMR/ EHR and the World Vision on this revolutionary change

Developing HL7 CDA-Based Data Warehouse for the Use of Electronic Health Record Data for Secondary Purposes

Background The growing availability of clinical and administrative data collected in electronic health records (EHRs) have led researchers and policy makers to implement data warehouses to improve the reuse of EHR data for secondary purposes. This approach can take advantages from a unique source of information that collects data from providers across multiple organizations. Moreover, the development of a data warehouse benefits from the standards adopted to exchange data provided by heterogeneous systems. Objective This article aims to design and implement a conceptual framework that semiautomatically extracts information collected in Health Level 7 Clinical Document Architecture (CDA) documents stored in an EHR and transforms them to be loaded in a target data warehouse. Results The solution adopted in this article supports the integration of the EHR as an operational data store in a data warehouse infrastructure. Moreover, data structure of EHR clinical documents and the data warehouse modeling schemas are analyzed to define a semiautomatic framework that maps the primitives of the CDA with the concepts of the dimensional model. The case study successfully tests this approach. Conclusion The proposed solution guarantees data quality using structured documents already integrated in a large-scale infrastructure, with a timely updated information flow. It ensures data integrity and consistency and has the advantage to be based on a sample size that covers a broad target population. Moreover, the use of CDAs simplifies the definition of extract, transform, and load tools through the adoption of a conceptual framework that load the information stored in the CDA in the data warehouse

Again-st Abandon. National Report Index

Lo studio e' stato realizzato da Stoa' e Studio Staff nell'ambito del progetto "AGAIN-ST ABANDON Contrastare il fenomeno degli abbandoni, ripensare i linguaggi della consulenza". Il progetto Again-st Abandon, finanziato dal Programma europeo "Leonardo da Vinci", si pone l'obiettivo di contrastare il fenomeno dei drop-out (DO) - quei giovani che interrompono il percorso scolastico e formativo rendendosi invisibili agli operatori del sociale - nell'ottica di un loro reinserimento nei contesti formali di istruzione, formazione ed impiego. Nel paper viene sviluppata un'analisi territoriale dell'area del Comune di Ercolano tesa ad indagare la domanda e l'offerta di servizi di orientamento e formazione, oltre alla visibilita' e all'accessibilita' degli stessi, attraverso l'utilizzo di dati statistici e indicatori di tipo qualitativo