Description: You really can have it all: readily available and relevant information derived from consistent and understood data. Getting at the Truth requires a good datawarehouse design and an appropriate business data model. Add a powerful and flexible Web–based analytical interface to get at the data and success in the pursuit of Truth will happen.

Description: There are many factors driving digitalization but a reliable and meaningful data architecture is the basic prerequisite to a successful digitalization strategy.

Description: While medical and pharmacy claims data is a well-established source for healthcare analytics, significant data can be found elsewhere in electronic medical records (EMRs) and in hospital admit, discharge, and transfer (ADT) messages. Increasing availability of bulk EMR data to analyze coupled with more powerful and specialized tools for analyzing it presents an opportunity for actuaries to incorporate these sources in their work. This session will take a look at some of the data available beyond claims in EMRs and HL7 ADT messages, and will discuss case studies, with consideration around structure, ease of use, cleanliness, and tools available for analyzing these data types including natural language processing.

Description: The barrier between humans and machines continues to blur, but curiously, this may have been prediction thousands of years ago in ancient myths. This article looks to how some of the early legends are becoming manifest in modern technology, particularly in the area of elder care. From automation, to humanoid assistants, to mind clones will the age of technology bring a new utopia?

Description: Recent health care reform activity has highlighted the importance of Clinical Integration in improving the quality, safety, efficiency and reimbursement infrastructure of the health care system. This article discusses relevance and implication of regulatory measures, implementation and data issues, and provides an end-to-end example.

Description: The authors envision a data warehouse with information at the policy level or lower, and demonstrate how this data can be used to analyze the sources of earnings. The key to their analysis is the data warehouse, which links each policy, not only to valuation assumptions and results, but also to general ledger accounting amounts and to projections - model output that feeds the financial plan.

Description: This book is all about granularity. The authors envision a data warehouse with information at the policy level or lower .

Description: 1999 SOA Annual Meeting, San Francisco. Presenters examine data warehousing applications primarily of use to actuaries, such as experience studies, profitability analysis, and performance measurement.