Description: This article discusses what actuaries see as ideal components of a health care reform package with an emphasis on cost control, efficiency, elimination of fraud and reduction of errors.

Description: This session discussion is about claim processing technology. Its artificial intelligence, medical expert systems, optical scanning and electronic claim submission. From Record of the Society of Actuaries Vol. 15, No. 1.

Description: In the evolving realm of healthcare actuarial practice, value-based contracts are reshaping the landscape. This article explores the pivotal role of AI-enhanced Electronic Medical Records (EMRs) in empowering actuaries to navigate this dynamic sector. Despite challenges in data standardization, AI-enhanced EMRs offer a solution by extracting and standardizing diverse medical records. The article delineates how AI-EMR integration benefits actuaries and provider organizations, enabling more accurate forecasting, earlier shared savings prepayments, and real-time quality metric aggregation. Moreover, it discusses how this fusion addresses historical data limitations, can help project catastrophic claims, and can help identify risk score capture opportunities. Ultimately, it indicates the transformative potential of AI-EMR synergy, positioning actuaries at the forefront of healthcare analytics with unprecedented precision and insight.

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.