Description: Review a recently completed research project for a multi-stakeholder data consortium on social determinants of health (SDOH). In this project, claims, external SDOH data, geospatial analysis, and machine learning models were used to examine several questions: How to identify SDOH vulnerabilities? How sensitive are the findings with respect to provider coding pattern variations? How much variability in cost can be explained by SDOH vs. morbidity? What are the key risk drivers revealed by machine learning models? The session will review the methodology and main findings from this project.

Description: This paper examines four and-a-half years of prescription records for an elderly population who have relatively comprehensive out-of-hospital drug coverage under the Pharmaceutical Assistance Contract for the Elderly program in Pennsylvania. The result is a discussion of the determination of non-parametric estimations of the distributions. From Actuarial Research Clearing House 1991, Vol 1.

Description: The presenters will cover the variation in risk adjustment approaches used across state Medicaid programs and compare them to other Federal programs. Additionally, recent developments, such as the use of OCR to extract data from medical charts for risk adjustment, will be discussed.

Description: The presenters will provide insights into fraud and abuse risk in the health insurance industry, including an examination of traditional and predictive modeling techniques for both prevention and detection. Emphasis will be placed on current and emerging risks. Canadian examples and perspectives will be offered, but the applications for attendees to use in practice are non-nation specific.

Description: The Society of Actuaries (“SOA”) Research Institute is the research arm of the SOA, providing objective, data-driven research that brings together tried and true practices and future-focused approaches to address societal challenges and business needs. The Institute provides trusted knowledge, extensive experience and new technologies to help effectively identify, predict and manage risks.

Description: This article discusses the problems in estimating the prevalence of HIV infection.

Description: Join us in this webinar where we explore the intricate relationship between Professional Employer Organizations (PEOs) and insurance, diving into the art of risk management within this industry. Gain a comprehensive understanding of the diverse insurance products offered by PEOs, the positioning of PEOs in the actuarial landscape, and the strategic navigation of regulatory challenges.

Description: This section presents book reviews and summaries of recent publications on a variety of topics.

Description: This is the complete January 2012 issue of Health Watch.

Description: This article discusses the causes of the 1918 influenza pandemic, the reasons it occurred and the likelihood that it could happen again. In addition, the author discussed ways, in general, to model and manage risks that occur infrequently, yet have a significant impact.