Description: This paper develops a parametric model for health care insurance claims using currently available software to fit parametric models to the data. Model selection is based on the Chi-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper develops a parametric model for health care insurance claims to fit parametric models to the data. Model selection is based on the ChJ-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. A copula function was used to model the bivariate portion of the data. From Actuarial Research Clearing House 1993, VOL. 3.

Description: In this paper several probability models for the random amounts of needed long-term care are explained, and one model is used to provide an alternate premium calculation method for certain long-term care coverages. From Actuarial Research Clearing House 1990, VOL. 2.

Description: Risk adjustment in government regulated health plans has been around for over two decades. Yet the strategies for promoting risk score accuracy haven't varied much during that time. Most health plans, physician groups, and vendors promote chart reviews and/or in-home assessments as the primary vehicle for collecting data not perceived to be present in the routine claims submission and adjudication stream. We know that most organizations trying to coalesce encounter data from multiple sources often fail to ensure that all relevant data is ultimately submitted to CMS or a state Medicaid agency. Crucial data, often with significant financial value, frequently gets lost in the data pipeline, somewhere between the provider's billing system and the health plan and/or its vendors. Because 837-formatted data is difficult to read, it complicates payers and vendor’s abilities to track encounter data so that every service delivered to patients is credited to the applicable risk adjustment formula. It is incumbent upon successful risk-adjusted entities to be able to track encounter data, identify processes and/or vendors which may be mangling or losing data, in order to ensure that risk scores are sufficiently accurate to be compliant with plan sponsor requirements and to ensure appropriate revenue to the health plan or provider group.

Description: This paper analyzes the U. S. Treasury monthly interest rates from 1953 to 1992, and the daily rates from 1981 to 1992 for various forms of chaotic behavior. The primary analysis was in determining the Burst Exponent by the use of Rescaled Range Analysis. This paper also discusses other possible uses of Fractional Brownian Motion in Finance Theory, Macroeconomics, and Actuarial Science. From Actuarial Research Clearing House 1994 VOL. 1.

Description: This brief article describes an actuarial model of continuing care retirement communities [CCRC] that was developed. The model uses a set of multiple-decrement, multi-life, multi-status functions to describe the population of a CCRC.

Description: This is the abstract for the paper entitled 'Pricing Long Term Insurance Contracts.' This paper considers several models describing the changes in the needs of the insured for care over time. From Actuarial Research Clearing House 1994, VOL. 1.

Description: This model arose from a project to evaluate the cost of a health care access' program to provide comprehensive medical care to uninsureds in Minnesota, for the Minnesota Health Care Access Commission. The project was to provide estimates of the impact on per-person and aggregate costs for various participation percentages in the access program. In order to evaluate those costs, the antiselection model described in this was developed. Of note, this was the ACTUARIAL EDUCATION AND RESEARCH FUND 1991 PRACTITIONERS AWARD WINNER. From Actuarial Research Clearing House 1991, VOL. 2.

Description: 1996 Valuation Actuary Symposium Proceedings, Session 11, discusses health financial projections and projection modeling in general.