Journal ArticleDOI
Behavioral Health Insurance Parity for Federal Employees
Howard H. Goldman,Richard G. Frank,M. Audrey Burnam,Haiden A. Huskamp,M. Susan Ridgely,Sharon-Lise T. Normand,Alexander S. Young,Alexander S. Young,Colleen L. Barry,Vanessa Azzone,Alisa B. Busch,Susan T. Azrin,Garrett Moran,Carolyn Lichtenstein,Margaret Blasinsky +14 more
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TLDR
When coupled with management of care, implementation of parity in insurance benefits for behavioral health care can improve insurance protection without increasing total costs.Abstract:
Background To improve insurance coverage of mental health and substance-abuse services, the Federal Employees Health Benefits (FEHB) Program offered mental health and substance-abuse benefits on a par with general medical benefits beginning in January 2001. The plans were encouraged to manage care. Methods We compared seven FEHB plans from 1999 through 2002 with a matched set of health plans that did not have benefits on a par with mental health and substance-abuse benefits (parity of mental health and substance-abuse benefits). Using a difference-in-differences analysis, we compared the claims patterns of matched pairs of FEHB and control plans by examining the rate of use, total spending, and out-of-pocket spending among users of mental health and substance-abuse services. Results The difference-in-differences analysis indicated that the observed increase in the rate of use of mental health and substance-abuse services after the implementation of the parity policy was due almost entirely to a general tr...read more
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The Impact of Mental Illness Stigma on Seeking and Participating in Mental Health Care
TL;DR: The complex elements of stigma are reviewed in order to understand its impact on participating in care and public policy considerations in seeking to tackle stigma in orderto improve treatment engagement are summarized.
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A Handbook for the Study of Mental Health: Social Contexts, Theories, and Systems
Teresa L. Scheid,Tony N. Brown +1 more
TL;DR: It is tested whether significant differences in mental illness exist in a matched sample of Mental illness and the criminal justice system.
Journal ArticleDOI
Increasing Prevalence of Atrial Fibrillation and Flutter in the United States
TL;DR: The current prevalence of AF and AFL is high and is projected to increase considerably by 2050, and the current and projected increases in the prevalence are greater than predicted by a previous sentinel study and might reflect more than the aging of the population.
Gender and mental health.
Sarah Rosenfield,Dawne M. Mouzon +1 more
TL;DR: Men and women experience different kinds of mental health problems as mentioned in this paper, while women exceed men in internalizing disorders such as depression and anxiety, men exhibit more externalizing disorders, such as substance abuse and antisocial behavior, which are problematic for others.
References
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An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Journal ArticleDOI
Interaction terms in logit and probit models
Chunrong Ai,Edward C. Norton +1 more
TL;DR: In this article, the authors present the correct way to estimate the magnitude and standard errors of the interaction effect in nonlinear models, which is the same way as in this paper.
Posted Content
Estimating Log Models: To Transform or Not to Transform?
TL;DR: This study examines how well the alternative estimators behave econometrically in terms of bias and precision when the data are skewed or have other common data problems (heteroscedasticity, heavy tails, etc).
Journal ArticleDOI
Estimating log models: to transform or not to transform?
Willard G. Manning,John Mullahy +1 more
TL;DR: In this article, the authors examined how well the alternative estimators behave econometrically in terms of bias and precision when the data are skewed or have other common data problems (heteroscedasticity, heavy tails).
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