Useful Data Files for Simulation Modelling

In recent years, researchers have created a number of complex simulation models to estimate future trends and the impacts of policy changes.  Some of the more prominant models include: RAND Comprehensive Assessment of Reform Efforts (COMPARE) CBO’s Health Insurance Simulation Model (HISim) Urban Institute’s Health Insurance Reform Simulation Model (HIRSM), Future Elderly Model (FEM) These…

Increased prescription drug use reduces spending on medical services

Increased use of prescription drugs could either increase or decrease spending on medical services.  On the one hand, increased use of pharmaceuticals could decrease hospitalizations and ER visits if pharmaceuticals are able to help patients control chronic conditions and prevent the onset of incidents requiring acute care.  On the other hand, increased use of pharmaceuticals…

Medicare Spending Growth Rates: 1994-2009

What is driving Medicare spending growth? According to a recent health affairs paper by Amitabh Chandra, Maurice A. Dalton, and Jonathan Holme (2013), the answer is post acute care. The authors use Medicare claims (5 percent MedPAR sample) to examine changes in Meidcare spending between 1994 and 2009. The authors find that post-acute spending has…

Model Fit for a Logistic Regression

How do you know if your model fits the data well?  When applying an OLS regression, the standard metric is the R-squared (i.e., R2).   If you have a dependent variable that is binary, however, most researchers prefer a logistic regression.  If you choose a logistic rather than an OLS approach, however, how do you know…