How to justify your survival curve extrapolation methodology

Clinical trials are typically of (relatively) short duration, but innovative treatments may impact patient survival over multiple years. Health economists and outcomes researchers often are faced with the challenge of extrapolating clinical trial survival curves to estimate long-term survival gains for the typical patient. These estimates may be done parameterically (e.g., exponential, Weibull, Gompertz, log-logistic,…

Who pays for health care? Who uses it?

Ultimately, individuals and households pay for health care. Whether payments are made directly to providers, via taxes or through commercial insurance, households are the sole source of health care financing. Further, all treatments are ultimately provided on behalf of individuals and households. A key question, however, is which types of individuals pay more for health…

Survival distributions in R

My former colleague Devin Incerti has a nice summary of how to implement survival function estimation in R. Not only does he mathematically describe the probability density function (PDF), cumulative density function (CDF), and hazard rates for 8 commonly used parametric survival curves [see table below], he also describes how to implement these using the…

Which inflation index should I use?

Many studies use data on health care costs from multiple time periods.  To make costs comparable over time, researchers often use an inflation index to translate previous years costs to current dollars.  The first question is, what inflation indices are available to make this adjustment.  A paper by Dunn et al. (2018) reviews the potential…