Federico Girosi

RAND researchers analyzed the health components of seven post-World War II nation-building efforts conducted after major conflicts-Germany, Japan, Somalia, Haiti, Kosovo, Afghanistan, Iraq-and found that two factors are correlated with successful health outcomes: planning and coordination, and infrastructure and resources.

Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of population death rates. Mortality forecasting is used in a wide variety of academic fields, and for policymaking in global health, social security and retirement planning, and other areas. Federico Girosi and Gary King provide an innovative framework for forecasting age-sex-country-cause-specific variables that makes it possible to incorporate more information than standard approaches. These new methods more generally make it possible to include different explanatory variables in a time-series regression for each cross section while still borrowing strength from one regression to improve the estimation of all. The authors show that many existing Bayesian models with explanatory variables use prior densities that incorrectly formalize prior knowledge, and they show how to avoid these problems. They also explain how to incorporate a great deal of demographic knowledge into models with many fewer adjustable parameters than classic Bayesian approaches, and develop models with Bayesian priors in the presence of partial prior ignorance. By showing how to include more information in statistical models, Demographic Forecasting carries broad statistical implications for social scientists, statisticians, demographers, public-health experts, policymakers, and industry analysts. * Introduces methods to improve forecasts of mortality rates and similar variables * Provides innovative tools for more effective statistical modeling * Makes available free open-source software and replication data * Includes full-color graphics, a complete glossary of symbols, a self-contained math refresher, and more

This book provides the technical details and results of the national-level efficiency savings that would be brought about by using Healthcare Information Technology and the costs the nation would have to incur to realize those savings. It also provides the technical details and results of one component of a study to better understand the role and importance of Electronic Medical Record Systems (EMR-S) in improving health and reducing healthcare costs - the national-level efficiency savings that would be brought about by using Healthcare Information Technology - and the costs the nation would have to incur to realize those savings.