Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending

Out-of-pocket medical spending for care of chronic conditions.

We examined out-of-pocket medical spending by persons with and without chronic conditions using data from the 1996 Medical Expenditure Panel Survey (MEPS). Our results show that mean out-of-pocket spending increased with the number of chronic conditions. The level of this spending also varied by age and insurance coverage, among other characteristics. Out-of-pocket spending for prescription dru...

National medical care spending.

Machine learning and spending patterns

The aim of this study is to research the possibility of using customer transactional data to identify spending patterns among individuals, that in turn can be used to assess creditworthiness. Two different approaches to unsupervised clustering are used and compared in the study, one being K-means and the other an hierarchical approach. The features used in both clustering techniques are extract...

Hospitalization for primary care susceptible conditions, health spending and Family Health Strategy: an analysis of trends.

The goal of this study was to analyze the trend over time of hospitalizations due to conditions susceptible to primary healthcare (HCSPC), and how it relates to healthcare spending and Family Health Strategy (FHS) coverage in the city of São Leopoldo, Rio Grande do Sul State, Brazil, between 2003 and 2012. This is an ecological, time-trend study. We used secondary data available in the Unified ...

Household spending on health care.

OBJECTIVES This article examines changes in household spending on health care between 1978 and 1998. It also provides a detailed look at household spending on health care in 1998. DATA SOURCES Data on household spending are from Statistics Canada's Family Expenditure Survey for survey years between 1978 and 1996, and from the annual Survey of Household Spending for 1997 and 1998. ANALYTICAL...