Modelling correlated healthcare costs with many zeroes : a two-part random effect approach

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review

View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Publication statusPublished - 3 Jul 2012

Conference

TitleInternational Conference on Business and Information
PlaceJapan
CitySapporo
Period3 - 5 July 2012

Abstract

Healthcare costs typically exhibit a substantial proportion of zero values together with very large positive values. For example, healthy people have no costs recorded in a given year whereas certain individuals may incur large medical expenses that increase tremendously by disease severity. Moreover, such semi-continuous data are often collected in hierarchical form and therefore correlated. A flexible two-part modelling approach is proposed to analyze the heterogeneous and correlated cost data. In the binary part, the odds of cost being positive are modelled using a logistic mixed regression model. In the continuous part, the mean cost given that costs have actually been incurred is assessed by a gamma mixed regression model. Random effects are incorporated within the two parts to account for correlation of the observations. Model fitting and inference are performed through the Gaussian quadrature technique, which can be implemented conveniently in statistical packages. The method is applied to evaluate the effectiveness of an occupational safety intervention program using longitudinal compensation claims cost data. The findings have important implications on healthcare administration and financial planning.

Citation Format(s)

Modelling correlated healthcare costs with many zeroes : a two-part random effect approach. / LEE, ANdy, H; HUI, Yer Van; YAU, Kelvin K W.

2012. Paper presented at International Conference on Business and Information, Sapporo, Japan.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review