Exploring the use of negative binomial regression modeling for pediatric peripheral intravenous catheterization

A large study conducted at two southeastern US hospitals from October 2007 through October 2008 sought to identify predictive variables for successful intravenous catheter (IV) insertion, a crucial procedure that is potentially difficult and time consuming in young children. The data was collected on a sample of 592 children that received a total of 1,195 attempts to start peripheral IV catheters in the inpatient setting. The outcome here is number of attempts to successful IV placement, for which the underlying data appears to have a negative binomial structure. The goal of this paper is to illustrate the appropriateness of a negative binomial assumption using visuals obtained from PROC SGPLOT and to determine the goodness of fit for a negative binomial model. Negative binomial regression output from PROC GENMOD will be contrasted with traditional ordinary least squares output. Akaike’s Information Criterion (AIC) illustrates that the negative binomial model has a better fit and comparisons are made in the inferences of covariate impact. Many scenarios of negative binomial regression follow from an application to overdispersed Poisson data; however, this project demonstrates a data set that fits well under the traditional ideology and purpose of a negative binomial model.