Modeling the risk: innovative approaches to understand and quantify the risk of severe FB injury

OBJECTIVES

The entry of a small item into the respiratory or digestive tract is still one of the leading causes of injuries in children up to 14 years old. The aim of the paper is to provide a quantitative risk assessment analysis for identifying consumer product features which contribute to increase the risk of sustaining a severe injury.

METHODS

Data on foreign body injuries were collected in 28 European countries and one Pakistani hospital. A total of 7296 cases were classified according to ICD-9CM 931-935. Information about injuries included age and gender of the injured child, circumstances of the accident and foreign body features. A classification tree was set up in order to analyze the impact of the item features like volume shape and rigidity on the severity of the injury.

RESULTS

Males are involved in severe injuries more often than females. Most severe injuries when the foreign body is localized in the ears were due to objects with volume lesser than 49 mm(3). Volume cut-off is slightly higher for foreign bodies that have been found in the nose (55 mm(3)). Objects with conforming rigidity pose children to higher risk of severe injury.

CONCLUSIONS

The presence and supervision of an adult is crucial in reducing the risk for severe injuries both in pharynx and laryhnx and in mouth.

Regression models for analyzing costs and their determinants in health care: an introductory review

OBJECTIVE

This article aims to describe the various approaches in multivariable modelling of healthcare costs data and to synthesize the respective criticisms as proposed in the literature.

METHODS

We present regression methods suitable for the analysis of healthcare costs and then apply them to an experimental setting in cardiovascular treatment (COSTAMI study) and an observational setting in diabetes hospital care.

RESULTS

We show how methods can produce different results depending on the degree of matching between the underlying assumptions of each method and the specific characteristics of the healthcare problem.

CONCLUSIONS

The matching of healthcare cost models to the analytic objectives and characteristics of the data available to a study requires caution. The study results and interpretation can be heavily dependent on the choice of model with a real risk of spurious results and conclusions.