Assessing the Impact of Patient Characteristics on Genetic Clinical Pathways: A Regression Approach

Abstract

Molecular genetic techniques allow for the diagnosing of hereditary diseases and congenital abnormalities prenatally. A high variability of treatments exists, engendering an inappropriate clinical response, an inefficient use of resources, and the violation of the principle of the equality of treatment for equal needs. The proposed framework is based on modeling clinical pathways that contribute to identifying major causes of variability in treatments justified by the clinical needs’ variability as well as depending on individual characteristics. An electronic data collection method for high-risk pregnant women addressing genetic facilities and laboratories was implemented. The collected data were analyzed retrospectively with two aims. The first is to identify how the whole activity of genetic services can be broken down into different clinical pathways. This was performed by building a flow chart with the help of doctors. The second aim consists of measuring the variability, within and among, the different paths due to individual characteristics. A set of statistical models was developed to determine the impact of the patient characteristics on the clinical pathway and its length. The results show the importance of considering these characteristics together with the clinical information to define the care pathway and the use of resources.

Keywords

• clinical pathways
• regression analysis
• statistical models
• genetic tests
• logistic regression
• pseudo Poisson maximum likelihood