Patients with cancer who receive bone marrow transplants (BMT) are at increased risk for central line-associated blood stream infections (CLABSI), a serious complication leading to increased costs, length of stay, and even death. Recognition of an increased CLABSI rate at one BMT unit in the southwestern United States prompted development of an evidence-based staff development education program to improve nurses’ knowledge of central line maintenance and CLABSI prevention practices. Guided by Lewin change theory, the program was developed based on a nurse-led analysis and synthesis of the evidence, and a formative evaluation of the educational program conducted by a 3-member expert panel made up of the BMT director, a BMT clinical nurse specialist and vascular access team member. The review confirmed the lack of standardized evidence-based guidelines for central venous catheter care, that any patient who has a central line is at risk for CLABSI, and BMT patients are at particular risk due to frequency of catheter manipulation. Findings reinforced the need for the recommendations to educate nurses in BMT settings on evidence-based central line practices, evaluate knowledge gained, and audit practice techniques post education. The social change implication of this DNP project will be the potential decrease in healthcare costs, length of stay, and mortality associated with central line infections when nursing staff are provided an educational program that aims to improve their knowledge and skills of evidence-based central line care and CLABSI prevention practices.

Dans la première partie de cette thèse, nous considérons plusieurs problèmes d'estimation de paramètre de dimension finie pour les séquences de Markov dans l'asymptotique des grands échantillons. Le comportement asymptotique des estimateurs bayésiens et les estimateurs obtenus par la méthode des moments sont décrits. Nous montrons que sous les conditions de régularité ces estimateurs sont consistants et asymptotiquement normaux et que l'estimateur bayésien est asymptotiquement efficace. Les estimateur-processus du maximum de vraisemblance un-pas et deux-pas sont étudiés. Ces estimateurs nous permettent de construire des estimateurs asymptotiquement efficaces sur la base de certainsestimateurs préliminaires, par exemple, les estimateurs obtenus par la méthode des moments ou l'estimateur deBayes et la structure de l'estimateur du maximum de vraisemblance un-pas. Nous proposons notamment des processus autorégressifs non linéaires comme exemple et nous illustrons les propriétés de ces estimateurs à l'aide de simulations numériques. Dans la deuxième partie, nous donnons les applications de processus de Markov en économie de la santé. Nous comparons les modèles de Markov homogènes et non-homogènes pour l'analyse coût-efficacité de l'utilisation depansements transparents contenant un gel de gluconate de chlorhexidine par rapport aux pansements transparents standard. Le pansement antimicrobien protège les accès vasculaire centrale et réduit le risque de bactériémies liées aux cathéters. L'impact de l'approche de modélisation sur la décision d'adopter des pansements antimicrobiens pour les patients gravement malades est discuté. / In the first part of this dissertation we consider several problems of finite-dimensional parameter estimation for Markov sequences in the asymptotics of large samples. The asymptotic behavior of the Bayesian estimators and the estimators of the method of moments are described. It is shown that under regularity conditions these estimators are consistent and asymptotically normal. We show that the Bayesian estimator is asymptotically efficient. The one-step and two-step maximum likelihood estimator-processes are studied. These estimators allow us to construct the asymptotically efficient estimators based on some preliminary estimators, say, the estimators of the method of moments or Bayes estimator and the one-step maximum likelihood estimator structure. We propose particular non-linear autoregressive processes as examples and we illustrate the properties of these estimators with the help of numerical simulations. In the second part we give theapplications of Markov processes in health economics. We compare homogeneous and non-homogeneous Markov models for cost-effectiveness analysis of routine use of transparent dressings containing a chlorhexidine gluconate gel pad versus standard transparent dressings. The antimicrobial dressing protects central vascular accesses reducing the risk of catheter-related bloodstream infections. The impact of the modeling approach on the decision of adopting antimicrobialdressings for critically-ill patients is discussed.