Outcomes assessment of a pediatric practice guideline

Objective. This study examines the structure, processes, and data necessary to assess the outcome variables, length of stay and total cost, for a pediatric practice guideline. The guideline was developed by a group of physicians and ancillary staff members representing the services that most commonly provide treatment for asthma patients at Texas Children's Hospital, as a means of standardizing care. Outcomes have needed to be assessed to determine the practice guideline's effectiveness.^ Data sources and study design. Data for the study were collected retrospectively from multiple hospital data bases and from inpatient chart reviews. All patients in this quasi-experimental study had a diagnosis of Asthma (ICD-9-CM Code 493.91) at the time of admission.^ The study examined data for 100 patients admitted between September 15, 1995 and November 15, 1995, whose physician had elected to apply the asthma practice guideline at the time of the patient's admission. The study examined data for 66 inpatients admitted between September 15, 1995 and November 15, 1995, whose physician elected not to apply the asthma practice guideline. The principal outcome variables were identified as "Length of Stay" and "Cost".^ Principal findings. The mean length of stay for the group in which the practice guideline was applied was 2.3 days, and 3.1 days for the comparison group, who did not receive care directed by the practice guideline. The difference was statistically significant (p value = 0.008). There was not a demonstrable difference in risk factors, health status, or quality of care between the groups. Although not showing statistical significance in the univariate analysis, private insurance showed a significant difference in the logistic regression model presenting an elevated odds ratio (odds ratio = 2.2 for a hospital stay $\le$2 days to an odds ratio = 4.7 for a hospital stay $\le$3 days) showing that patients with private insurance experienced greater risk of a shorter hospital stay than the patients with public insurance in each of the logistic regression models. Public insurance included; Medicaid, Medicare, and charity cases. Private insurance included; private insurance policies whether group, individual, or managed care. The cost of an admission was significantly less for the group in which the practice guideline was applied, with a mean difference between the two groups of $1307 per patient.^ Conclusion. The implementation and utilization of a pediatric practice guideline for asthma inpatients at Texas Children's Hospital has a significant impact in terms of reducing the total cost of the hospital stay and length of the hospital stay for asthma patients admitted to Texas Children's Hospital. ^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.