THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

The evolution and assessment of pharmaceutical care: Structure, processes, and outcomes

The evolution of pharmaceutical care is identified through a complete review of the literature published in the American Journal of Health-System Pharmacy, the sole comprehensive publication of institutional pharmacy practice. The evolution is categorized according to characteristics of structure (organizational structure, the role of the pharmacist), process (drug delivery systems, formulary management, acquiring drug products, methods to impact drug therapy decisions), and outcomes (cost of drug delivery, cost of drug acquisition and use, improved safety, improved health outcomes) recorded from the 1950s through the 1990s. While significant progress has been made in implementing basic drug distribution systems, levels of pharmacy involvement with direct patient care is still limited.^ A new practice framework suggests enhanced direct patient care involvement through increase in the efficiency and effectiveness of traditional pharmacy services. Recommendations advance internal and external organizational structure relationships that position pharmacists to fully use their unique skills and knowledge to impact drug therapy decisions and outcomes. Specific strategies facilitate expansion of the breadth and scope of each process component in order to expand the depth of integration of pharmacy and pharmaceutical care within the broad healthcare environment. Economic evaluation methods formally evaluate the impact of both operational and clinical interventions.^ Outcome measurements include specific recommendations and methods to increase efficiency of drug acquisition, emphasizing pharmacists' roles that impact physician prescribing decisions. Effectiveness measures include those that improve safety of drug distribution systems, decrease the potential of adverse drug therapy events, and demonstrate that pharmaceutical care can significantly contribute to improvement in overall health status.^ The implementation of the new framework is modeled on a case study at the M.D. Anderson Cancer Center. The implementation of several new drug distribution methods facilitated the redeployment of personnel from distributive functions to direct patient care activities with significant personnel and drug cost reduction. A cost-benefit analysis illustrates that framework process enhancements produced a benefit-to-cost ratio of 7.9. In addition, measures of effectiveness demonstrated significant levels of safety and enhanced drug therapy outcomes. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Targeting Special Populations for Family Preservation: The Influence of Worker Competence and Organizational Culture

Today there are approximately 581,000 children in the United States foster care system. Children of color, one special population group, are disproportionately represented in the foster care system. Family preservation, a program that aims to improve family functioning and thus decrease the need for foster care, has been examined closely. Some researchers believe that family preservation programs have failed partly due to practitioners' inability to target appropriate families (Feldman, 1990; Schuerman, Rzepnicki & Littell, 1994). Additionally, research confirms that children of color are not the target of family preservation services (Denby, Curtis, & Alford, 1998). Improvements in the effectiveness of family preservation will require many types of reform both internal and external to the program. Among the types of internal reform needed is accurate "targeting of services. " Given the overrepresentation of children of color in the foster care system, this group must be among those who are targeted for services. The results of a national survey of 254 family preservation workers reveal a "profile" of the worker who is likely to target special populations, including children of color, for family preservation services. A case is made for service improvements and training to facilitate the "profiled" workers' competencies.