Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Prescription drug abuse, in particular prescription opioid abuse is a public health concern. One measurement of the effects of prescription opioids is the number of patients visiting the emergency departments (ED) with opioid-related problems. Knowing more about the patients who visit the ED with opioid-related problems may assist in addressing this problem. This study examined hospital and prescription claims of Texas Medicaid enrollees from 2008 to 2011 to determine whether demographic factors could help predict the opioid prescription history of the ED patients. Age, sex and race/ethnicity were used as demographic predictors. A patient’s prescriptive history was categorized as a non-prescribed user, a short-term user, or a long-term user based on Texas Medicaid prescription claims. Of the 1001 Texas Medicaid enrollees in our dataset who had a claim for an opioid-related ED visit, 622 were classified as non-prescribed users, 65 were short-term users, and 314 were long-term users. Our ordinal logistic regression model was a poor model for predicting prescriptive history. This study does suggest that the number of opioid-related ED visits in the Texas Medicaid population is increasing. The majority of Texas Medicaid enrollees in our study were classified as non-prescribed users. Focused efforts to address the growing problem of opioid-related ED visits cannot be limited to the patients being with claims for opioid prescriptions. / text

Antipsychotic medications are effective in the treatment of psychotic disorders. Monotherapy (MT) with antipsychotics is consistently recommended as the treatment of choice by several guidelines yet antipsychotic polypharmacy (APP) is widespread in clinical practice. The objectives of this study were to evaluate the incidence of APP, identify predictors of APP, and compare adherence, health resource utilization, and costs between patients on MT and APP using prescription and medication claims from Texas Medicaid (2006 to 2011). Patients newly initiated on antipsychotics were followed for 12 months and categorized into the APP (exposure to two or more antipsychotics for a defined time interval) and MT (no evidence of APP during the study period) groups. This sample of patients was used to evaluate incidence and predictors of APP and compare medication adherence and persistence between the MT and APP groups using multiple, logistic, and Cox proportional hazards regressions. Patients in the MT and APP groups were then matched based on their duration of exposure to antipsychotics and all-cause healthcare utilization and costs were compared using logistic and generalized linear models regression (negative binomial, Poisson, and gamma). Regression analyses for patients matched on duration of antipsychotic exposure accounted for the correlation between matched pairs. The incidence of APP was 5.4%. Several demographic, clinical, physician, and prior utilization characteristics were associated with APP. Medication adherence and persistence were better in the APP group. Length of hospital stay and medical, drug, and total costs were higher for the APP group. Sensitivity analyses were conducted for psychiatric-related costs and varied overlap and gap periods. The results for most of the sensitivity analyses were similar to the base case. Patients prescribed APP had higher medical, drug and total costs and also higher healthcare utilization i.e. increased drug costs were not offset by decreased medical costs. Long-term APP raises concern as state Medicaid agencies are allocating their limited resources to this expensive treatment which has very scarce data supporting its use. More effectiveness research on APP is needed to help provide prescription guidance to clinicians for patients who do not respond well to treatment with a single antipsychotic. / text

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Thesis (M. P. A.)--Texas State University-San Marcos, 2006. / "Summer 2006." Includes bibliographical references (leaves 96-99).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references (leaves 259-274). Available also in an electronic version.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1984. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 159-167).

No description available.