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eBook details

• Title: Assessing Health State Preferences and the Decision to Medicate in Overactive Bladder
• Author : Spencer E. Harpe
• Release Date : January 19, 2013
• Genre: Medical,Books,Professional & Technical,
• Pages : * pages
• Size : 15427 KB

Description

Overactive bladder is a condition that affects millions of Americans. While various studies exist to examine the cost-effectiveness of treatment alternatives, very few studies have examined the area of patient preferences. Once symptoms develop many individuals construct their preferences for treatment after considering the quality of life (QOL) effects of OAB and whether they possess prescription drug insurance. The purpose of this study was twofold: to examine the relative importance patients place on prescription drug coverage and QOL and to examine the effects of symptom severity and various demographic characteristics on patient quality of life. The sample taken from a large clinic consisted of 133 patients with self-reported symptoms of OAB. To be included, participants were either male or female and were not taking medications to control their OAB symptoms. Data were obtained via self-administered questionnaire and telephone using trained interviewers. The QOL domains were those identified by the OAB-q instrument developed by Coyne et al.: coping, symptom concern, sleep disturbances, and problems with social interactions. All profile attributes had two levels—high / present or low / not present. Using conjoint methodology, a questionnaire consisting of nine hypothetical profiles was used to elicit preferences. A linear fixed-effects model was used to analyze the results. The following coefficients were found for the five profile attributes: insurance coverage, 34.36; sleep disturbances, 23.69; symptom concern, 19.73; social interaction problems, 19.44; and coping, 15.62. This suggests that prescription insurance coverage is the most important factor patients consider when considering medication therapy to control OAB symptoms. The effects of demographic variables on QOL were examined using a linear regression model. After assembling the data on demographics and symptom severity, a model-building exercise was conducted to maximize the model R-squared value. The final model contained four variables: age, symptom severity, previous medication use, and medical insurance. After adjusting for outlying observations, the final model R-squared was 0.149. Since the concept of QOL is very large and encompasses many areas of an individual’s life, this value was acceptable.

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