Marc L Fleming1, Jamie C Barner2, Carolyn M Brown2, Marvin D Shepherd2, Scott Strassels2, Suzanne Novak2. 1. Department of Clinical Sciences and Administration, College of Pharmacy, University of Houston, 1441 Moursund St., Houston, TX 77030, USA. Electronic address: MLFlemi2@central.uh.edu. 2. Division of Health Outcomes and Pharmacy Practice, College of Pharmacy, The University of Texas at Austin, 1 University Station A1900, Austin, TX, USA.
Abstract
BACKGROUND: Prescription drug monitoring programs (PDMPs) are state-operated electronic databases that contain patients' controlled drug histories. Most states provide these data to pharmacists via online web portals to combat prescription drug abuse and diversion. OBJECTIVES: The objectives of this study were to: 1) explore the theory of planned behavior's (TPB) utility in predicting Texas pharmacists' intention to utilize an online accessible PDMP; 2) to determine the contribution of each construct, attitude (A), subjective norm (SN) and perceived behavioral control (PBC) in predicting pharmacists' intention; and 3) test whether the addition of perceived obligation (PO) is significantly related to pharmacists' intention. METHODS: A cross-sectional, 36-item questionnaire was developed from focus groups and literature of pharmacists' views regarding prescription drug abuse. A total of 998 practicing Texas community pharmacists were surveyed to collect data on their intention to utilize a PDMP database. Descriptive statistics, multivariate and hierarchical logistic regression analyses were used to address the study objectives. RESULTS: The response rate was 26.2% (261/998). TPB constructs were significant predictors of pharmacists' high intention to utilize the PDMP. Pharmacists with positive attitudes were almost twice as likely to have high intention (odds ratio [OR] = 1.8, 95% confidence interval [CI] = 1.2-2.8). SN was the strongest predictor of pharmacists' high intention (OR = 2.2, 95% CI = 1.4-3.3). Pharmacists with high PBC were also twice as likely to have high intention (OR = 1.9, 95% CI = 1.2-3.0). Additionally, pharmacists' PO contributed to the prediction of high intention (OR = 1.8, 95% CI = 1.0-3.1) above that explained by the TPB model constructs (X(2) = 4.14, P < 0.05). CONCLUSIONS: TPB with the addition of PO was useful in predicting pharmacists' high intention to utilize a PDMP database. Interventions that address pharmacists' A, SN, PBC, and PO may be valuable to increase pharmacists' high intention. Pharmacists' utilization of PDMPs may lead to a decrease in the morbidity and mortality associated with prescription drug abuse. Future studies that assess whether intention to use PDMPs translates to actual usage are needed to strengthen these findings.
BACKGROUND: Prescription drug monitoring programs (PDMPs) are state-operated electronic databases that contain patients' controlled drug histories. Most states provide these data to pharmacists via online web portals to combat prescription drug abuse and diversion. OBJECTIVES: The objectives of this study were to: 1) explore the theory of planned behavior's (TPB) utility in predicting Texas pharmacists' intention to utilize an online accessible PDMP; 2) to determine the contribution of each construct, attitude (A), subjective norm (SN) and perceived behavioral control (PBC) in predicting pharmacists' intention; and 3) test whether the addition of perceived obligation (PO) is significantly related to pharmacists' intention. METHODS: A cross-sectional, 36-item questionnaire was developed from focus groups and literature of pharmacists' views regarding prescription drug abuse. A total of 998 practicing Texas community pharmacists were surveyed to collect data on their intention to utilize a PDMP database. Descriptive statistics, multivariate and hierarchical logistic regression analyses were used to address the study objectives. RESULTS: The response rate was 26.2% (261/998). TPB constructs were significant predictors of pharmacists' high intention to utilize the PDMP. Pharmacists with positive attitudes were almost twice as likely to have high intention (odds ratio [OR] = 1.8, 95% confidence interval [CI] = 1.2-2.8). SN was the strongest predictor of pharmacists' high intention (OR = 2.2, 95% CI = 1.4-3.3). Pharmacists with high PBC were also twice as likely to have high intention (OR = 1.9, 95% CI = 1.2-3.0). Additionally, pharmacists' PO contributed to the prediction of high intention (OR = 1.8, 95% CI = 1.0-3.1) above that explained by the TPB model constructs (X(2) = 4.14, P < 0.05). CONCLUSIONS: TPB with the addition of PO was useful in predicting pharmacists' high intention to utilize a PDMP database. Interventions that address pharmacists' A, SN, PBC, and PO may be valuable to increase pharmacists' high intention. Pharmacists' utilization of PDMPs may lead to a decrease in the morbidity and mortality associated with prescription drug abuse. Future studies that assess whether intention to use PDMPs translates to actual usage are needed to strengthen these findings.
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