Using the theory of planned behavior to examine pharmacists' intention to utilize a prescription drug monitoring program database.

Res Social Adm Pharm

Division of Health Outcomes and Pharmacy Practice, College of Pharmacy, The University of Texas at Austin, 1 University Station A1900, Austin, TX, USA.

Published: November 2014

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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http://dx.doi.org/10.1016/j.sapharm.2013.05.009DOI Listing

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