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3.
Res Social Adm Pharm ; 7(4): 359-68, 2011 Dec.
Article in English | MEDLINE | ID: mdl-21530417

ABSTRACT

BACKGROUND: Clinical decision support (CDS), such as drug-drug interaction (DDI) and drug-allergy checking, has been used in pharmacy information systems for several decades; however, there has been limited research on CDS use by practicing pharmacists. OBJECTIVE: The purpose of this study was to document pharmacists' awareness of DDI and other medication-related CDS features available within pharmacy information systems. METHODS: Researchers conducted on-site interviews with pharmacists throughout the state of Arizona from December 2008 to November 2009 regarding their pharmacy information systems features. Pharmacists were asked to provide information about DDI and other medication-related decision support features of the pharmacy software at their practice site. Descriptive statistics were used to summarize interview responses. RESULTS: Sixty-one pharmacists from a variety of practice settings completed the interview. All respondents indicated that their pharmacy system provided drug-allergy and DDI alerts. Approximately 60% of the pharmacists reported that their DDI decision support systems included recommendations for managing drug interactions. Two-thirds of respondents reported that their pharmacy's computer system permitted the addition of medications from other pharmacies and/or over-the-counter products to a patient's profile. Approximately 40% of the pharmacists reported that some drugs entered into the pharmacy computer system were not included in (or linked to) the electronic DDI checking. Most pharmacists indicated the presence of other medication-related decision support features, such as drug-disease (78%), drug-age precautions (67%), and inappropriate dosage alerts (79%). However, fewer pharmacists reported more advanced functionality, such as laboratory recommendations (34%) and pediatric dosing (39%). CONCLUSION: Overall, pharmacists' awareness regarding the many decision support functionalities of their systems was limited. Based on the study findings, it appears that there are a number of limitations associated with currently available pharmacy decision support software. Further research is needed to formally evaluate pharmacist knowledge of pharmacy decision support software functionality. More formal training about software capabilities coupled with the addition of more advanced decision support features has the potential to improve pharmacists' use of these systems to make better clinical decisions and avoid preventable errors.


Subject(s)
Clinical Pharmacy Information Systems , Decision Support Systems, Clinical , Pharmaceutical Services/organization & administration , Pharmacists/statistics & numerical data , Arizona , Drug Hypersensitivity/prevention & control , Drug Interactions , Health Care Surveys , Health Knowledge, Attitudes, Practice , Humans , Medication Errors/prevention & control , Pilot Projects , Software
4.
J Am Pharm Assoc (2003) ; 51(3): 418-24, 2011.
Article in English | MEDLINE | ID: mdl-21555296

ABSTRACT

OBJECTIVES: To assess the performance of pharmacy clinical decision support (CDS) systems for drug-drug interaction (DDI) detection and to identify approaches for improving the ability to recognize important DDIs. PRACTICE DESCRIPTION: Pharmacists rely on CDS systems to assist in the identification of DDIs, and research suggests that these systems perform suboptimally. The software evaluation tool described here may be used in all pharmacy settings that use electronic decision support to detect potential DDIs, including large and small community chain pharmacies, community independent pharmacies, hospital pharmacies, and governmental facility pharmacies. PRACTICE INNOVATION: A tool is provided to determine the ability of pharmacy CDS systems to identify established DDIs. It can be adapted to evaluate potential DDIs that reflect local practice patterns and patient safety priorities. Beyond assessing software performance, going through the evaluation processes creates the opportunity to evaluate inadequacies in policies, procedures, workflow, and training of all pharmacy staff relating to pharmacy information systems and DDIs. CONCLUSION: The DDI evaluation tool can be used to assess pharmacy information systems' ability to recognize relevant DDIs. Suggestions for improvement include determining whether the software allows for customization, creating standard policies for handling specific interactions, and ensuring that drug knowledge database updates occur frequently.


Subject(s)
Clinical Pharmacy Information Systems , Decision Support Systems, Clinical , Drug Interactions , Humans , Medication Errors/prevention & control , Pharmaceutical Services/organization & administration , Pharmacists/organization & administration , Software Validation
5.
J Am Med Inform Assoc ; 18(1): 32-7, 2011.
Article in English | MEDLINE | ID: mdl-21131607

ABSTRACT

OBJECTIVE: Pharmacy clinical decision-support (CDS) software that contains drug-drug interaction (DDI) information may augment pharmacists' ability to detect clinically significant interactions. However, studies indicate these systems may miss some important interactions. The purpose of this study was to assess the performance of pharmacy CDS programs to detect clinically important DDIs. DESIGN: Researchers made on-site visits to 64 participating Arizona pharmacies between December 2008 and November 2009 to analyze the ability of pharmacy information systems and associated CDS to detect DDIs. Software evaluation was conducted to determine whether DDI alerts arose from prescription orders entered into the pharmacy computer systems for a standardized fictitious patient. The fictitious patient's orders consisted of 18 different medications including 19 drug pairs-13 of which were clinically significant DDIs, and six were non-interacting drug pairs. MEASUREMENTS: The sensitivity, specificity, positive predictive value, negative predictive value, and percentage of correct responses were measured for each of the pharmacy CDS systems. RESULTS: Only 18 (28%) of the 64 pharmacies correctly identified eligible interactions and non-interactions. The median percentage of correct DDI responses was 89% (range 47-100%) for participating pharmacies. The median sensitivity to detect well-established interactions was 0.85 (range 0.23-1.0); median specificity was 1.0 (range 0.83-1.0); median positive predictive value was 1.0 (range 0.88-1.0); and median negative predictive value was 0.75 (range 0.38-1.0). CONCLUSIONS: These study results indicate that many pharmacy clinical decision-support systems perform less than optimally with respect to identifying well-known, clinically relevant interactions. Comprehensive system improvements regarding the manner in which pharmacy information systems identify potential DDIs are warranted.


Subject(s)
Clinical Pharmacy Information Systems , Decision Support Systems, Clinical , Drug Interactions , Medication Errors/prevention & control , Arizona , Health Care Surveys , Humans , Predictive Value of Tests , Sensitivity and Specificity , Software Validation
6.
Am J Pharm Educ ; 73(2): 27, 2009 Apr 07.
Article in English | MEDLINE | ID: mdl-19513165

ABSTRACT

OBJECTIVE: To evaluate the ability of third- and fourth-year pharmacy students to identify clinically significant drug-drug interactions (DDIs) METHODS: A questionnaire designed to measure DDI knowledge was disseminated to fourth-year pharmacy students in a school of pharmacy. A second questionnaire was distributed to third-year pharmacy students in 2 schools of pharmacy (schools A and B) and re-administered to students in 1 of the schools 1 year later. RESULTS: Class of 2005 fourth-year pharmacy students correctly categorized an average of 52% +/- 13% DDI pairs on the first questionnaire. Third-year pharmacy students at schools A and B correctly categorized an average of 61% +/- 18% and 66% +/- 15% of DDI pairs, respectively. The average percentage of correct responses for fourth-year students from the class of 2007 was 65% (+/- 17%). CONCLUSION: Pharmacy students' ability to identify important DDIs is far from optimal, even after completing experiential requirements.


Subject(s)
Clinical Competence/standards , Drug Interactions , Students, Pharmacy , Adult , Educational Measurement/methods , Educational Measurement/standards , Female , Humans , Male , Surveys and Questionnaires , Young Adult
7.
Am Health Drug Benefits ; 2(7): 309-16, 2009 Nov.
Article in English | MEDLINE | ID: mdl-25126304

ABSTRACT

BACKGROUND: Allergic rhinitis causes significant economic losses and substantial reductions in quality of life. Improving a patient's symptoms can therefore enhance the patient's quality of life. OBJECTIVE: To measure the relative cost-effectiveness of prescription second-generation antihistamines (levocetirizine, desloratadine, and fexofenadine) and montelukast based on their impact on quality of life in patients with uncomplicated allergic rhinitis. METHODS: A retrospective, cost-effectiveness model was constructed using 1-year costs to managed care payers and using the Rhinoconjunctivitis Quality of Life Questionnaire to measure the quality of life in patients taking prescription second-generation antihistamines or montelukast for the treatment of allergic rhinitis. Clinical trial results for levocetirizine, desloratadine, fexofenadine (brand and generic), or montelukast were combined as standardized mean differences to create a pooled effectiveness measure. The costs of prescription drugs and physician office visits for allergic rhinitis were used as direct costs measures. Sensitivity was assessed by a Monte Carlo simulation run 1000 times. RESULTS: All the drugs in the study showed significant improvement in quality of life, with levocetirizine showing the greatest improvement. The incremental cost-effectiveness of levocetirizine dominated montelukast (incremental cost-effective ratio, -1317; 95% confidence interval, -7471, -212). The incremental cost-effectiveness favored levocetirizine compared with desloratadine and branded fexofenadine. CONCLUSION: There are significant differences in the cost-effectiveness of various oral prescription agents with regard to improving quality of life of patients with allergic rhinitis.

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