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Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach

Authors Al-Taani GM, Al-Azzam SI, Alzoubi KH, Darwish Elhajji FW, Scott MG, Alfahel H, Aldeyab MA

Received 19 October 2016

Accepted for publication 17 May 2017

Published 28 July 2017 Volume 2017:9 Pages 65—70


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Dr Rajender R Aparasu

Ghaith M Al-Taani,1 Sayer I Al-Azzam,2 Karem H Alzoubi,2 Feras W Darwish Elhajji,3 Michael G Scott,4 Hamzah Alfahel,5 Mamoon A Aldeyab6

1Department of Pharmacy Practice, Faculty of Pharmacy, Yarmouk University, 2Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, 3Department of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan; 4Medicines Optimisation Innovation Centre, Pharmacy and Medicines Management Centre, Northern Health and Social Care Trust, Ballymena, Northern Ireland, UK; 5General and Specialized Surgery Department, Faculty of Medicine, Hashemite University, Zarqa, Jordan; 6School of Pharmacy and Pharmaceutical Science, University of Ulster, Coleraine, County Londonderry, UK

Objective: Drug-related problems (DRPs) are considered a serious, expensive, and important undesirable complication of health care. However, as current health care resources are limited, pharmacist DRP services cannot be provided to all patients. Using a modeling approach, we aimed to identify risk factors for DRPs so that patients for DRP-reduction services can be better identified.
Methods: Patients with diabetes from outpatient clinics from five key university-affiliated and public hospitals in Jordan were assessed for DRPs (drug without an indication, untreated indication, and drug efficacy problems). Potential risk factors for DRPs were assessed. A logistic regression model was used to identify risk factors using a randomly selected, independent, nonoverlapping development (75%) subsample from full dataset. The remaining validation subsample (25%) was reserved to assess the discriminative ability of the model.
Results: A total of 1,494 patients were recruited. Of them, 81.2% had at least one DRP. Using the development subsample (n=1,085), independent risk factors for DRPs identified were male gender, number of medications, prescribed gastrointestinal medication, and nonadherence to self-care and non-pharmacological recommendations. Validation results (n=403) showed an area under the receiver operating characteristic curve of 0.679 (95% confidence interval=0.629–0.720); the model sensitivity and specificity values were 65.4% and 63.0%, respectively.
Conclusion: Within the outpatient setting, the results of this study predicted DRPs with acceptable accuracy and validity. Such an approach will help in identifying patients needing pharmacist DRP services, which is an important first step in appropriate intervention to address DRPs.

Keywords: medication-related problems, drug-related problems, pharmaceutical care, outpatient, diabetes

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