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

Ghaith M. Al-Taani, Sayer I. Al-Azzam, Karem H. Alzoubi, Feras W.Darwish Elhajji, Michael G. Scott, Hamzah Alfahel, Mamoon A. Aldeyab

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)65-70
Number of pages6
JournalDrug, Healthcare and Patient Safety
Volume9
DOIs
Publication statusPublished - 28 Jul 2017
Externally publishedYes

Fingerprint

Outpatients
Pharmaceutical Preparations
Pharmacists
Logistic Models
Delivery of Health Care
Jordan
Aptitude
Medication Adherence
Health Resources
Public Hospitals
Self Care
Ambulatory Care Facilities
ROC Curve
Confidence Intervals
Sensitivity and Specificity

Cite this

Al-Taani, Ghaith M. ; Al-Azzam, Sayer I. ; Alzoubi, Karem H. ; Elhajji, Feras W.Darwish ; Scott, Michael G. ; Alfahel, Hamzah ; Aldeyab, Mamoon A. / Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach. In: Drug, Healthcare and Patient Safety. 2017 ; Vol. 9. pp. 65-70.
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abstract = "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.",
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Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach. / Al-Taani, Ghaith M.; Al-Azzam, Sayer I.; Alzoubi, Karem H.; Elhajji, Feras W.Darwish; Scott, Michael G.; Alfahel, Hamzah; Aldeyab, Mamoon A.

In: Drug, Healthcare and Patient Safety, Vol. 9, 28.07.2017, p. 65-70.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Prediction of drug-related problems in diabetic outpatients in a number of hospitals, using a modeling approach

AU - Al-Taani, Ghaith M.

AU - Al-Azzam, Sayer I.

AU - Alzoubi, Karem H.

AU - Elhajji, Feras W.Darwish

AU - Scott, Michael G.

AU - Alfahel, Hamzah

AU - Aldeyab, Mamoon A.

PY - 2017/7/28

Y1 - 2017/7/28

N2 - 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.

AB - 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.

KW - Diabetes

KW - Drug-related problems

KW - Medication-related problems

KW - Outpatient

KW - Pharmaceutical care

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DO - 10.2147/DHPS.S125114

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