TY - JOUR
T1 - Computerized pharmacy surveillance and alert system for drug-related problems
AU - Ferrández, O.
AU - Urbina, O.
AU - Grau, S.
AU - Mateu-de-Antonio, J.
AU - Marin-Casino, M.
AU - Portabella, J.
AU - Mojal, S.
AU - Riu, M.
AU - Salas, E.
PY - 2017/4/1
Y1 - 2017/4/1
N2 - © 2017 John Wiley & Sons Ltd What is known and objective: Because of the impact of drug-related problems (DRPs) on morbidity and mortality, there is a need for computerized strategies to increase drug safety. The detection and identification of the causes of potential DRPs can be facilitated by the incorporation of a pharmacy warning system (PWS) in the computerized prescriber order entry (CPOE) and its application in the routine validation of inpatient drug therapy. A limited number of studies have evaluated a clinical decision support system to monitor drug treatment. Most of these applications have utilized a small range of drugs with alerts and/or types of alert. The objective of this study was to describe the implementation of a PWS integrated in the electronic medical record (EMR). Methods: The PWS was developed in 2003–2004. Pharmacological information to generate drug alerts was entered on demographic data, drug dosage, laboratory tests related to the prescribed drug and drug combinations (interactions, duplications and necessary combinations). The PWS was applied in the prescription reviews conducted in patients admitted to the hospital in 2012. Results and discussion: Information on 83% of the drugs included in the pharmacopeia was introduced into the PWS, allowing detection of 2808 potential DRPs, representing 79·1% of all potential DRPs detected during the study period. Twenty per cent of PWS DRPs were clinically relevant, requiring pharmacist intervention. What is new and conclusion: The PWS detected most potential DRPs, thus increasing inpatient safety. The detection ability of the PWS was higher than that reported for other tools described in the literature.
AB - © 2017 John Wiley & Sons Ltd What is known and objective: Because of the impact of drug-related problems (DRPs) on morbidity and mortality, there is a need for computerized strategies to increase drug safety. The detection and identification of the causes of potential DRPs can be facilitated by the incorporation of a pharmacy warning system (PWS) in the computerized prescriber order entry (CPOE) and its application in the routine validation of inpatient drug therapy. A limited number of studies have evaluated a clinical decision support system to monitor drug treatment. Most of these applications have utilized a small range of drugs with alerts and/or types of alert. The objective of this study was to describe the implementation of a PWS integrated in the electronic medical record (EMR). Methods: The PWS was developed in 2003–2004. Pharmacological information to generate drug alerts was entered on demographic data, drug dosage, laboratory tests related to the prescribed drug and drug combinations (interactions, duplications and necessary combinations). The PWS was applied in the prescription reviews conducted in patients admitted to the hospital in 2012. Results and discussion: Information on 83% of the drugs included in the pharmacopeia was introduced into the PWS, allowing detection of 2808 potential DRPs, representing 79·1% of all potential DRPs detected during the study period. Twenty per cent of PWS DRPs were clinically relevant, requiring pharmacist intervention. What is new and conclusion: The PWS detected most potential DRPs, thus increasing inpatient safety. The detection ability of the PWS was higher than that reported for other tools described in the literature.
KW - alerts
KW - computerized prescriber order entry
KW - drug-related problem
KW - pharmacy warning system
KW - prescription review
UR - https://www.scopus.com/pages/publications/85010908318
U2 - 10.1111/jcpt.12495
DO - 10.1111/jcpt.12495
M3 - Article
SN - 0269-4727
VL - 42
SP - 201
EP - 208
JO - Journal of Clinical Pharmacy and Therapeutics
JF - Journal of Clinical Pharmacy and Therapeutics
IS - 2
ER -