Appl Clin Inform 2019; 10(03): 513-520
DOI: 10.1055/s-0039-1693426
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety

Sara Ibáñez-Garcia
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Carmen Rodriguez-Gonzalez
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Vicente Escudero-Vilaplana
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Maria Luisa Martin-Barbero
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Belén Marzal-Alfaro
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Jose Luis De la Rosa-Triviño
2  Ysengineers S.L., Málaga, Spain
,
Irene Iglesias-Peinado
3  Pharmacology Department, College of Pharmacy, Complutense University of Madrid, Madrid, Spain
,
Ana Herranz-Alonso
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
,
Maria Sanjurjo Saez
1  Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Hospital General Universitario Gregorio Marañón, Madrid, Spain
› Institutsangaben
Funding This project was supported by iPharma (Pharmacy Innovation Center) through funding received with project PI12/02883 (Instituto de Salud Carlos III).
Weitere Informationen

Publikationsverlauf

23. Januar 2019

06. Juni 2019

Publikationsdatum:
17. Juli 2019 (online)

Abstract

Background Clinical decision support systems (CDSSs) are a good strategy for preventing medication errors and reducing the incidence and severity of adverse drug events (ADEs). However, these systems are not very effective and are subject to multiple limitations that prevent their implementation in clinical practice.

Objectives The objective of this study was to evaluate the effectiveness of an advanced CDSS, HIGEA, which generates alerts based on predefined clinical rules to identify patients at risk of an ADE.

Methods A multidisciplinary team defined the system and the clinical rules focusing on medication errors commonly encountered in clinical practice. Four intervention programs were defined: (1) dose adjustment in renal impairment; (2) adjustment of anticoagulation/antiplatelet therapy; (3) detection of biochemical/hematologic toxicities; and (4) therapeutic drug monitoring. We performed a 6-month observational prospective study to analyze the effectiveness of these clinical rules by calculating the positive predictive value (PPV).

Results The team defined 211 clinical rules. During the study period, HIGEA generated 1,086 alerts (8.9 alerts per working day), which were reviewed by pharmacists. Fifty-one percent (554/1,086) of alerts generated an intervention to prevent a possible ADE; of these, 66% (368/554) required a documented modification to therapy owing to a real prescription error intercepted. The intervention program that induced the highest number of modifications to therapy was the dose adjustment in renal impairment program (PPV = 0.51), followed by the adjustment of anticoagulation/antiplatelet therapy program (PPV = 0.24). The percentage of accepted interventions was similar in surgical units (68%), medical units (67%), and critical care units (63%).

Conclusion Our study offers evidence that HIGEA is highly effective in preventing potential ADEs at the prescription stage.

Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by Gregorio Marañón Hospital Institutional Review Board.


Supplementary Material