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Polimedication: applicability of a computer tool to reduce polypharmacy in nursing homes

Published online by Cambridge University Press:  11 May 2018

Tomás M. García-Caballero
Affiliation:
Estrutura de Xestión Integrada de Vigo, Vigo, Spain and Universidad de Santiago de Compostela, Spain
Juan Lojo
Affiliation:
Servicio de Apoyo a la Investigación, Hospital Universitario de Ourense, Ourense, Spain
Carlos Menéndez
Affiliation:
Estrutura de Xestión Integrada de Ourense, Ourense, Spain
Roberto Fernández-Álvarez
Affiliation:
Estrutura de Xestión Integrada de Ourense, Ourense, Spain
Raimundo Mateos
Affiliation:
Departamento de Psiquiatría, Facultad de Medicina, Universidad de Santiago, de Compostela, Spain
Alejandro Garcia-Caballero*
Affiliation:
Departamento de Psiquiatría, Facultad de Medicina, Universidad de Santiago, de Compostela, Spain Servicio de Psiquiatría, Instituto de Investigación Biomédica Galicia Sur, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Complexo Hospitalario Universitario de Ourense, Ourense, Spain
*
Correspondence should be addressed to: Alejandro Garcia-Caballero, Servicio de Psiquiatría, EOXI de Ourense, Rúa Ramón Puga s/n, 32005 Ourense, Spain. Phone: +34-988-263681. Email: [email protected].

Abstract

Background:

The risks of polypharmacy can be far greater than the benefits, especially in the elderly. Comorbidity makes polypharmacy very prevalent in this population; thus, increasing the occurrence of adverse effects. To solve this problem, the most common strategy is to use lists of potentially inappropriate medications. However, this strategy is time consuming.

Methods:

In order to minimize the expenditure of time, our group devised a pilot computer tool (Polimedication) that automatically processes lists of medication providing the corresponding Screening Tool of Older Persons’ potentially inappropriate Prescriptions alerts and facilitating standardized reports. The drug lists for 115 residents in Santa Marta Nursing Home (Fundación San Rosendo, Ourense, Spain) were processed.

Results:

The program detected 10.04 alerts/patient, of which 74.29% were not repeated. After reviewing these alerts, 12.12% of the total (1.30 alerts/patient) were considered relevant. The largest number of alerts (41.48%) involved neuroleptic drugs. Finally, the patient's family physician or psychiatrist accepted the alert and made medication changes in 62.86% of the relevant alerts. The largest number of changes (38.64%) also involved neuroleptic drugs. The mean time spent in the generation and review of the warnings was 6.26 minute/patient. Total changes represented a saving of 32.77 € per resident/year in medication.

Conclusions:

The application of Polimedication tool detected a high proportion of potentially inappropriate prescriptions in institutionalized elderly patients. The use of the computerized tool achieved significant savings in pharmaceutical expenditure, as well as a reduction in the time taken for medication review.

Type
Original Research Article
Copyright
Copyright © International Psychogeriatric Association 2018 

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