RT Journal Article
T1 Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications.
A1 Berrouiguet, S
A1 Barrigón Estévez, María Luisa
A1 Brandt, SA
A1 Ovejero García, Santiago
A1 Álvarez García, R
A1 Carballo Belloso, Juan José
A1 Lenca, P
A1 Courtet, P
A1 Baca García, E
AB Purpose: The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose CDSS.Method: A web application (www.MEmind.net) was developed to assess patients and collect data regarding gender, age, diagnosis and treatment. We analyzed antipsychotic prescriptions in 4345 patients attended in five Psychiatric Community Mental Health Centers from June 2014 to October 2014. The web-application reported average daily dose prescribed for antipsychotics, prescribed daily dose (PDD), and the PDD to defined daily dose (DDD) ratio.Results: The MEmind web-application reported that antipsychotics were used in 1116 patients out of the total sample, mostly in 486 (44%) patients with schizophrenia related disorders but also in other diagnoses. Second generation antipsychotics (quetiapine, aripiprazole and long-acting paliperidone) were preferably employed. Low doses were more frequently used than high doses. Long acting paliperidone and ziprasidone however, were the only two antipsychotics used at excessive dosing. Antipsychotic polypharmacy was used in 287 (26%) patients with classic depot drugs, clotiapine, amisulpride and clozapine.Conclusions: In this study we describe the first step of the development of a web application that is able to make polypharmacy, high dose usage and off label usage of antipsychotics visible to clinicians. Current development of the MEmind web application may help to improve prescription security via momentary feedback of prescription and clinical decision support system.
PB PLOS
YR 2016
FD 2016-10-20
LK https://hdl.handle.net/20.500.14352/128565
UL https://hdl.handle.net/20.500.14352/128565
LA eng
NO Berrouiguet S, Barrigón ML, Brandt SA, Ovejero-García S, Álvarez-García R, Carballo JJ, Lenca P, Courtet P; MEmind Study Group; Baca-García E. Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications. PLoS One. 2016 Oct 20;11(10):e0163796. doi: 10.1371/journal.pone.0163796. PMID: 27764107; PMCID: PMC5072715.
DS Docta Complutense
RD 31 dic 2025