Comparative evaluation of three clinical decision support systems: prospective screening for medication errors in 100 medical inpatients.
Purpose: Clinical decision support systems (CDSS) are promoted as powerful screening tools to improve pharmacotherapy. The aim of our study was to evaluate the potential contribution of CDSS to patient management in clinical practice. Methods: We prospectively analyzed the pharmacotherapy of 100 med...
| Publicado en: | European Journal of Clinical Pharmacology Vol. 68; no. 8; pp. 1209 - 1220 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104476936&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104476936 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00316970 NP9 jtl: European Journal of Clinical Pharmacology issn: 00316970 maglogo: N pubinfo: dt: Aug2012 vid: 68 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104476936 77736373 10.1007/s00228-012-1241-6 NLM22374346 104476936 ppf: 1209 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Comparative evaluation of three clinical decision support systems: prospective screening for medication errors in 100 medical inpatients. aug: au: Fritz, Daniela Ceschi, Alessandro Curkovic, Ivanka Huber, Martin Egbring, Marco Kullak-Ublick, Gerd Russmann, Stefan affil: Department of Clinical Pharmacology and Toxicology, University Hospital Zurich, Rämistrasse 100 8091 Zurich Switzerland sug: subj: Medication Errors Prevention and Control Decision Making, Computer Assisted Evaluation Decision Making, Clinical Evaluation Adverse Drug Event Prevention and Control Decision Making, Computer Assisted Methods Prospective Studies Human Inpatients Cross Sectional Studies Academic Medical Centers Treatment Outcomes Sensitivity and Specificity Data Analysis Software Male Female Adult Middle Age Aged Aged, 80 and Over Descriptive Statistics Polypharmacy Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Purpose: Clinical decision support systems (CDSS) are promoted as powerful screening tools to improve pharmacotherapy. The aim of our study was to evaluate the potential contribution of CDSS to patient management in clinical practice. Methods: We prospectively analyzed the pharmacotherapy of 100 medical inpatients through the parallel use of three CDSS, namely, Pharmavista, DrugReax, and TheraOpt. After expert discussion that also considered all patient-specific clinical information, we selected apparently relevant alerts, issued suitable recommendations to physicians, and recorded subsequent prescription changes. Results: For 100 patients with a median of eight concomitant drugs, Pharmavista, DrugReax, and TheraOpt generated a total of 53, 362, and 328 interaction alerts, respectively. Among those we identified and forwarded 33 clinically relevant alerts to the attending physician, resulting in 19 prescription changes. Four adverse drug events were associated with interactions. The proportion of clinically relevant alerts among all alerts (positive predictive value) was 5.7, 8.0, and 7.6%, and the sensitivity to detect all 33 relevant alerts was 9.1, 87.9, and 75.8% for Pharmavista, DrugReax and TheraOpt, respectively. TheraOpt recommended 31 dose adjustments, of which we considered 11 to be relevant; three of these were followed by dose reductions. Conclusions: CDSS are valuable screening tools for medication errors, but only a small fraction of their alerts appear relevant in individual patients. In order to avoid overalerting CDSS should use patient-specific information and management-oriented classifications. Comprehensive information should be displayed on-demand, whereas a limited number of computer-triggered alerts that have management implications in the majority of affected patients should be based on locally customized and supported algorithms. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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