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The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy

BACKGROUND: Estimate the expenditure of computer-related worktime resulting from the use of clinical decision support systems (CDSS) to prevent adverse drug reactions (ADR) among patients undergoing chronic pain therapy and compare the employed check systems with respect to performance and practicab...

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Autores principales: Hecht, Timm, Bundscherer, Anika C., Lassen, Christoph L., Lindenberg, Nicole, Graf, Bernhard M., Ittner, Karl-Peter, Wiese, Christoph H. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4521352/
https://www.ncbi.nlm.nih.gov/pubmed/26231078
http://dx.doi.org/10.1186/s12871-015-0094-9
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author Hecht, Timm
Bundscherer, Anika C.
Lassen, Christoph L.
Lindenberg, Nicole
Graf, Bernhard M.
Ittner, Karl-Peter
Wiese, Christoph H. R.
author_facet Hecht, Timm
Bundscherer, Anika C.
Lassen, Christoph L.
Lindenberg, Nicole
Graf, Bernhard M.
Ittner, Karl-Peter
Wiese, Christoph H. R.
author_sort Hecht, Timm
collection PubMed
description BACKGROUND: Estimate the expenditure of computer-related worktime resulting from the use of clinical decision support systems (CDSS) to prevent adverse drug reactions (ADR) among patients undergoing chronic pain therapy and compare the employed check systems with respect to performance and practicability. METHODS: Data were collected retrospectively from 113 medical records of patients under chronic pain therapy during 2012/2013. Patient-specific medications were checked for potential drug-drug interactions (DDI) using two publicly available CDSS, Apotheken Umschau (AU) and Medscape (MS), and a commercially available CDSS AiDKlinik® (AID). The time needed to analyze patient pharmacotherapy for DDIs was taken with a stopwatch. Measurements included the time needed for running the analysis and printing the results. CDSS were compared with respect to the expenditure of time and usability. Only patient pharmacotherapies with at least two prescribed drugs and fitting the criteria of the corresponding CDSS were analyzed. Additionally, a qualitative evaluation of the used check systems was performed, employing a questionnaire asking five pain physicians to compare and rate the performance and practicability of the three CDSSs. RESULTS: The AU tool took a total of 3:55:45 h with an average of 0:02:32 h for 93 analyzed patient regimens and led to the discovery of 261 DDIs. Using the Medscape interaction checker required a total of 1:28:35 h for 38 patients with an average of 0:01:58 h and a yield of 178 interactions. The CDSS AID required a total of 3:12:27 h for 97 patients with an average time of analysis of 0:01:59 h and the discovery of 170 DDIs. According to the pain physicians the CDSS AID was chosen as the preferred tool. CONCLUSIONS: Applying a CDSS to examine a patients drug regimen for potential DDIs causes an average extra expenditure of work time of 2:09 min, which extends patient treatment time by 25 % on average. Nevertheless, the authors believe that the extra expenditure of time employing a CDSS is outweighed by their benefits, including reduced ADR risks and safer clinical drug management.
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spelling pubmed-45213522015-08-01 The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy Hecht, Timm Bundscherer, Anika C. Lassen, Christoph L. Lindenberg, Nicole Graf, Bernhard M. Ittner, Karl-Peter Wiese, Christoph H. R. BMC Anesthesiol Research Article BACKGROUND: Estimate the expenditure of computer-related worktime resulting from the use of clinical decision support systems (CDSS) to prevent adverse drug reactions (ADR) among patients undergoing chronic pain therapy and compare the employed check systems with respect to performance and practicability. METHODS: Data were collected retrospectively from 113 medical records of patients under chronic pain therapy during 2012/2013. Patient-specific medications were checked for potential drug-drug interactions (DDI) using two publicly available CDSS, Apotheken Umschau (AU) and Medscape (MS), and a commercially available CDSS AiDKlinik® (AID). The time needed to analyze patient pharmacotherapy for DDIs was taken with a stopwatch. Measurements included the time needed for running the analysis and printing the results. CDSS were compared with respect to the expenditure of time and usability. Only patient pharmacotherapies with at least two prescribed drugs and fitting the criteria of the corresponding CDSS were analyzed. Additionally, a qualitative evaluation of the used check systems was performed, employing a questionnaire asking five pain physicians to compare and rate the performance and practicability of the three CDSSs. RESULTS: The AU tool took a total of 3:55:45 h with an average of 0:02:32 h for 93 analyzed patient regimens and led to the discovery of 261 DDIs. Using the Medscape interaction checker required a total of 1:28:35 h for 38 patients with an average of 0:01:58 h and a yield of 178 interactions. The CDSS AID required a total of 3:12:27 h for 97 patients with an average time of analysis of 0:01:59 h and the discovery of 170 DDIs. According to the pain physicians the CDSS AID was chosen as the preferred tool. CONCLUSIONS: Applying a CDSS to examine a patients drug regimen for potential DDIs causes an average extra expenditure of work time of 2:09 min, which extends patient treatment time by 25 % on average. Nevertheless, the authors believe that the extra expenditure of time employing a CDSS is outweighed by their benefits, including reduced ADR risks and safer clinical drug management. BioMed Central 2015-08-01 /pmc/articles/PMC4521352/ /pubmed/26231078 http://dx.doi.org/10.1186/s12871-015-0094-9 Text en © Hecht et al. 2015 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Hecht, Timm
Bundscherer, Anika C.
Lassen, Christoph L.
Lindenberg, Nicole
Graf, Bernhard M.
Ittner, Karl-Peter
Wiese, Christoph H. R.
The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title_full The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title_fullStr The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title_full_unstemmed The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title_short The expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
title_sort expenditure of computer-related worktime using clinical decision support systems in chronic pain therapy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4521352/
https://www.ncbi.nlm.nih.gov/pubmed/26231078
http://dx.doi.org/10.1186/s12871-015-0094-9
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