Cargando…

Comparison of Medication Alerts from Two Commercial Applications in the USA

INTRODUCTION: Medication organizations across the USA have adopted electronic health records, and one of the most anticipated benefits of these was improved medication safety, but alert fatigue has been a major issue. OBJECTIVE: We compared the appropriateness of medication-related clinical decision...

Descripción completa

Detalles Bibliográficos
Autores principales: Shah, Sonam N., Seger, Diane L., Fiskio, Julie M., Horn, John R., Bates, David W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184526/
https://www.ncbi.nlm.nih.gov/pubmed/33616888
http://dx.doi.org/10.1007/s40264-021-01048-0
_version_ 1783704609399767040
author Shah, Sonam N.
Seger, Diane L.
Fiskio, Julie M.
Horn, John R.
Bates, David W.
author_facet Shah, Sonam N.
Seger, Diane L.
Fiskio, Julie M.
Horn, John R.
Bates, David W.
author_sort Shah, Sonam N.
collection PubMed
description INTRODUCTION: Medication organizations across the USA have adopted electronic health records, and one of the most anticipated benefits of these was improved medication safety, but alert fatigue has been a major issue. OBJECTIVE: We compared the appropriateness of medication-related clinical decision support alerts triggered by two commercial applications: EPIC and Seegnal’s platform. METHODS: This was a retrospective comparison of two commercial applications. We provided Seegnal with deidentified inpatient, outpatient, and inpatient genetic electronic medical record (EMR)-extracted datasets for 657, 2731, and 413 patients, respectively. Seegnal then provided the alerts that would have triggered, which we compared with those triggered by EPIC in clinical care. A random sample of the alerts triggered were reviewed for appropriateness, and the positive predictive value (PPV) and negative predictive value (NPV) were calculated. We also reviewed all the inpatient and outpatient charts for patients within our cohort who were receiving ten or more concomitant medications with alerts we found to be appropriate to assess whether any adverse events had occurred and whether Seegnal’s platform could have prevented them. RESULTS: Results from EPIC and the Seegnal platform were compared based on alert load, PPV, NPV, and potential adverse events. Overall, compared with EPIC, the Seegnal platform triggered fewer alerts in the inpatient (1697 vs. 27,540), outpatient (2341 vs. 35,134), and inpatient genetic (1493 vs. 20,975) cohorts. The Seegnal platform had higher specificity in the inpatient (99 vs. 0.3%; p < 0.0001), outpatient (99 vs. 0.3%; p < 0.0001), and inpatient genetic (97.9 vs. 1.2%; p < 0.0001) groups and higher sensitivity in the inpatient (100 vs. 68.8%; p < 0.0001) and outpatient (88.6 vs.78.3%; p < 0.0001) groups but not in the inpatient genetic cohort (81 vs. 78.5%; p = 0.11). We identified 16 adverse events that occurred in the inpatient setting, 11 (69%) of which potentially could have been prevented with the Seegnal platform. CONCLUSIONS: Overall, the Seegnal platform triggered 94% fewer alerts than EPIC in the inpatient setting and 93% fewer in the outpatient setting, with much higher sensitivity and specificity. This application could substantially reduce alert fatigue and improve medication safety at the same time. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s40264-021-01048-0) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-8184526
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-81845262021-06-25 Comparison of Medication Alerts from Two Commercial Applications in the USA Shah, Sonam N. Seger, Diane L. Fiskio, Julie M. Horn, John R. Bates, David W. Drug Saf Original Research Article INTRODUCTION: Medication organizations across the USA have adopted electronic health records, and one of the most anticipated benefits of these was improved medication safety, but alert fatigue has been a major issue. OBJECTIVE: We compared the appropriateness of medication-related clinical decision support alerts triggered by two commercial applications: EPIC and Seegnal’s platform. METHODS: This was a retrospective comparison of two commercial applications. We provided Seegnal with deidentified inpatient, outpatient, and inpatient genetic electronic medical record (EMR)-extracted datasets for 657, 2731, and 413 patients, respectively. Seegnal then provided the alerts that would have triggered, which we compared with those triggered by EPIC in clinical care. A random sample of the alerts triggered were reviewed for appropriateness, and the positive predictive value (PPV) and negative predictive value (NPV) were calculated. We also reviewed all the inpatient and outpatient charts for patients within our cohort who were receiving ten or more concomitant medications with alerts we found to be appropriate to assess whether any adverse events had occurred and whether Seegnal’s platform could have prevented them. RESULTS: Results from EPIC and the Seegnal platform were compared based on alert load, PPV, NPV, and potential adverse events. Overall, compared with EPIC, the Seegnal platform triggered fewer alerts in the inpatient (1697 vs. 27,540), outpatient (2341 vs. 35,134), and inpatient genetic (1493 vs. 20,975) cohorts. The Seegnal platform had higher specificity in the inpatient (99 vs. 0.3%; p < 0.0001), outpatient (99 vs. 0.3%; p < 0.0001), and inpatient genetic (97.9 vs. 1.2%; p < 0.0001) groups and higher sensitivity in the inpatient (100 vs. 68.8%; p < 0.0001) and outpatient (88.6 vs.78.3%; p < 0.0001) groups but not in the inpatient genetic cohort (81 vs. 78.5%; p = 0.11). We identified 16 adverse events that occurred in the inpatient setting, 11 (69%) of which potentially could have been prevented with the Seegnal platform. CONCLUSIONS: Overall, the Seegnal platform triggered 94% fewer alerts than EPIC in the inpatient setting and 93% fewer in the outpatient setting, with much higher sensitivity and specificity. This application could substantially reduce alert fatigue and improve medication safety at the same time. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s40264-021-01048-0) contains supplementary material, which is available to authorized users. Springer International Publishing 2021-02-22 2021 /pmc/articles/PMC8184526/ /pubmed/33616888 http://dx.doi.org/10.1007/s40264-021-01048-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Shah, Sonam N.
Seger, Diane L.
Fiskio, Julie M.
Horn, John R.
Bates, David W.
Comparison of Medication Alerts from Two Commercial Applications in the USA
title Comparison of Medication Alerts from Two Commercial Applications in the USA
title_full Comparison of Medication Alerts from Two Commercial Applications in the USA
title_fullStr Comparison of Medication Alerts from Two Commercial Applications in the USA
title_full_unstemmed Comparison of Medication Alerts from Two Commercial Applications in the USA
title_short Comparison of Medication Alerts from Two Commercial Applications in the USA
title_sort comparison of medication alerts from two commercial applications in the usa
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184526/
https://www.ncbi.nlm.nih.gov/pubmed/33616888
http://dx.doi.org/10.1007/s40264-021-01048-0
work_keys_str_mv AT shahsonamn comparisonofmedicationalertsfromtwocommercialapplicationsintheusa
AT segerdianel comparisonofmedicationalertsfromtwocommercialapplicationsintheusa
AT fiskiojuliem comparisonofmedicationalertsfromtwocommercialapplicationsintheusa
AT hornjohnr comparisonofmedicationalertsfromtwocommercialapplicationsintheusa
AT batesdavidw comparisonofmedicationalertsfromtwocommercialapplicationsintheusa