Cargando…

Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity

OBJECTIVES: To enable early detection of adverse drug reactions (ADRs) in patients using HMG-CoA reductase inhibitors (statins), we developed an algorithm that automatically detects liver injury caused by statins from Electronic Medical Record (EMR) data. We verified the performance of our algorithm...

Descripción completa

Detalles Bibliográficos
Autores principales: Hong, Joo Young, Kim, Hun-Sung, Choi, In Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572524/
https://www.ncbi.nlm.nih.gov/pubmed/28875055
http://dx.doi.org/10.4258/hir.2017.23.3.199
_version_ 1783259540587806720
author Hong, Joo Young
Kim, Hun-Sung
Choi, In Young
author_facet Hong, Joo Young
Kim, Hun-Sung
Choi, In Young
author_sort Hong, Joo Young
collection PubMed
description OBJECTIVES: To enable early detection of adverse drug reactions (ADRs) in patients using HMG-CoA reductase inhibitors (statins), we developed an algorithm that automatically detects liver injury caused by statins from Electronic Medical Record (EMR) data. We verified the performance of our algorithm through manual ADR assessment and a direct chart review. METHODS: The subjects in this study were patients who had been prescribed a statin for the first time among outpatients in Seoul St. Mary's Hospital in Korea between January 2009 and December 2012. We extracted basic information about the patients, including laboratory information, underlying disease, diagnosis information, prescription information, and concomitant drugs. We developed an automatic ADR detection algorithm by using EMR data. We validated the results of the algorithm through a chart review. RESULTS: We developed the algorithm to assess ADR occurrences based on alanine transaminase (ALT) and alkaline phosphatase (ALP) levels. According to the proposed algorithm, any of these result options could be attained: ADR-free, little association, strong association, and weak association or indeterminable. The results of the ADR assessments obtained using the proposed algorithm showed that the data of 126 patients (1.4% of all 9,241 patients) included suspicious figures, thus indicating the possibility of an ADR. In the EMR chart review for verifying the algorithm, ADRs of 33 patients were not associated with statin use; therefore, the ADR occurrence rate was found to be 1.0% (93/9,241). Therefore, the positive predictive value was calculated to be 73.8% (93/126; 95% confidence interval, 69.2%–77.6%). No differences were observed between statin types (p = 0.472). CONCLUSIONS: For early detection of statin-induced liver injury, we developed an automatic ADR assessment algorithm. We expect that algorithms that are more reliable can be developed if we conduct supplement clinical studies with a focus on adverse drug effects.
format Online
Article
Text
id pubmed-5572524
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Korean Society of Medical Informatics
record_format MEDLINE/PubMed
spelling pubmed-55725242017-09-05 Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity Hong, Joo Young Kim, Hun-Sung Choi, In Young Healthc Inform Res Original Article OBJECTIVES: To enable early detection of adverse drug reactions (ADRs) in patients using HMG-CoA reductase inhibitors (statins), we developed an algorithm that automatically detects liver injury caused by statins from Electronic Medical Record (EMR) data. We verified the performance of our algorithm through manual ADR assessment and a direct chart review. METHODS: The subjects in this study were patients who had been prescribed a statin for the first time among outpatients in Seoul St. Mary's Hospital in Korea between January 2009 and December 2012. We extracted basic information about the patients, including laboratory information, underlying disease, diagnosis information, prescription information, and concomitant drugs. We developed an automatic ADR detection algorithm by using EMR data. We validated the results of the algorithm through a chart review. RESULTS: We developed the algorithm to assess ADR occurrences based on alanine transaminase (ALT) and alkaline phosphatase (ALP) levels. According to the proposed algorithm, any of these result options could be attained: ADR-free, little association, strong association, and weak association or indeterminable. The results of the ADR assessments obtained using the proposed algorithm showed that the data of 126 patients (1.4% of all 9,241 patients) included suspicious figures, thus indicating the possibility of an ADR. In the EMR chart review for verifying the algorithm, ADRs of 33 patients were not associated with statin use; therefore, the ADR occurrence rate was found to be 1.0% (93/9,241). Therefore, the positive predictive value was calculated to be 73.8% (93/126; 95% confidence interval, 69.2%–77.6%). No differences were observed between statin types (p = 0.472). CONCLUSIONS: For early detection of statin-induced liver injury, we developed an automatic ADR assessment algorithm. We expect that algorithms that are more reliable can be developed if we conduct supplement clinical studies with a focus on adverse drug effects. Korean Society of Medical Informatics 2017-07 2017-07-31 /pmc/articles/PMC5572524/ /pubmed/28875055 http://dx.doi.org/10.4258/hir.2017.23.3.199 Text en © 2017 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Hong, Joo Young
Kim, Hun-Sung
Choi, In Young
Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title_full Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title_fullStr Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title_full_unstemmed Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title_short Pilot Algorithm Designed to Help Early Detection of HMG-CoA Reductase Inhibitor-Induced Hepatotoxicity
title_sort pilot algorithm designed to help early detection of hmg-coa reductase inhibitor-induced hepatotoxicity
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572524/
https://www.ncbi.nlm.nih.gov/pubmed/28875055
http://dx.doi.org/10.4258/hir.2017.23.3.199
work_keys_str_mv AT hongjooyoung pilotalgorithmdesignedtohelpearlydetectionofhmgcoareductaseinhibitorinducedhepatotoxicity
AT kimhunsung pilotalgorithmdesignedtohelpearlydetectionofhmgcoareductaseinhibitorinducedhepatotoxicity
AT choiinyoung pilotalgorithmdesignedtohelpearlydetectionofhmgcoareductaseinhibitorinducedhepatotoxicity