Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER) system

2018 ◽  
Vol 25 (4) ◽  
pp. 1232-1243 ◽  
Author(s):  
Abhishek Pandey ◽  
Kory Kreimeyer ◽  
Matthew Foster ◽  
Oanh Dang ◽  
Thomas Ly ◽  
...  
Keyword(s):  
Adverse Event ◽  
Text Mining ◽  
Small Sample ◽  
Event Extraction ◽  
Electronic Records ◽  
Secondary Use ◽  
The Us ◽  
Medical Dictionary ◽  
Event Based ◽  
Ether System

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record’s ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

scholarly journals Cardiovascular Safety Profile of Romosozumab: A Pharmacovigilance Analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS)

2021 ◽  
Vol 10 (8) ◽  
pp. 1660
Author(s):  
Annika Vestergaard Kvist ◽  
Junaid Faruque ◽  
Enriqueta Vallejo-Yagüe ◽  
Stefan Weiler ◽  
Elizabeth M. Winter ◽  
...  
Keyword(s):  
Adverse Event ◽  
Drug Administration ◽  
Cardiovascular Events ◽  
Reporting System ◽  
Food And Drug Administration ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Cardiovascular Safety ◽  
Event Reporting ◽  
The Us

Background: Cardiovascular safety concerns for major cardiovascular events (MACE) were raised during the clinical trials of romosozumab. We aimed to evaluate the cardiovascular safety profile of romosozumab in a large pharmacovigilance database. Methods: All cases reported between January 2019 and December 2020 where romosozumab was reported were extracted from the Food and Drug Administration Adverse Event Reporting System (FAERS). The outcome of interest was MACE (myocardial infarction (MI), stroke, or cardiovascular death). A disproportionality analysis was conducted by estimating the reporting odds ratios (RORs) and 95% confidence intervals. Disproportionality analyses were stratified by sex and reporting region (US, Japan, other). Results: Of the 1995 eligible cases with romosozumab, the majority (N = 1188; 59.5%) originated from Japan. Overall, 206 suspected MACE reports were identified, of which the majority (n = 164; 13.8%) were from Japan, and 41 (5.2%) were from the United States (US). Among Japanese reports, patients were older and more frequently male than reports from the US. Similarly, cases with a reported MACE were older and had higher reports of cardioprotective drugs than those without cardiovascular events. Elevated reports for MACE (ROR 4.07, 95% CI: 2.39–6.93) was identified overall, which was primarily driven by the significant disproportionality measures in the Japanese reports. Conclusions: The current pharmacovigilance study identified a potential signal for elevated MACE, particularly in Japan. The results support the current safety warnings from the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) to avoid use in high-risk patients.

scholarly journals Dependence in the Banking Sector of the United States and Mexico: A Copula Approach

2021 ◽  
Vol 16 (TNEA) ◽  
pp. 1-23
Author(s):  
Christian Bucio Pacheco ◽  
Luis Villanueva ◽  
Raúl de Jesús Gutiérrez
Keyword(s):  
United States ◽  
Stock Prices ◽  
Banking Sector ◽  
Tail Dependence ◽  
The United States ◽  
Small Sample ◽  
High Dependency ◽  
The Us ◽  
Rolling Windows ◽  
Main Banks

The objective of this work is to estimate the patterns of dependence between the yields of the stock prices of the main banks of the United States (US) and Mexico. We estimate the patterns of absolute dependence and tail dependence through copulas of the Archimedean family and the use of rolling windows of 245 days. The data employed come from the daily share prices at closing from January 2, 2015, to December 31, 2020, for seven banks. Our results show that: i) there are patterns of high dependence among the main banks in the US, ii) there are patterns of very low dependence among the main banks in the US and Mexico, and iii) there are patterns of low dependence among the main banks in Mexico. These results have several implications, among them that the high-dependency patterns obtained among major US banks limit the joint selection of these US bank equity assets in an investment portfolio. Although this paper focuses on a small sample of banks, they represent an important portion of the banking sector in both countries. Given the limited literature on this subject in Mexico, our paper contributes to expanding this literature with a novel approach.

Events Automatic Extraction from Arabic Texts

2020 ◽  
pp. 1686-1704
Author(s):  
Emna Hkiri ◽  
Souheyl Mallat ◽  
Mounir Zrigui
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Text Mining ◽  
Machine Translation ◽  
Language Processing ◽  
Question Answering ◽  
Arabic Language ◽  
Event Extraction ◽  
Mining Machine ◽  
Open Domain

The event extraction task consists in determining and classifying events within an open-domain text. It is very new for the Arabic language, whereas it attained its maturity for some languages such as English and French. Events extraction was also proved to help Natural Language Processing tasks such as Information Retrieval and Question Answering, text mining, machine translation etc… to obtain a higher performance. In this article, we present an ongoing effort to build a system for event extraction from Arabic texts using Gate platform and other tools.

scholarly journals A novel method for drug-adverse event extraction using machine learning

2019 ◽  
Vol 17 ◽  
pp. 100190 ◽  
Author(s):  
Kajal Negi ◽  
Arun Pavuri ◽  
Ladle Patel ◽  
Chirag Jain
Keyword(s):  
Machine Learning ◽  
Adverse Event ◽  
Event Extraction ◽  
Drug Adverse Event ◽  
Novel Method

Testing the Integrative Quality Care Assessment Tool (INQUAT)

2019 ◽  
Vol 33 (1) ◽  
pp. 120-144
Author(s):  
Rebecca Amati ◽  
Tommaso Bellandi ◽  
Amer A. Kaissi ◽  
Annegret F. Hannawa
Keyword(s):  
Quality Improvement ◽  
Continuity Of Care ◽  
Assessment Tool ◽  
Small Sample Size ◽  
Quality Care ◽  
Small Sample ◽  
Content Type ◽  
Care Assessment ◽  
Quality Aspects ◽  
The Us

Purpose Identifying the factors that contribute or hinder the provision of good quality care within healthcare institutions, from the managers’ perspective, is important for the success of quality improvement initiatives. The purpose of this paper is to test the Integrative Quality Care Assessment Tool (INQUAT) that was previously developed with a sample of healthcare managers in the USA. Design/methodology/approach Written narratives of 69 good and poor quality care episodes were collected from 37 managers in Italy. A quantitative content analysis was conducted using the INQUAT coding scheme, to compare the results of the US-based study to the new Italian sample. Findings The core frame of the INQUAT was replicated and the meta-categories showed similar distributions compared to the US data. Structure (i.e. organizational, staff and facility resources) covered 8 percent of all the coded units related to quality aspects; context (i.e. clinical factors and patient factors) 10 percent; process (i.e. communication, professional diligence, timeliness, errors and continuity of care) 49 percent; and outcome (i.e. process- and short-term outcomes) 32 percent. However, compared to the US results, Italian managers attributed more importance to different categories’ subcomponents, possibly due to the specificity of each sample. For example, professional diligence, errors and continuity of care acquired more weight, to the detriment of communication. Furthermore, the data showed that process subcomponents were associated to perceived quality more than outcomes. Research limitations/implications The major limitation of this investigation was the small sample size. Further studies are needed to test the reliability and validity of the INQUAT. Originality/value The INQUAT is proposed as a tool to systematically conduct in depth analyses of successful and unsuccessful healthcare events, allowing to better understand the factors that contribute to good quality and to identify specific areas that may need to be targeted in quality improvement initiatives.

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