Literature DB >> 23377696

Postmarketing safety surveillance : where does signal detection using electronic healthcare records fit into the big picture?

Preciosa M Coloma1, Gianluca Trifirò, Vaishali Patadia, Miriam Sturkenboom.   

Abstract

The safety profile of a drug evolves over its lifetime on the market; there are bound to be changes in the circumstances of a drug's clinical use which may give rise to previously unobserved adverse effects, hence necessitating surveillance postmarketing. Postmarketing surveillance has traditionally been carried out by systematic manual review of spontaneous reports of adverse drug reactions. Vast improvements in computing capabilities have provided opportunities to automate signal detection, and several worldwide initiatives are exploring new approaches to facilitate earlier detection, primarily through mining of routinely-collected data from electronic healthcare records (EHR). This paper provides an overview of ongoing initiatives exploring data from EHR for signal detection vis-à-vis established spontaneous reporting systems (SRS). We describe the role SRS has played in regulatory decision making with respect to safety issues, and evaluate the potential added value of EHR-based signal detection systems to the current practice of drug surveillance. Safety signal detection is both an iterative and dynamic process. It is in the best interest of public health to integrate and understand evidence from all possibly relevant information sources on drug safety. Proper evaluation and communication of potential signals identified remains an imperative and should accompany any signal detection activity.

Entities:  

Mesh:

Year:  2013        PMID: 23377696     DOI: 10.1007/s40264-013-0018-x

Source DB:  PubMed          Journal:  Drug Saf        ISSN: 0114-5916            Impact factor:   5.606


  69 in total

Review 1.  Quantitative methods in pharmacovigilance: focus on signal detection.

Authors:  Manfred Hauben; Xiaofeng Zhou
Journal:  Drug Saf       Date:  2003       Impact factor: 5.606

2.  Experience implementing electronic health records in three East African countries.

Authors:  William M Tierney; Marion Achieng; Elaine Baker; April Bell; Paul Biondich; Paula Braitstein; Daniel Kayiwa; Sylvester Kimaiyo; Burke Mamlin; Brian McKown; Nicholas Musinguzi; Winstone Nyandiko; Joseph Rotich; John Sidle; Abraham Siika; Martin Were; Ben Wolfe; Kara Wools-Kaloustian; Ada Yeung; Constantin Yiannoutsos
Journal:  Stud Health Technol Inform       Date:  2010

3.  Comparison of evidence on harms of medical interventions in randomized and nonrandomized studies.

Authors:  Panagiotis N Papanikolaou; Georgia D Christidi; John P A Ioannidis
Journal:  CMAJ       Date:  2006-02-28       Impact factor: 8.262

4.  Electronic healthcare databases for active drug safety surveillance: is there enough leverage?

Authors:  Preciosa M Coloma; Gianluca Trifirò; Martijn J Schuemie; Rosa Gini; Ron Herings; Julia Hippisley-Cox; Giampiero Mazzaglia; Gino Picelli; Giovanni Corrao; Lars Pedersen; Johan van der Lei; Miriam Sturkenboom
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-02-08       Impact factor: 2.890

Review 5.  Primer: administrative health databases in observational studies of drug effects--advantages and disadvantages.

Authors:  Samy Suissa; Edeltraut Garbe
Journal:  Nat Clin Pract Rheumatol       Date:  2007-12

6.  Intussusception among infants given an oral rotavirus vaccine.

Authors:  T V Murphy; P M Gargiullo; M S Massoudi; D B Nelson; A O Jumaan; C A Okoro; L R Zanardi; S Setia; E Fair; C W LeBaron; M Wharton; J R Livengood; J R Livingood
Journal:  N Engl J Med       Date:  2001-02-22       Impact factor: 91.245

7.  Accuracy of diagnostic coding for Medicare patients under the prospective-payment system.

Authors:  D C Hsia; W M Krushat; A B Fagan; J A Tebbutt; R P Kusserow
Journal:  N Engl J Med       Date:  1988-02-11       Impact factor: 91.245

8.  EU-ADR healthcare database network vs. spontaneous reporting system database: preliminary comparison of signal detection.

Authors:  Gianluca Trifirò; Vaishali Patadia; Martijn J Schuemie; Preciosa M Coloma; Rosa Gini; Ron Herings; Julia Hippisley-Cox; Giampiero Mazzaglia; Carlo Giaquinto; Lorenza Scotti; Lars Pedersen; Paul Avillach; Miriam C J M Sturkenboom; Johan van der Lei
Journal:  Stud Health Technol Inform       Date:  2011

9.  Stroke associated with sympathomimetics contained in over-the-counter cough and cold drugs.

Authors:  Carlos Cantu; Antonio Arauz; Luis M Murillo-Bonilla; Mario López; Fernando Barinagarrementeria
Journal:  Stroke       Date:  2003-06-05       Impact factor: 7.914

Review 10.  Cardiovascular risk with non-steroidal anti-inflammatory drugs: systematic review of population-based controlled observational studies.

Authors:  Patricia McGettigan; David Henry
Journal:  PLoS Med       Date:  2011-09-27       Impact factor: 11.069

View more
  29 in total

1.  A study of deep learning approaches for medication and adverse drug event extraction from clinical text.

Authors:  Qiang Wei; Zongcheng Ji; Zhiheng Li; Jingcheng Du; Jingqi Wang; Jun Xu; Yang Xiang; Firat Tiryaki; Stephen Wu; Yaoyun Zhang; Cui Tao; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2020-01-01       Impact factor: 4.497

2.  Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect Relationships.

Authors:  Justin Mower; Devika Subramanian; Ning Shang; Trevor Cohen
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

Review 3.  Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

Authors:  Yuan Luo; William K Thompson; Timothy M Herr; Zexian Zeng; Mark A Berendsen; Siddhartha R Jonnalagadda; Matthew B Carson; Justin Starren
Journal:  Drug Saf       Date:  2017-11       Impact factor: 5.606

4.  Big Data and Pharmacovigilance: Data Mining for Adverse Drug Events and Interactions.

Authors:  C Lee Ventola
Journal:  P T       Date:  2018-06

5.  Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records.

Authors:  Feifan Liu; Abhyuday Jagannatha; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

6.  Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications.

Authors:  Justin Mower; Devika Subramanian; Trevor Cohen
Journal:  J Am Med Inform Assoc       Date:  2018-10-01       Impact factor: 4.497

Review 7.  "Big data" and the electronic health record.

Authors:  M K Ross; W Wei; L Ohno-Machado
Journal:  Yearb Med Inform       Date:  2014-08-15

8.  Effect of Lawyer-Submitted Reports on Signals of Disproportional Reporting in the Food and Drug Administration's Adverse Event Reporting System.

Authors:  James R Rogers; Ameet Sarpatwari; Rishi J Desai; Justin M Bohn; Nazleen F Khan; Aaron S Kesselheim; Michael A Fischer; Joshua J Gagne; John G Connolly
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

9.  Liver injury with novel oral anticoagulants: assessing post-marketing reports in the US Food and Drug Administration adverse event reporting system.

Authors:  Emanuel Raschi; Elisabetta Poluzzi; Ariola Koci; Francesco Salvo; Antoine Pariente; Maurizio Biselli; Ugo Moretti; Nicholas Moore; Fabrizio De Ponti
Journal:  Br J Clin Pharmacol       Date:  2015-05-20       Impact factor: 4.335

10.  From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources.

Authors:  Gianluca Trifirò; Janet Sultana; Andrew Bate
Journal:  Drug Saf       Date:  2018-02       Impact factor: 5.606

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.