OHDSI MEETINGS THIS WEEK
OHDSI Community Call - Tuesday at 12pm EThttps://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.986822111212
Population-Level Estimation (Eastern hemisphere) workgroup meeting - Wednesday at 3pm Hong Kong timehttps://meetings.webex.com/collabs/meetings/join?uuid=M6WE9AOKFETH2VEFPVCZWWBIT0-D1JL
Architecture Working Group - Thursday at 10am EThttps://jjconferencing.webex.com/mw3100/mywebex/default.do?service=1&siteurl=jjconferencing&nomenu=true&main_url=%2Fmc3100%2Fe.do%3Fsiteurl%3Djjconferencing%26AT%3DMI%26EventID%3D610982452%26UID%3D501476547%26Host%3DQUhTSwAAAAQu4P1o9qm71JJ1Zj4-uvZbjQttsCinu71JCRxBAHAXnzjjRAiTspTzU9ojLmjMF4CcTBWw4zn1dqYPTWu5vJ9_0%26FrameSet%3D2%26MTID%3Dm3e1ceeca56f1e94c9fcf1ae98c10e02e
GIS working group meeting - Next Monday (July 2nd) at 10am ET
Simple, modern video meetings for the global workforce. Join from anywhere, including your desktop, browser, mobile device, or video room device.
ANNOUNCEMENTS
2018 OHDSI Symposium - TUTORIAL REGISTRATION OPEN https://www.ohdsi.org/tutorial-workshops/ https://www.ohdsi.org/tutorial-registration-2/
Intro tutorials
Advanced tutorials
2018 OHDSI Symposium - CALL FOR PARTICIPATION https://www.ohdsi.org/collaborator-showcase/
2018 China Symposium https://www.ohdsi.org/events/2018-china-symposium/
Moving Study Materials to Github https://github.com/OHDSI/StudyProtocolSandbox https://github.com/OHDSI/StudyProtocols
A letdown is worth a few songs. A heartbreak is worth a few albums.
COMMUNITY PUBLICATIONS
Tissue‐Specific Analysis of Pharmacological Pathwayshttps://ascpt.onlinelibrary.wiley.com/doi/full/10.1002/psp4.12305
OpenPVSignal: Advancing Pharmacovigilance Signals Information Search, Sharing and Reuse via FAIR Principles and Semantic Web Technologies
“Minimally invasive research?” Use of the electronic health record to facilitate research in pediatric urology.
VM Vemulakonda, RA Bush and MG Kahn,
Journal of pediatric urology , Jun 2018 09
The electronic health record (EHR) was designed as a clinical and administrative tool to improve clinical patient care. Electronic healthcare systems have been successfully adopted across the world through use of government mandates and incentives.Using electronic health record, health information system, electronic medical record, health information systems, research, outcomes, pediatric, surgery, and urology as initial search terms, the literature focusing on clinical documentation data capture and the EHR as a potential resource for research related to clinical outcomes, quality improvement, and comparative effectiveness was reviewed. Relevant articles were supplemented by secondary review of article references as well as seminal articles in the field as identified by the senior author.US federal funding agencies, including the Agency for Healthcare Research and Quality, the Patient-Centered Outcomes Research Institute, the National Institutes of Health, and the Food and Drug Administration have recognized the EHR's role supporting research. The main approached to using EHR data include enhanced lists, direct data extraction, structured data entry, and unstructured data entry. The EHR's potential to facilitate research, overcoming cost and time burdens associated with traditional data collection, has not resulted in widespread use of EHR-based research tools.There are strengths and weaknesses for all existing methodologies of using EHR data to support research. Collaboration is needed to identify the method that best suits the institution for incorporation of research-oriented data collection into routine pediatric urologic clinical practice.
Can Electronic Health Records Databases Complement Spontaneous Reporting System Databases? A Historical-Reconstruction of the Association of Rofecoxib and Acute Myocardial Infarction.
VK Patadia, MJ Schuemie, PM Coloma, R Herings, J van der Lei, M Sturkenboom and G Trifirò,
Frontiers in pharmacology , 2018
Background: Several initiatives have assessed if mining electronic health records (EHRs) may accelerate the process of drug safety signal detection. In Europe, Exploring and Understanding Adverse Drug Reactions (EU-ADR) Project Focused on utilizing clinical data from EHRs of over 30 million patients from several European countries. Rofecoxib is a prescription COX-2 selective Non-Steroidal Anti-Inflammatory Drugs (NSAID) approved in 1999. In September 2004, the manufacturer withdrew rofecoxib from the market because of safety concerns. In this study, we investigated if the signal concerning rofecoxib and acute myocardial infarction (AMI) could have been identified in EHR database (EU-ADR project) earlier than spontaneous reporting system (SRS), and in advance of rofecoxib withdrawal. Methods: Data from the EU-ADR project and WHO-VigiBase (for SRS) were used for the analysis. Signals were identified when respective statistics exceeded defined thresholds. The SRS analyses was conducted two ways- based on the date the AMI events with rofecoxib as a suspect medication were entered into the database and also the date that the AMI event occurred with exposure to rofecoxib. Results: Within the databases participating in EU-ADR it was possible to identify a strong signal concerning rofecoxib and AMI since Q3 2000 [RR LGPS = 4.5 (95% CI: 2.84-6.72)] and peaked to 4.8 in Q4 2000. In WHO-VigiBase, for AMI term grouping, the EB05 threshold of 2 was crossed in the Q4 2004 (EB05 = 2.94). Since then, the EB05 value increased consistently and peaked in Q3 2006 (EB05 = 48.3) and then again in Q2 2008 (EB05 = 48.5). About 93% (2260 out of 2422) of AMIs reported in WHO-VigiBase database actually occurred prior to the product withdrawal, however, they were reported after the risk minimization/risk communication efforts. Conclusion: In this study, EU-EHR databases were able to detect the AMI signal 4 years prior to the SRS database. We believe that for events that are consistently documented in EHR databases, such as serious events or events requiring in-patient medical intervention or hospitalization, the signal detection exercise in EHR would be beneficial for newly introduced medicinal products on the market, in addition to the SRS data.
Comprehensive comparison of monotherapies for psychiatric hospitalization risk in bipolar disorders.
A Nestsiarovich, AJ Mazurie, NG Hurwitz, B Kerner, SJ Nelson, AS Crisanti, M Tohen, RL Krall, DJ Perkins and CG Lambert,
Bipolar disorders , Jun 2018 19
This study compared 29 drugs for risk of psychiatric hospitalization in bipolar disorders, addressing the evidence gap on the >50 drugs used by US patients for treatment.The Truven Health Analytics MarketScan® database was used to identify 190 894 individuals with bipolar or schizoaffective disorder who filled a prescription for one of 29 drugs of interest: lithium, first- or second-generation antipsychotics, mood-stabilizing anticonvulsants, and antidepressants. Competing risks regression survival analysis was used to compare drugs for risk of psychiatric hospitalization, adjusting for patient age, sex, comorbidities, and pretreatment medications. Other competing risks were ending monotherapy and non-psychiatric hospitalization.Three drugs were associated with significantly lower risk of psychiatric hospitalization than lithium: valproate (relative risk [RR] = 0.80, P = 3.20 × 10-4 ), aripiprazole (RR = 0.80, P = 3.50 × 10-4 ), and bupropion (RR = 0.80, P = 2.80 × 10-4 ). Eight drugs were associated with significantly higher risk of psychiatric hospitalization: haloperidol (RR = 1.57, P = 9.40 × 10-4 ), clozapine (RR = 1.52, P = .017), fluoxetine (RR = 1.17, P = 3.70 × 10-3 ), sertraline (RR = 1.17, P = 3.20 × 10-3 ), citalopram (RR = 1.14, P = .013), duloxetine (RR = 1.24, P = 5.10 × 10-4 ), venlafaxine (RR = 1.33; P = 1.00 × 10-6 ), and ziprasidone (RR = 1.25; P = 6.20 × 10-3 ).This largest reported retrospective observational study on bipolar disorders pharmacotherapy to date demonstrates that the majority of patients end monotherapy within 2 months after treatment start. The risk of psychiatric hospitalization varied almost two-fold across individual medications. The data add to the evidence favoring lithium and mood stabilizer use in short-term bipolar disorder management. The findings that the dopaminergic drugs aripiprazole and bupropion had better outcomes than other members of their respective classes and that antidepressant outcomes may vary by baseline mood polarity merit further investigation.
Low Rates of Screening for Celiac Disease Among Family Members.
AS Faye, F Polubriaginof, PHR Green, DK Vawdrey, N Tatonetti and B Lebwohl,
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association , Jun 2018 18
Given the increased morbidity and potential mortality of celiac disease, guidelines recommend screening high-risk individuals, including first-degree relatives of patients. We assessed how commonly celiac disease testing occurs in these individuals and identified factors that influence testing.Relatives of 2081 patients with biopsy-diagnosed celiac disease and followed up at Columbia University Medical Center were identified using relationship inference from the electronic health record-a validated method that uses emergency contact information to identify familial relationships. We manually abstracted data from each record and performed univariate and multivariate analyses to identify factors associated with testing relatives for celiac disease.Of 539 relatives identified, 212 (39.3%) were tested for celiac disease, including 50.4% (193 of 383) of first-degree relatives and 71.5% (118 of 165) of symptomatic first-degree relatives. Of the 383 first-degree relatives, only 116 (30.3%) had a documented family history of celiac disease. On multivariate analysis, testing was more likely in adults (odds ratio [OR], for 18-39 y vs younger than 18 y, 2.27; 95% CI, 1.12-4.58); relatives being seen by a gastroenterologist (OR, 15.16; 95% CI, 7.72-29.80); relatives with symptoms (OR, 3.69; 95% CI, 2.11-6.47); first-degree relatives of a patient with celiac disease (OR, 4.90, 95% CI, 2.34-10.25); and relatives with a documented family history of celiac disease (OR, 11.9, 95% CI, 5.56-25.48).By using an algorithm to identify relatives of patients with celiac disease, we found that nearly 30% of symptomatic first-degree relatives of patients with celiac disease have not received the tests recommended by guidelines. Health care providers should implement strategies to identify and screen patients at increased risk for celiac disease, including methods to ensure adequate documentation of family medical history.
