Weekly OHDSI Digest - 9Apr2018

MauraBeaton · April 9, 2018, 6:08pm

OHDSI MEETINGS THIS WEEK

OHDSI Community Call - Tuesday at 12pm ET (5pm CET)
https://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.986822133
US TOLL: +1-415-655-0001
Meeting Number: 199 982 907

Population-Level Estimation (Western hemisphere) workgroup meeting - Thursday at 12pm ET (5pm CET)
https://meetings.webex.com/collabs/#/meetings/detail?uuid=M3T9BZV9RSB6YNDM8WDDZMI19D-D1JL&rnd=229240.54296

Hadoop WG meeting - Friday at 11am ET (4pm CET)
https://meet.lync.com/quintiles-quintilesims/mui.vanzandt/R8V4N3S9
Call in Number: 1-646-838-2458
Attendee access code: 75630528

GIS working group meeting - Monday (April 16th) at 10am ET

Meeting Number: 735 317 239
Password: gaia

ANNOUNCEMENTS

Epically OHDSI: Check out the first episode of OHDSI’s vlog here: https://youtu.be/V3hVgIOV6Z8
The episode covers highlights from the ATLAS 2.3 release

OHDSI Europe Tutorial Videos - Coming soon! Tutorial recordings from our first European Symposium will be uploaded on the OHDSI youtube channel later this week. Keep an eye out!

2018 OHDSI Symposium - Collaborator showcase
Back by popular demand, the collaborator showcase will be part of the 2018 OHDSI Symposium, set to take place on September 18th at the Bethesda North Marriott! Once again we’ll be inviting collaborators to participate in the collaborator showcase by submitting abstracts to give poster presentations, software demonstrations or oral presentations. More details coming soon!

Life is not a problem to be solved, but a reality to be experienced

Soren Kierkegaard

COMMUNITY PUBLICATIONS

A systematic approach to improving the reliability and scale of evidence from health care data

Psychotropic Medication Use Among Adults With Schizophrenia and Schizoaffective Disorder in the United States
https://ps.psychiatryonline.org/doi/abs/10.1176/appi.ps.201700356

Vojtech_Huser · April 9, 2018, 7:59pm

This recent article is also of note

ncbi.nlm.nih.gov

Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data.

MJ Schuemie, G Hripcsak, PB Ryan, D Madigan and MA Suchard, Proceedings of the National Academy of Sciences of the United States of America, 2018 13 03

Observational healthcare data, such as electronic health records and administrative claims, offer potential to estimate effects of medical products at scale. Observational studies have often been found to be nonreproducible, however, generating conflicting results even when using the same database to answer the same question. One source of discrepancies is error, both random caused by sampling variability and systematic (for example, because of confounding, selection bias, and measurement error). Only random error is typically quantified but converges to zero as databases become larger, whereas systematic error persists independent from sample size and therefore, increases in relative importance. Negative controls are exposure-outcome pairs, where one believes no causal effect exists; they can be used to detect multiple sources of systematic error, but interpreting their results is not always straightforward. Previously, we have shown that an empirical null distribution can be derived from a sample of negative controls and used to calibrate P values, accounting for both random and systematic error. Here, we extend this work to calibration of confidence intervals (CIs). CIs require positive controls, which we synthesize by modifying negative controls. We show that our CI calibration restores nominal characteristics, such as 95% coverage of the true effect size by the 95% CI. We furthermore show that CI calibration reduces disagreement in replications of two pairs of conflicting observational studies: one related to dabigatran, warfarin, and gastrointestinal bleeding and one related to selective serotonin reuptake inhibitors and upper gastrointestinal bleeding. We recommend CI calibration to improve reproducibility of observational studies.