Information
Click on a row to explore the results for that model. When you wish to explore a different model, then select the new result row and the tabs will be updated.
Demo VideoOHDSI Covid-19 Simple Models Results
The Observational Health Data Sciences and Informatics (OHDSI) international community is hosting a COVID-19 virtual study-a-thon this week (March 26-29) to inform healthcare decision-making in response to the current global pandemic. The preliminary research results on this web-based application are from a retrospective, real-world, observational study in support of this activity and will subsequently be submitted to a peer-reviewed, scientific journal.
This shiny application contains the results of the simple models that were developed to assess the performance loss that occurs on various OHDSI COVID19 prediction problems.
During manuscript development and the subsequent review period, these results are considered under embargo and should not be disclosed without explicit permission and consent from the authors.
Below are links for study-related artifacts that have been made available as part of this study:
Protocol: link
Development Status: Under Development
Study lead: Jenna Reps, Ross Williams, Peter Rijnbeek
Study lead forums tag: jreps, RossW, Rijnbeek
App Instructions
Click on the ‘Summary’ button in the left hand menu to see a table where each row corresponds to a result where a model has been valdiated on some data. Clicking on a row then populates the ‘Performance’ and ‘Model’ buttons with that specific result (you can view more details of the evaluation that the row corresponds to). See the ‘Help’ button for a youtube video demostrating the shiny app.
Database Information
- Development Database: OptumDoD, MDCR
- Validation Databases: AUSOM, CCAE, MDCD, MDCR, JMDC, IPCI, optumEhr, optumDoD, Tufts, SIDIAP, HIRA, AU_ePBRN
Abstract
Below is the abstract of the manuscript that summarizes the findings:
Background:
Methods:
Results:
Discussion:
Packages
Data Information
The following databases were used in this study:
| Database | Name | Country | Type | Years |
|---|---|---|---|---|
| OptumDoD | Optum® De-Identified Clinformatic Data Mart Database – Date of Death (DOD) | USA | Claims | 2000-2019 |
| AUSOM | Ajou University School of Medicine Database | Korea | EHR | 1999-2018 |
| CCAE | IBM MarketScan® Commercial Database | USA | Claims | 2000-2019 |
| MDCD | IBM MarketScan® Multi-State Medicaid Database | USA | Claims | 2006-2019 |
| MDCR | IBM MarketScan® Medicare Supplemental Database | USA | Claims | 2000-2019 |
| JMDC | Japan Medical Data Center | Japan | Claims | 2000-2019 |
| IPCI | Integrated Primary Care Information | Netherlands | GP | 2006-2020 |
| optumEhr | Optum® de-identified Electronic Health Record Dataset | USA | EHR | 2006-2019 |
| Tufts - CLARET | Clinical Academic Research Enterprise Trust (CLARET) | USA | EHR | 2006-2020 |
| SIDIAP | The Information System for Research in Primary Care (SIDIAP) | Spain | GP | 2016-2020 |
| HIRA | Health Insurance and Review Assessment | Korea | Claims | 2013-2020 |
| AU_ePBRN | electronic Practice Based Research Network | Australia | EHR (GP + Hospital) | 2012-2019 |
All databases obtained IRB approval or used deidentified data that was considered exempt from IRB approval.