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OHDSI Informatics Study: DQD Lab Thresholds


(Vojtech Huser) #1

I am seeking sites who would be willing to run a new OHDSI network study. (a methods study (subtype informatics study))

This study supports DataQualityDashboard. The goal is to do DQA (data quality assessment) of laboratory values.

See study protocol here: https://github.com/vojtechhuser/DataQuality/tree/master/extras/protocol
Study github is here: https://github.com/vojtechhuser/DataQuality

The study was piloted on DQD forum thread but, for updates, I created this new thread to keep things better organized.

(Vojtech Huser) #2

March 10 updates

6 sites (and datasets) were analyzed in the study so far.

Central Processing code is here: https://github.com/vojtechhuser/DataQuality/blob/master/extras/CentralProcessingDQDThresholds.R

The preliminary results are being summarized in an emerging AMIA 2020 abstract. (AMIA deadline extension is helping)

The study analyzes 5943 distinct lab-unit pairs. A total of 1350 lab-unit pairs have data from 2+ sites allowing production of benchmark data.

The study is in great need of non-US datasets. (e.g., from Europe or Asia or elsewhere).

Please join the study ! The package no longer depends on Achilles and you just need table MEASUREMENT (v5 and v6 CDM versions should work)

(Thomas Falconer) #3

Hi @Vojtech_Huser, if you need/want additional US data, Columbia would be happy to participate. Let me know!

(Vojtech Huser) #4

The AMIA abstract was submitted. COVID19 showed additional importance of similar data quality checking (as for values) for value_as_concept_id filed. Yesterday, the ‘Thresholds and Values Study’ was updated to include this additional data quality focus. A new step was added in addition to DataQuality::dashboardLabThresholds() called DataQuality::dashboardLabValueAsConceptID(). Updated protocol was published. I am looking for sites that are willing to execute the v5.0 of the study. Existing sites must update the package and check that they are using v5.0.

The extracted data for dashboardLabValueAsConceptID are done as percentages so the site is not revealing the actual counts of the test. Only the ratio of result values. For example for blood type group, you don’t reveal number of tests, just the fact that x% of results indicate coded value: ABnegative. This should facilitate greater site participation in the study.

The instructions to run the study remain the same and can be found at https://github.com/vojtechhuser/DataQuality/#support-development-of-data-quality-dashboard-dqd