While I understand that Achilles (and its components) and DQD provide some ways to assess the data quality of the CDM dataset. My questions are as below
a) Can Achilles and DQD be used on non-CDM datasets as well? If yes, can share any doc or example on how it is done? I did go through Achilles Github but couldn’t find on non-cdm data quality assessment
b) the only difference between Achilles and DQD is that DQD has very exhaustive rules coverages for data quality check whereas Achilles (heel) has a limited set of rules.
c) While I did read this stmt in github
Some Heel rules can be generalized to non-OMOP datasets. Other rules are dependant on OMOP concept ids and a translation of the code to other CDMs would be needed (for example rule with rule_id of 29 uses OMOP specific concept;concept 195075). - May I check does this mean, we can use the same R package to evaluate data quality on non-omop dataset. Is there any other tutorial on how to use it for non-cdm dataset?
Also tagging @Ajit_Londhe as I have benefitted through your related posts on Achilles in the forum. Would really be helpful if you can help me with this?