BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
cdubs
Quartz | Level 8

Hi all, 

 

I've been given an algorithm to select patients who have a certain type of illness. Given a set of ICD-9 codes + inclusion procedure codes, + other criteria (age, region, etc). 

 

Generally with claims data (this is Truven) -- should I clean the entire set first, and then isolate my sample, or isolate my sample and then clean?

 

Thanks, 

1 ACCEPTED SOLUTION

Accepted Solutions
ballardw
Super User

I agree in general with @Reeza but experience has taught me if age is involved to always at least check it early in any process where it is important.

Finding data like date of birth after the date a service is performed or age (not to mention gender) inappropriate services might be a concern.

 

You may also have to consider age at time of service vs age at data extract depending on your data systems. Many systems will maintain demographics such as birth date separately from services and may calculate an age based on the date of the extract for each record even though the services were on different dates.

View solution in original post

2 REPLIES 2
Reeza
Super User

@cdubs wrote:

Hi all, 

 

I've been given an algorithm to select patients who have a certain type of illness. Given a set of ICD-9 codes + inclusion procedure codes, + other criteria (age, region, etc). 

 

Generally with claims data (this is Truven) -- should I clean the entire set first, and then isolate my sample, or isolate my sample and then clean?

 

Thanks, 


Depends on your cleaning process. If the cleaning process can affect selection then it needs to go first. 

ballardw
Super User

I agree in general with @Reeza but experience has taught me if age is involved to always at least check it early in any process where it is important.

Finding data like date of birth after the date a service is performed or age (not to mention gender) inappropriate services might be a concern.

 

You may also have to consider age at time of service vs age at data extract depending on your data systems. Many systems will maintain demographics such as birth date separately from services and may calculate an age based on the date of the extract for each record even though the services were on different dates.

hackathon24-white-horiz.png

The 2025 SAS Hackathon has begun!

It's finally time to hack! Remember to visit the SAS Hacker's Hub regularly for news and updates.

Latest Updates

How to connect to databases in SAS Viya

Need to connect to databases in SAS Viya? SAS’ David Ghan shows you two methods – via SAS/ACCESS LIBNAME and SAS Data Connector SASLIBS – in this video.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 2 replies
  • 1302 views
  • 4 likes
  • 3 in conversation