Hi All,
For each member number we need to look at the discharge date should be less than 30 days of the next admit date, if so Y else N on the Readmission variable. Please let me know how to apply date logic for this.
Member_Number Claim_ID Admit_Date Discharge_Date Readmission
420000000694600 0102241579644 2/15/2015 2/19/2015
420000000694600 0102121583902 2/2/2015 2/6/2015
420000000694600 0101161597102 1/6/2015 1/8/2015
420000009817200 0106101514987 5/26/2015 5/28/2015
420000009817200 0105051585970 4/18/2015 4/24/2015
420000009817200 0104151510931 4/1/2015 4/3/2015
420000009817200 0103241584788 3/10/2015 3/14/2015
Thanks for your help.
Hi,
Something like this, assuming dates are date format, and data is sorted.
data want;
set have;
if lag(member_number)=member_number and admit_date - 30 <= lag(discharge_date) <= admit_date then result="Y";
else if lag(member_number)=member_number then result="N";
run;
Hi, Thanks for your reply. It doesn't the satisfy the required condition. Your output looks like as below,
MEMBER CLAIM ADMIT DISCHARGE result
420000000694600 0102241579646 7/10/2015 7/12/2015
420000000694600 0102241579645 6/15/2015 6/19/2015 N
420000000694600 0102241579644 2/15/2015 2/19/2015 N
420000000694600 0102121583902 2/2/2015 2/6/2015 N
420000000694600 0101161597102 1/6/2015 1/8/2015 N
420000009817200 0106101514987 5/26/2015 5/28/2015
420000009817200 0105051585970 4/18/2015 4/24/2015 N
420000009817200 0104151510931 4/1/2015 4/3/2015 N
420000009817200 0103241584788 3/10/2015 3/14/2015 N
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.