topic Re: Identifying events that will happen multiple time and information about each in SAS Programming

Identifying events that will happen multiple time and information about each

weweaw — Fri, 12 May 2017 19:08:39 GMT

I really don't know where to begin but I've been trying and failing for days.

The end is I need to count how many times type a happened 90 days before type b, but there cannot be any other type b's 90 days before. I can do this if I'm only looking at one instance of type b. I did then by adding a new var of the date of type b of a person's to all their other claims. I have a very crude idea how to do this for all but I'm hoping for a more elegant solution. Here are the funny parts of my data: type b can happen multiple times in the same claim so day and in that case I would treat it as one type b event. A person can also have many type b's, I think it can be as high as 150 of them. So I need to mark the b events that have no other b events 90 days before so then I can count the type a events that happened in that window. In my real data type a can be many types and I will need to have how many time a type a happened and what category the type a was.

ID	Claim_ID	Claim_line	Date	Type
1	1	1	11-Feb	a
1	2	1	11-Mar	b
1	2	2	11-Mar	b
1	2	3	11-Mar	a
1	3	1	11-Jun	b
1	3	2	11-Jun	a
1	3	3	11-Jun	a
1	4	1	3-Jul	a
1	5	1	6-Jun	a
1	6	1	9-Sep	b
2	1	1	8-Aug	a
2	2	1	10-Sep	b
2	3	1	30-Nov	a
2	4	1	11-Dec	b

Re: Identifying events that will happen multiple time and information about each

kiranv_ — Fri, 12 May 2017 19:30:43 GMT

can you also please show how your output looks like for a particular scenario.

Re: Identifying events that will happen multiple time and information about each

Reeza — Fri, 12 May 2017 19:34:07 GMT

Search using either Google or the Forum: "30 day readmission"

There are several methods that can be implemened - usually using SQL processing.

Re: Identifying events that will happen multiple time and information about each

weweaw — Fri, 12 May 2017 19:41:57 GMT

I added a few rows to show when there is a type b within 90 days of another and how then the type a would not count and type be would be marked as bad.

I'm not even for sure but I think this would do it. I will need to be able to calculate what is the average number of a's for each good b event and also what is the total good type a's.

ID	Claim_ID	Claim_line	Date	Type	Type_b_good	typeb_number	in_90_good
1	1	1	11-Feb	a	.	.	1
1	2	1	11-Mar	b	1	1	0
1	2	2	11-Mar	b	0	2	0
1	2	3	11-Mar	a	.	.	1
1	3	1	11-Jun	b	1	3	0
1	3	2	11-Jun	a	.	.	0
1	3	3	11-Jun	a	.	.	0
1	4	1	3-Jul	a	.	.	0
1	5	1	6-Jul	a	.	.	0
1	6	1	9-Sep	b	1	4	0
2	1	1	8-Aug	a	.	.	1
2	2	1	10-Sep	b	.	1	0
2	3	1	30-Nov	a	.	.	1
2	4	1	11-Dec	b	1	2	0
2	5	1	12-Dec	a	.	.	0
2	6	1	13-Dec	b	0	3	0