Advice on how best to manage this dataset? - database

Question

New to SAS and would appreciate advice and help on how best to handle this data mangement situation.
I have a dataset in which each observation represents a client. Each client has a "description" variable which could include either a comprehensive assessment, treatment or discharge. I have created 3 new variables to flag each observation if they contain one of these.
So for example:
treat_yes = 1 if description contains "tx", "treatment"
dc_yes = 1 if description contains "dc", "d/c" or "discharge"
ca_yes = 1 if desciption contains "comprehensive assessment" or "ca" or "comprehensive ax"
My end goal is to have a new dataset of clients that have gone through a Comprehensive Assessment, Treatment and Discharge.
I'm a little stumped as to what my next move should be here. I have all my variables flagged for clients. But there could be duplicate observations just because a client could have come in many times. So for example:
Client_id treatment_yes ca_yes dc_yes
1234 0 1 1
1234 1 0 0
1234 1 0 1
All I really care about is if for a particular client the variables treatment_yes, ca_yes and dc_yes DO NOT equal 0 (i.e., they each have at least one "1". They could have more than one "1" but as long as they are flagged at least once).
I was thinking my next step might be to collapse the data (how do you do this?) for each unique client ID and sum treatment_yes, dc_yes and ca_yes for each client.
Does that work?
If so, how the heck do I accomplish this? Where do I start?
thanks everyone!

Answer 1

I think the easiest thing to do at this point is to use a proc sql step to find the max value of each of your three variables, aggregated by client_id:
data temp;
input Client_id $ treatment_yes ca_yes dc_yes;
datalines;
1234 0 1 1
1234 1 0 0
1234 1 0 1
;
run;
proc sql;
create table temp_collapse as select distinct
client_id, max(treatment_yes) as treatment_yes,
max(ca_yes) as ca_yes, max(dc_yes) as dc_yes
from temp
group by client_id;
quit;
A better overall approach would be to use the dataset you used to create the _yes variables and do something like max(case when desc = "tx" then 1 else 0 end) as treatment_yes etc., but since you're still new to SAS and understand what you've done so far, I think the above approach is totally sufficient.

Answer 2

The following code allows you to preserve other variables from your original dataset. I have added two variables (var1 and var2) for illustrative purposes:
data temp;
input Client_id $ treatment_yes ca_yes dc_yes var1 var2 $;
datalines;
1234 0 1 1 10 A
1234 1 0 0 11 B
1234 1 0 1 12 C
;
run;
Join the dataset with itself so that each row of a client_id in the original dataset is merged with its corresponding row in an aggregated dataset constructed in a subquery.
proc sql;
create table want as
select *
from temp as a
left join (select client_id,
max(treatment_yes) as max_treat,
max(ca_yes) as max_ca,
max(dc_yes) as max_dc
from temp
group by client_id) as b
on a.client_id=b.client_id;
quit;