Hi guys, I have a dataset of medication pick-up dates for a list of patients that I am trying to reformat. There are a total of 4 different drugs in the dataset. Each line is a unique person (key variable = id), each time they pick up a new drug at the pharmacy a new drugX_startdate and a corresponding drugX_enddate is added in wide format to the dataset. Sometimes the drug periods overlap (e.g. drugB_startdate1 is before drugA_enddate1). Most of the patients are only on one of the 4 drugs and will just have missing data on the other drugs. I want to get rid of the drug names and just get them all sorted as drug_start1-etc drug_end1-etc such that all patients in the dataset have a drug_start1 corresponding to whichever drug they start on. It varies from 0 to 45 on the number of pick-ups for any of the 4 drugs.   The dataset is currently in the format: id drugA_start1 drugA_start2 drugA_start3 drugA_end1 drugA_end2 drugA_end3 drugB_start1 drugB_end1 etc 1.  01JAN2000  01FEB2000  01MAR2000  10JAN2000  10FEB2000 18MAR2000 02APR2000   20APR2000 2.  01AUG2001  01SEP2001           .          20AUG2001  18SEP2001           .          01JAN2001   31JAN2001 3.           .                     .                    .                    .                      .                  .          01JAN2002   15FEB2002 4.  01JAN2003  01FEB2003  01MAR2003  10JAN2003  10FEB2003 18MAR2003            .                    . Only there are many more startdates and enddates for each drug and there are a total of 4 different drugs.   I want to reformat the dataset into the following chronological order and get rid of the drug-specific prefix but such that drug_stat(x) still corresponds to drug_end(x): id   drug_start1   drug_start2   drug_start3   drug_start4  (etc) drug_end1  drug_end2   drug_end3   drug_end4 (etc) 1.  01JAN2000  01FEB2000  01MAR2000  02APR2000        10JAN2000 10FEB2000 18MAR2000 20APR2000 2.  01JAN2001  01AUG2001  01SEP2001            .                 31JAN2001 20AUG2001 18SEP2001          .        3.  01JAN2002           .                      .                    .                 15FEB2001          .                  .                     . 4.  01JAN2003  01FEB2003  01MAR2003            .                 10JAN2003  10FEB2003  18MAR2003        .   I hope this makes sense 🙂 In the end I need to calculate the proportion of time on any medication as the number of days on medication/total days in period which is why I need the data like this. Can anyone give me some guidance on how to reformat the data like this? Thanks in advance! ... View more