Hello SAS experts, I have a dataset and would like to identify an individual's true disease type based on the following:   If an individual has Type A or B, select the record closest to the reference date based on service start or end date. If an individual only has "Unspecified" and no valid A or B, retain the "Unspecified" record. The reference date is the same for each individual. Each individual should appear only once in the final output dataset (ie one line per individual ID)   Below is the dataset I have and the expected output.     data WORK.SUBTYPE_SAMPLE; infile datalines dsd truncover; input ID:BEST12. Type:$12. Reference_date:DATE9. service_start:DATE9. service_end:DATE9.; format ID BEST12. Reference_date DATE9. service_start DATE9. service_end DATE9.; datalines; 1 A 04JAN2016 10JAN2016 21JAN2016 1 B 04JAN2016 09JUL2018 09NOV2019 1 Unspecified 04JAN2016 06JAN2016 10FEB2016 2 B 08JUN2019 08DEC2019 19DEC2019 2 Unspecified 08JUN2019 22OCT2019 09AUG2019 3 Unspecified 02FEB2017 02APR2017 15APR2017 4 A 01JAN2020 03MAR2020 24MAR2020 4 A 01JAN2020 05MAY2018 10MAY2018 4 Unnspecified 01JAN2020 02JAN2020 03JAN2020 5 A 09SEP2016 11NOV2016 15NOV2016 5 B 09SEP2016 09SEP2016 10NOV2016 6 A 03MAR2016 30AUG2016 02NOV2016 6 A 03MAR2016 14OCT2016 19OCT2016 6 A 03MAR2016 26MAR2016 19DEC2016 6 Unspecified 03MAR2016 20OCT2016 21OCT2016 6 Unspecified 03MAR2016 12DEC2016 28DEC2016 6 B 03MAR2016 28JUN2016 15AUG2016 7 B 10OCT2022 11OCT2022 14NOV2022 8 Unspecified 01JAN2019 05MAY2019 06MAY2019 8 Unspecified 01JAN2019 07MAY2019 08MAY2019 ;;;;     Want: Id true_type 1 A 2 B 3 Unspecified 4 A 5 B 6 A 7 B 8 Unspecified   Thank you ... View more

Hello,   I am trying to parse out the drug name, strength, and unit variable for specific medications only (Amantadine, Carbidopa, Entacapone, Apomorphine, Trihexyphenidyl, Amantadine, Trihexyphenidyl, and levodopa). The final aim is to calculate the daily dose of these medications. I have tried using the scan, compress followed by the  coalescec option to no avail. 1) Things to note a) Use of different delimeters "-" and "/" for the strength variable, (b) different position of drug of interest : position1/position2/position3.   I have included my data and table desired.   Thank you for your assistance.       data WORK.HAVE; infile datalines dsd truncover; input Patient_ID:32. Drug_Name:$37. Strength:$12.; label Patient_ID="Patient ID" Drug_Name="Drug_Name" Strength="Strength"; datalines; 1 Carbidopa 25 MG 1 Carbidopa/Levodopa 25-100 MG 2 Levodopa/Entacapone 100-200 MG 2 Apomorphine 2 MG/ML 2 Ropinirole/Entacapone 2-200 MG 3 Levodopa/Entacapone/Ropinirole 100-200-2 MG 3 Pramipexole/Entacapone/Amantadine 1-200-100 MG 3 Pramipexole/Trihexyphenidyl 1-2 MG 4 Amantadine/Benztropine 100-1 MG 5 Trihexyphenidyl/Rasagiline/Entacapone 2-0.5-200 MG ;;;;     Want Patient ID Drug_of_Interest Strength1 Unit1 Drug of interest 2 Strength2 Unit2 1 Amantadine 100 MG   . . 1 Carbidopa 25 MG Levodopa 100 MG 2 Entacapone 200 MG   . . 2 Apomorphine 2 MG/ML   . . 2 Entacapone 200 MG   . . 3 Entacapone 200 MG       3 Entacapone 200 MG Amantadine 100 MG 3 Trihexyphenidyl 2 MG . . . 4 Amantadine 100 MG . . . 5 Trihexyphenidyl 2 MG Entacapone 200 MG ... View more

Hi SAS Experts,   I am trying to calculate readmissions within 30days post first MS diagnosis based on the following conditions           1) Discharge date is not the same as the index admission date. For instance, 2JAN20 cannot be used as index admission because patients was discharged on same day. 2) Index admission date is used once for patients with multiple readmissions Specifically, I would like to identify: 1) Readmissions within 30 days as a binary variable yes=1 and no=0 2) For each patient, calculate the number of readmissions that occur within 30 days. 3) For readmissions meeting the "within" 30 day readmission criteria, identify the setting they were readmitted to  4) Gap: the gap between the current admission date and the immediate previous discharge date   I have provided a sample data below and desired output. In the data, MS diagnosis is named MSflag and coded 1. Claimstartdate is the first date of the MS claim (in most cases is the same as admission date but in some cases its not, hence the interest in readmission post first MS flag).   Thank you   data WORK.IMPORT2; infile datalines dsd truncover; input ID:BEST. Claimstartdate:DATE9. Admitdate:DATE9. Dischargedate:DATE9. MSFlag:BEST. Setting:$4.; format ID BEST. Claimstartdate DATE9. Admitdate DATE9. Dischargedate DATE9. MSFlag BEST.; label ID="ID" Claimstartdate="Claimstartdate" Admitdate="Admitdate" Dischargedate="Dischargedate" MSFlag="MSFlag" Setting="Setting"; datalines; 1 26APR2020 26APR2020 28APR2020 1 IP 1 16JUN2020 16JUN2020 28APR2020 1 SNF 2 02JAN2020 02JAN2020 02JAN2020 1 IP 2 04FEB2020 04FEB2020 10FEB2020 1 IP 2 15FEB2020 18JUN2020 15AUG2020 1 IP 3 02JAN2020 02JAN2020 22FEB2020 1 Home 3 15NOV2020 15NOV2020 20DEC2020 1 ER 4 04MAR2020 04MAR2020 14MAY2020 1 ER 5 26AUG2020 26AUG2020 13SEP2020 1 Home 5 15SEP2020 15SEP2020 20NOV2020 1 ER 6 01JAN2020 05JAN2020 08JAN2020 1 IP 6 11JAN2020 12JAN2020 18JAN2020 1 ER 6 05JUN2020 05JUN2020 15JUN2020 1 IP 6 19JUN2020 19JUN2020 05JUL2020 1 SNF 6 15SEP2020 15SEP2020 25SEP2020 1 IP 6 01NOV2020 01NOV2020 05NOV2020 1 Home 7 06MAR2020 06MAR2020 09MAR2020 1 IP 8 02JAN2020 02JAN2020 08JAN2020 1 IP 9 16JUL2020 19JUL2020 20JUL2020 1 SNF 10 01AUG2020 10AUG2020 22AUG2020 1 IP 11 26OCT2020 26OCT2020 30OCT2020 1 IP 12 21FEB2020 21FEB2020 24FEB2020 1 IP 12 27FEB2020 27FEB2020 25JUN2020 1 SNF 13 11JAN2020 11JAN2020 18JAN2020 1 IP 13 20MAR2020 20MAR2020 26MAR2020 1 IP 13 28MAR2020 28MAR2020 10JUN2020 1 IP 13 15JUN2020 15JUN2020 27DEC2020 1 SNF 14 14MAR2020 14MAR2020 18MAR2020 1 IP 15 11SEP2020 12SEP2020 22SEP2020 1 IP 16 10FEB2020 10FEB2020 11FEB2020 1 IP 16 15FEB2020 15FEB2020 04MAY2020 1 HSPC ;;;;   ID Claim_start_date Admit_date Discharge_date MS Flag Setting Readmitted Within 30 days No of Readmissions Setting Readmiited to GAP Explanation 2 2-Jan-20 2-Jan-20 2-Jan-20 1 IP No . . . Not index admission date beacause patient was discharged on same day 2 4-Feb-20 4-Feb-20 10-Feb-20 1 IP No . . 33   2 15-Feb-20 18-Jun-20 15-Aug-20 1 IP Yes 1 IP 129   3 2-Jan-20 2-Jan-20 22-Feb-20 1 Home No . . .   3 15-Nov-20 15-Nov-20 20-Dec-20 1 ER No . . 267   4 4-Mar-20 4-Mar-20 14-May-20 1 ER No . . .   5 26-Aug-20 26-Aug-20 13-Sep-20 1 Home No . . .   5 15-Sep-20 15-Sep-20 20-Nov-20 1 ER Yes 1 ER 2   6 1-Jan-20 5-Jan-20 8-Jan-20 1 IP No . . .   6 11-Jan-20 12-Jan-20 18-Jan-20 1 ER Yes 1 ER 4   6 5-Jun-20 5-Jun-20 15-Jun-20 1 IP No 1 . 139   6 19-Jun-20 19-Jun-20 5-Jul-20 1 SNF Yes 2 SNF 4   6 15-Sep-20 15-Sep-20 25-Sep-20 1 IP No 2 . 72   6 1-Nov-20 1-Nov-20 5-Nov-20 1 Home No 2 . 37   7 6-Mar-20 6-Mar-20 9-Mar-20 1 IP No . . .   8 2-Jan-20 2-Jan-20 8-Jan-20 1 IP No . . .   9 16-Jul-20 19-Jul-20 20-Jul-20 1 SNF No . . .   10 1-Aug-20 10-Aug-20 22-Aug-20 1 IP No . . .   11 26-Oct-20 26-Oct-20 30-Oct-20 1 IP No . . .   12 21-Feb-20 21-Feb-20 24-Feb-20 1 IP No . . .   12 27-Feb-20 27-Feb-20 25-Jun-20 1 SNF Yes 1 SNF 3   13 11-Jan-20 11-Jan-20 18-Jan-20 1 IP No . . .   13 20-Mar-20 20-Mar-20 26-Mar-20 1 IP No . . 62   13 28-Mar-20 28-Mar-20 10-Jun-20 1 IP Yes 1 IP 2   13 15-Jun-20 15-Jun-20 27-Dec-20 1 SNF Yes 2 SNF 5   14 14-Mar-20 14-Mar-20 18-Mar-20 1 IP No . . .   15 11-Sep-20 12-Sep-20 22-Sep-20 1 IP No . . .   16 10-Feb-20 10-Feb-20 11-Feb-20 1 IP no . . .   16 15-Feb-20 15-Feb-20 4-May-20 1 HSPC Yes 1 HSPC 4       ... View more