Hi, I have a data set that tracks unique person identifier, and number of activities they had on a website and call center per YearMonth. An example below, I have the first 4 variables. What I would like to do is flag the YearMonth where the FIRST event occurred and populate the variable with 1 and 0 otherwise. Also my actual data set has multiple years of data.     Have Want PersonID YearMonth Logons Calls FirstLogon FirstCall A 201701 0 5 0 1 A 201702 0 0 0 0 A 201703 0 0 0 0 A 201704 1 0 1 0 A 201705 5 1 0 0 A 201706 0 0 0 0 A 201707 0 0 0 0 A 201708 2 0 0 0 A 201709 1 0 0 0 A 201710 0 2 0 0 A 201711 2 0 0 0 A 201712 1 0 0 0 ... View more

I have a rather complex merge operation I am trying to perform on inpatient and outpatient medical claims.   The basic idea is once a patient has been discharged from an inpatient hospital stay, identify the first consecutive outpatient PCP visit, and the first consecutive outpatient Specialist visit. There may be many but I only want the first for each. If there are none, then it should be tracked as a missing value. There may be many discharges for the same patient. If the next consecutive inpatient row for the patient has a readmission_flag = Y, then I'd like to track that too.   I am wondering if advice can be offered on how to do this, either by setting up the initial data steps differently, or by creating a merge with several considerations. Thank you for your help.     Have - Inpatient                   Patient_ID Diagnostic_Category Type_of_Service Admit_Date Discharge_Date Readmission_Flag         A Nervous System Medical 21-Jan-16 15-Feb-16           A Circulatory System Surgical 15-Jul-16 21-Jul-16           A Infection Medical 31-Jul-16 2-Aug-16 Y                             Have - Outpatient                 Patient_ID Type_of_Service OP_Visit_DT PROVIDER             A Lab 1-Jan-16 Specialist             A Office Visit 15-Jan-16 PCP             A Office Visit 18-Feb-16 Specialist             A Office Visit 20-Feb-16 PCP             A Office Visit 22-Feb-16 PCP             A Office Visit 15-Mar-16 Specialist             A Office Visit 12-Sep-16 Specialist             A Office Visit 1-Oct-16 Specialist                                                     Merged- Want                   Patient_ID Diagnostic_Category Type_of_Service Admit_Date Discharge_Date First_OP_Visit_Specailist_Dt First_OP_Visit_Specailist_TOS First_OP_Visit_PCP_Dt First_OP_Visit_PCP_TOS Resulted _Readmission A Nervous System Medical 21-Jan-16 15-Feb-16 18-Feb-16 Office Visit 20-Feb-16 Office Visit   A Circulatory System Surgical 15-Jul-16 21-Jul-16 12-Sep-16 Office Visit na na Y A Infection Medical 31-Jul-16 2-Aug-16 12-Sep-16 Office Visit na na   ... View more

I have a tricky problem collapsing inpatient hospital admissions and haven't had success getting a solution from previous blog posts. What I would like to do, is collapse rows where the ADMISSION_START_DT = the ADMISSION_END_DT of the preceeding row. The idea is that this is really one admission. In this event I would like to keep the APR_MDC_DESC and HOSPITAL_ID from the more current, second row.   In the event that the ADMISSION_START_DT is < 15 days from the ADMISSION_END_DT from the preceeding row, I would like to populate a new variable, READMIT_FLAG_15_DAY so that we can track readmissions.    I have some sample data below. Any help would be greatly appreciated.     Have PATIENT_ID ADMISSION_START_DT ADMISSION_END_DT APR_MDC_DESC SERVICE_CAT HOSPITAL_ID ABC 24-Nov-15 26-Nov-15 Diabetes MED 123 ABC 26-Nov-15 3-Dec-15 Surgery SURG 456 ABC 16-Jan-16 22-Jan-16 Hypertension  MED 123 ABC 25-Feb-16 29-Feb-16 Diabetes MED 123 ABC 29-Feb-16 29-Feb-16 Observation MED 123 ABC 2-Mar-16 2-Mar-16 Hypertension  MED 123 ABC 19-Mar-16 23-Mar-16 Observation MED 123   Want PATIENT_ID ADMISSION_START_DT ADMISSION_END_DT APR_MDC_DESC SERVICE_CAT HOSPITAL_ID READMIT_FLAG_15_DAY ABC 24-Nov-15 3-Dec-15 Surgery MED 456   ABC 16-Jan-16 22-Jan-16 Hypertension  MED 123   ABC 25-Feb-16 29-Feb-16 Observation MED 123   ABC 2-Mar-16 2-Mar-16 Hypertension  MED 123   ABC 19-Mar-16 23-Mar-16 Observation MED 123 Y ... View more

SAS Community,   I am trying to solve a merging problem. Data set Have1 is a table with hospital admission and discharge dates. Have2 is a table of outpatient office visit dates.   What I want to do, is merge the two in such a way: For each row where a person/discharge date on Have1, join the date of the first subsequent office visit from Have2. A patient may have several, but I just want to add the first.   A second component that is a bit tricky, is if a person is readmitted to the hospital before they have an outpatient office visit, then the Soonest Follow Up_ Office Visit Date should be left blank, and a flag for readmission set to "Y". In the example below, the patient was discharged on Sept 3. The first subsequent office visit was on Sep 20, however an admission occured prior to this office visit on Sept 5. So in this case I don't want to populate the Soonest Follow Up field, since the person didn't follow up because they were back in the hospital.   Any help is greatly appreciated. Thank you.   Have 1     Person Admit _date Discharge Date A 30APR2015 01MAY2015 A 02SEPT2015 03SEPT2015 A 05SEPT2015 07SEPT2015 A 11NOV2015 12NOV2015 A 19DEC2015 21DEC2015   Have 2   Person Office Visit Date A 01JAN2015 A 02JUNE2015 A 15JUL2015 A 20SEPT2015 A 20NOV2015 A 05DEC2015   Want           Person Admit _date Discharge Date Soonest Follow Up_ Office Visit Date Admitted Prior to Office Visit   A 30APR2015 01MAY2015 02JUNE2015 N /*June 2 was the first office visit that occurred after this discharge*/ A 02SEPT2015 03SEPT2015   Y /*The patient was readmitted before the first most recent office visit. No date populated, admitted flag set to Y*/ A 05SEPT2015 07SEPT2015 20SEPT2015 N /*Sept 20 was the first office visit that occurred after this discharge*/ A 11NOV2015 12NOV2015 20NOV2015 N /*Nov 20 was the fist office visit that occurred after this discharge*/ A 19DEC2015 21DEC2015   N /*no office visits had a date that was after this discharge. Value is left blank*/ ... View more