Hello,
I’d like to find a solution to the following problem - preferably using pivot tables, but I can also use a work around with the raw data before running the pivot table if needed:
Essentially, my data lists medical encounters with criteria such as date of service, service code, client name, clinician name, and so on.
In any particular data set, there are likely to be numerous entries for the same client (with different dates, service codes, etc)
I’d like to find a way to remove data (or omit in the pivot field) based on these conditions:
If client A shows service code 90791, count the code towards total appointments for client A. If client A shows a code 90791, but also shows code 96101 in ANY other row of data, remove all records (or omit all data) for client A that will impact the pivot table.
I’m not sure if this is a filtering issue, or potentially could be used with the index/match function - any help would be greatly appreciated!
I’d like to find a solution to the following problem - preferably using pivot tables, but I can also use a work around with the raw data before running the pivot table if needed:
Essentially, my data lists medical encounters with criteria such as date of service, service code, client name, clinician name, and so on.
In any particular data set, there are likely to be numerous entries for the same client (with different dates, service codes, etc)
I’d like to find a way to remove data (or omit in the pivot field) based on these conditions:
If client A shows service code 90791, count the code towards total appointments for client A. If client A shows a code 90791, but also shows code 96101 in ANY other row of data, remove all records (or omit all data) for client A that will impact the pivot table.
I’m not sure if this is a filtering issue, or potentially could be used with the index/match function - any help would be greatly appreciated!