LTHTR-DST / hdruk_avoidable_admissions

HDRUK Data Science Collaboration on Avoidable Admissions in the NHS.
https://lthtr-dst.github.io/hdruk_avoidable_admissions/
MIT License
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Pulling edchiefcomplaint members from HDRUK V2 Google sheet #37

Closed MattStammers closed 1 year ago

MattStammers commented 1 year ago

https://docs.google.com/spreadsheets/d/18XbVmWJsccACoTDFd8EBeslKPtsPApqi/edit#gid=589962562

vvcb commented 1 year ago

Thanks @MattStammers .

I think #36 that @ccarenzoIC raised is subtly different and is around the feature engineering aspect.

Moreover, it will also break the current workflow around how missing or erroneous codes that are not in a refset are labelled.

Please see feature_maps.py for how this is achieved through a combination of the {category:[array of codes]} dictionaries that appear later in the same module and the refset members data that appears in nhsdd_snomed.py.

nhsdd_snomed.py is meant to be autogenerated using nhsdd_generator.py.

Happy to jump on a quick call this afternoon if it will help.

MattStammers commented 1 year ago

Don't merge it if it will break the rest of the workflow. If @ccarenzoIC is also working on this then prioritize what she is doing as she has been working on this for far longer than I have (just tinkering with it this morning)

ccarenzoIC commented 1 year ago

Yes, mine as @vvcb if for the feature engineering part. I will work on this during the week.

Thanks,

ccarenzoIC commented 1 year ago

On my side, will push the feature engineering code for grouping the chief complaint (https://github.com/LTHTR-DST/hdruk_avoidable_admissions/issues/36) tomorrow morning and let you know if I'm facing any problem. Apologies, got delayed with other projects

ccarenzoIC commented 1 year ago

On my side, will push the feature engineering code for grouping the chief complaint (#36) tomorrow morning and let you know if I'm facing any problem. Apologies, got delayed with other projects

https://github.com/LTHTR-DST/hdruk_avoidable_admissions/pull/40