feat: 🚧 skeleton of the core diabetes classification #142
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Aastedet
reviewed
Sep 19, 2024
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| # Exclusion steps ----- | ||
| exclusions <- gld_purchases |> |
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maybe name the output gld_hba1c_after_exclusions or something similar?
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| classify_t1d <- function(data) { | ||
| # data |> | ||
| # get_has_t1d_primary_diagnosis() |> | ||
| # get_only_insulin_purchases() |> | ||
| # get_majority_of_t1d_primary_diagnosis() |> | ||
| # get_insulin_purchases_within_180_days() |> | ||
| # get_insulin_is_two_thirds_of_gld_purchases() | ||
| } |
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If it is still present in the classify_diabetes() function environment, then adding the gld_hba1c_after_exclusions object as an input to get_insulin_purchases_within_180_days() would allow us to reuse the post-exclusion GLD data to assess insulin purchases in relation to the date of diabetes variable. This could be a way to solve what we discussed earlier today.
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Closes #141.
This will form the basis of slowly building up this function. So as we add more inclusion/exclusion functions, we uncomment from here. And at the same time, the general logic of what is needed and what goes into what, as well as the argument names of the functions, can be seen from this function.
@Aastedet I know you had some things you mentioned that needed updating from the diagram, so maybe this function can help clarify that.