Alessandro Gasparini

Hello Jack! Thanks for the heads up. I choose to grep for all the codes assuming that grepping for non-existent codes _should_ never results in hits - that code _should_...

Thanks @salmasian and @jackwasey for the interesting discussion! I like the idea of having a `validate()` function that returns all potential invalid codes - I plan to include more ICD...

This is interesting, thank you @aalexandersson! I replicated your example using simulated ICD9 data (only valid codes): ``` r library(comorbidity) library(icd) library(tidyverse) ``` Simulating real ICD-9 codes: ```r set.seed(1) N...

Hi guys, I modified my example as before to obtain IDs of individuals whose score differ: ``` r library(comorbidity) library(icd) #> Welcome to the 'icd' package for finding comorbidities and...

`comorbidity` returns both a simple sum score and a weighted score as well; weights for the Charlson score are according to the original formulation by Charlson _et al_. in 1987,...

Hello @aalexandersson! The difference in score is due to the fact that `comorbidity` by default does not count the same comorbidity with different degree of severity twice when computing the...

@jackwasey `comorbidity` computes the simple sum of comorbidities (with hierarchy depending on the `assign0` argument), and also the Charlson and van Walraven scores (with weights and hierarchy via `assign0` as...

Aha, thanks for the information, that's very useful. Would you be eager to receive PRs with new templates (either here of there)?

Hi @mattmoo, Sorry – I haven't had time to progress on this, but it looks like things will be calmer in the next few months. I'll get back to this...

Hi, thanks for reporting this. I wouldn't change the default behavior, but I am keen on adding an option to return a long format dataset instead. Let me have a...