Join Medicare Part D spending data to ATC Classification System

[darya-akimova]

Status

• @darwinyfu has expressed interest in working on this problem
• Ongoing: @Anandkarthick has made progress on this issue by matching the spending files to drug_uses.csv (on data.world) by the drugname_generic

Update:

• Upon working with it, I've discovered that drug_uses.csv is missing drugs that should be in the ATC system (and are present in the atc_codes_clean.csv dataset). It seems that the atc_codes_clean.csv is the way to go, even though it's currently in a messier state.

Update 3/1/2018

Matched app. 3k out of 4.5k items in the Medicare Part D dataset (see /drug-spending/R/datawrangling/atc_merge_atc_codes_clean_da and /atc_merge_drug_uses_csv_da for notebook), but putting this issue on hold and switching directions because:

• ATC classification offers limited matching on brand name. While it is possible to get some successful matches based on the generic/chemical names, this approach becomes complicated for drugs with multiple active ingredients
• Unsure how to combine multiple ATC code assignments, both for single compounds that have multiple ATC classifications and for drugs with multiple (2-8) active ingredients.
• Started hitting a wall where a lot of research and hand annotation would be required to make progress

Task

Join drugs in the Medicare Part D spending data to their ATC Classification System categories by join the spending-201x.csv files on data.world to either atc_codes_clean.csv or drug_uses.csv.

What we're looking for

Potential outputs that would help greatly to further the goal of this project:

• A csv file of the two joined files if able to match all of the drugs in the Medicare spending files to ATC classification categories OR both of the following (because the above will probably be challenging and/or a big time investment for one person):
• A work in progress csv file with all successfully matched drugs
• A work in progress csv file containing all of the drugs that COULD NOT be matched

The potential routes of matching drugs to their ATC classification categories:

atc_codes_clean.csv dataset

• Match the drugname_generic column from any of the spending-201x.csv files on data.world to the atc_codes_clean.csv file on data.world by the level5 or kegg columns. But these columns are very messy in the atc_codes_clean.csv file. To be honest I didn't put in much effort into cleaning them because I wasn't sure how these columns would be used down the line.

OR

drug_uses.csv dataset (which may be the easier of the two)

Two options:

• Join the drugname_brand column in any of the spending-201x.csv datasets to the drugname_brand column in drug_uses.csv. OR
• Match the drugname_generic column from any of the spending-201x.csv files on data.world to the drugname_generic or substance or name columns in drug_uses.csv. These columns in the drug_uses.csv dataset are much cleaner than the atc_codes_clean.csv and I only realized that this file contained ATC classification information after I uploaded the atc_codes_clean.csv.

Side note: all of the spending-201x.csv files should have the same drugs in the same format, since they come from a parent wide .xlsx file that had the years data spread across the columns. If the drugs from one of the spending files are matched successfully, then the same steps should successfully join the other files, so no need to try and compare all of the spending files to find differences in drug names.

Ideal file formats for the analysis:

• Jupyter notebook with code outputs OR
• R Markdown file (ideally knitted to html) with code outputs

How this will help

We're working towards matching drugs to their therapeutic uses. The USP Classification system, FDA drug approval data, and the ATC Classification system seem to be the best potential grouping categories of drugs from the datasets that have already been collected. The ATC classifications system provides classification seems to be more scientific/medical jargon-leaning, but it can be potentially useful down the line.

[Anandkarthick]

I just completed this task for one dataset.. spending_2011. How can I share the dataset? just wanted to get a comment before doing this for all dataset.

[SeniorHealthcareAdvisors]

When CMS overhauls its Electronic Health Record (EHR) how will it affect supplemental health insurance costs & Medicare Open Enrollment 2019?