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WRAP-UP.md

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Lessons Learned

Start of project: pretty much right after D4D formed; gather Medicare drug spending data and analyze to find interesting trends, anomalies, etc.

Data sources

  • CMS.gov (for Medicare drug spending data)
  • FDA (for FDA drug codes, which are IDs assigned to each individual drug)
  • Genome.jp (for ATC codes, which map drugs to their usages)
  • Centerwatch.com (for mappings between drug names and their usages)

All data now housed either at data.world (mostly there) or in the project’s Git repository:

Issues

Communication

  • For a short while, both co-leads had to step away at roughly the same time; this made work on the project a bit less cohesive and resulted in some confusion
  • Lack of specific questions: we knew Medicare drug spending was worthy of our attention, but we didn’t know where to start or what had already been explored
    • Couldn’t find any subject matter experts until later in the project’s life; by that time, activity had already died down considerably
    • Led to a lack of actionable tasks, even with available volunteers
    • Led to lack of interest/activity in the project’s Slack channel

Technical

  • Difficult to cross-reference drug names with other information (e.g., treatments, conditions)
    • Drug names and authorized usages differ by brand, locality, and method of use
    • Many different sources of truth
  • (Minor) Multiple programming languages in use
    • Some volunteers knew one, some knew another
    • # of available reviewers for any given PR depended on the language the submitter used