This application uses the Mindmeld framework to build a conversational agent that inquires and collects information about a patient's medication record. The use case for this application is medication reconciliation, which is the process of creating an accurate record of a patient's current medication regimen.

This agent aims to accomplish the following tasks:

• Collect medication brand, primary ingredients, dosage, and frequency from natural language
• Inquire user for missing information about their medications
• Cross check information with RxNorm, a database of standardized perscription drug information maintained by the US Library of Medicine

This application is currently under development.

The medication domain is to support the following intents:

• add_medication — Patient reports a series of new medications that are to be added to their record.
• update_record — Agent interviews patient about medications on their existing record and updates it as needed.
• start_over — Clears information from the current conversation and goes back to the start message.

The general domain is to support the following intents:

• greet — Begins the interaction. Greet the patient and inform them about the agent's functionality.
• exit — Ends the current interaction and say goodbye to the patient.
• help — State the agent's functionality and recomend several actions they can take in case the patient gets stuck.
• unsupported — Patient has inquired for information outside the scope of the agent's knowledge.

• medication_history_examples — Examples of medication reconciliation dialogue from Vanderbilt University Medical Center's training videos.
• sds4rx — Mindmeld application
  • data — JSON knowledge base of all known medications
  • domains — Contains annotated example queries for all intents, sorted by domain.
  • entities — Contains training data for entity resolution.
  • scripts — custom Python scripts used to generate data in the three folders described previously.
    • rxnorm.py — Collects data from RxNorm API
    • kb_generatory.py — Generates a JSON knowledge base given a list of ingredients using information from RxNorm.
    • entity_generator.py — Generates entity mapping files given a JSON knowledge base.
    • frequencies_gen.py — Generates natural language phrases for describing frequencies.

• This application's knowledge base is limited to the 50 most perscribed medications in the US (Fuentes, 2018).
• Representative training data is currently being generated to train the NLP classifiers. (related Mindmeld documentation)

• Include a knowledge base component that directly interfaces with the RxNorm API instead of a locally-stored database.