AI for Drug Shortages and Pharmacy Inventory Quiz

Answers and explanations appear as you take the quiz.

1. Where does the guide say most drug shortages originate?
   • On the supply side, through quality failures, few manufacturers and thin margins
   • In pharmacies that forecast poorly
   • In prescribers overusing antibiotics
   • In insurance formulary changes
2. Why does the guide warn against buying as much as possible when a shortage alert appears?
   • Warehouses charge by volume
   • Panic ordering amplifies through the supply chain and worsens shortages for others
   • FDA forbids stockpiling any drug
   • Drugs expire the moment they are purchased
3. Why should demand be forecast at the ingredient, strength and form level rather than only by NDC?
   • NDCs are confidential
   • Ingredients never change price
   • During shortages pharmacies switch manufacturers and packages, breaking NDC-level history
   • FDA requires ingredient-level reporting
4. What must therapeutic substitution follow, according to the guide?
   • The lowest-price option chosen by the wholesaler
   • Whatever the forecasting model outputs
   • The manufacturer's marketing guidance
   • Protocols approved by the pharmacy and therapeutics committee, confirmed by a pharmacist
5. Which method suits items with many zero-use days?
   • Croston's method or probabilistic models for intermittent demand
   • Simple linear regression on price
   • Ignoring those items entirely
   • Counting only the busiest week
6. How should a shortage risk model's output be interpreted?
   • As an exact date when supply will run out
   • As a risk ranking, since shortages are rare and often sudden
   • As a legal notice to prescribers
   • As an automatic purchase order
7. Which measure does the guide recommend for evaluating shortage prediction?
   • Overall accuracy across all products
   • Number of products scored
   • Precision among top-ranked items and how much warning time it gives
   • How many NDCs the model memorized
8. According to the guide, what would improve shortage warnings more than better algorithms?
   • More colorful dashboards
   • Faster pharmacy printers
   • Removing substitution protocols
   • Better data sharing between manufacturers, wholesalers and providers