Pharmacy AI Managed Inventory System (PHAIMIS)

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

High-impactSource: a) High-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

Not reported

Mission

Topic area

Health and Medical

Operational functions

Forecasting and prediction, Procurement and acquisition Derived by keyword rules; see methodology

Problem the AI is intended to solve

PhAIMIS is intended to represent an overarching inventory management tool for pharmacy, and has various areas where AI could be leveraged: • Predictive analytics on product needs – establishing optimal Min/Max ; ROP/ROQ (reducing on hand stock while reducing out of stock) • Inventory forecasting and identification of backorder/ supply chain issues (backorders) • Recommendations for resolution of supply chain/ backorder issues • Pharmacoeconomic reviews and recommendations for cost savings with equivalent product conversions • Expiring product utilization optimization (leverage PINS or other to share product that will not be used prior to expiration with facilities that will) • Contracting compliance/order creation • Streamlining of administrative tasks such as B09 audit/reconciliations

Expected benefits

Enhanced medication availability and cost savings as it relates to more efficient supply chain management

System outputs

Inventory mapping, predictions, and decision support for medication procurement

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported