Derrick Billups discusses AI‑driven supply chain resilience on

Derrick Billups, MSHA, CMRP, FACHE, Vice President of Supply Chain and Support Services at UC Health – Cincinnati, told the Becker’s Healthcare podcast that AI tools are now central to the health system’s demand‑forecasting and supply‑chain risk‑management strategy【2】.

AI as the engine for demand forecasting

Billups explained that the health system has moved from manual spreadsheets to machine‑learning models that ingest historical usage, seasonality, and external factors such as flu trends. The models generate forecasts with tighter confidence intervals, allowing inventory planners to reduce safety stock while maintaining service levels. He noted that the AI‑driven approach has already cut forecast error by a single‑digit percentage point compared with the prior year’s manual process, though the exact figure was not disclosed.

Reducing clinical variation and supply‑chain risk

Beyond forecasting, Billups highlighted two complementary AI applications. First, predictive analytics flag potential shortages before they materialize, prompting pre‑emptive procurement actions. Second, the system uses variation‑analysis dashboards to identify clinical practice differences across the network, enabling standard‑of‑care protocols that lower both cost and waste. He stressed that these tools are especially valuable as hospitals confront “an increasingly complex healthcare environment” where supply‑chain disruptions can directly affect patient outcomes【2】.

What to watch

• AI model updates – monitor any announced upgrades or new data sources that could further sharpen forecasts.
• Supply‑chain risk alerts – watch for public statements from UC Health about upcoming shortages or mitigation actions.
• Clinical variation reports – follow releases of variation‑analysis findings that may signal shifts in practice patterns.

Billups’ remarks illustrate how large health systems are leveraging AI not just for efficiency but as a strategic shield against the volatility that has long plagued medical‑supply logistics. The next step will be seeing whether these tools can scale across the broader industry and deliver measurable cost savings.