healthsystemCIO – Strategies for Hospital IT Leaders

Jim Bilsky, SVP and CTO, and Ryan Hooley, VP of Enterprise Architecture and AI, at Baptist Health in Jacksonville, Fla., discuss how they brought Epic, Microsoft, IGEL, ControlUp and Imprivata into one room to speed up virtual desktop sign-in. They explain the log-level evidence their architects gathered, why physicians told the vendors what slow logins cost, and how sign-in fell from about 90 seconds to 10 to 15.

Chris Carmody, senior vice president and CIO at UPMC, explains how the health system weighs AI solutions and agents against their return and is prepared to turn off those that fall short. Carmody discusses token costs, the policy and review group behind AI adoption, and the pilot of 1,000 physicians per vendor that chose Abridge over Nuance DAX, along with why UPMC keeps that ambient AI decision open.

Stephanie Hines, senior vice president and CIO at Valleywise Health, discusses why the operators accountable for results should own technology decisions and their risk, with IT acting as steward of a central budget. Hines explains how a decision science framework lays out the cost, cyber risk and integration burden of point solutions, and how look-backs make IT's value visible without asking for credit.

Alex Forman, chief data officer at WVU Medicine, explains why the health system standardized how its hospitals build and measure OR block time before turning on Epic's AI-assisted scheduling tools. Forman discusses treating block utilization as a stewardship measure, keeping one version of the numbers when vendors bring their own analytics, and building data models for AI agents. Main-OR block utilization rose from about 60% to 67%.

Naomi Lenane, CIO and senior vice president of information services at Dana-Farber Cancer Institute, discusses how much data quality a health system needs before acting on its data. Lenane explains why the answer depends on the decision, why data definitions and ownership come before cleanup, how related measures show whether a report deserves trust and what it takes for clinicians to trust AI output built on imperfect data.