Nilay Deshmukh
Senior Associate | Senior Medical PlannerNBBJGrounded in the belief that well-designed healthcare facilities change lives, Nilay approaches every project with empathy as a guiding principle. With more than two decades of experience, he has planned complex clinical environments for leading healthcare systems including Boston Children’s Hospital, UC San Diego Health, and Yale New Haven Health. His portfolio spans emergency departments, interventional cardiology, imaging, surgical, and hybrid platforms, with a focus on how design advances safety, workflow, and clinical outcomes. As senior member of NBBJ’s healthcare practice, Nilay aligns teams around shared goals while advancing operational efficiency, user experience, and evidence-based design.
E94 – AI: A New Partner in Healthcare Design — From Conceptual Design Through Occupancy
Artificial intelligence is rapidly moving from experimentation to practical application across the healthcare facility lifecycle—from early planning t…Artificial intelligence is rapidly moving from experimentation to practical application across the healthcare facility lifecycle—from early planning through transition and occupancy. This session explores how AI-enabled tools can optimize design deci…Artificial intelligence is rapidly moving from experimentation to practical application across the healthcare facility lifecycle—from early planning through transition and occupancy. This session explores how AI-enabled tools can optimize design decisions with clinical operations, improving outcomes while reducing risk. To examine how AI-enabled analytics can accelerate clinical programming, this presentation will explore examples that integrate …Artificial intelligence is rapidly moving from experimentation to practical application across the healthcare facility lifecycle—from early planning through transition and occupancy. This session explores how AI-enabled tools can optimize design decisions with clinical operations, improving outcomes while reducing risk. To examine how AI-enabled analytics can accelerate clinical programming, this presentation will explore examples that integrate operational data, staffing models, and throughput assumptions to inform space planning and adjacencies. Predictive modeling and AI-supported workflow analysis will demonstrate how patient, staff, and material flows can be evaluated early, helping teams identify inefficiencies and operational risks before they are embedded in design. The session will also address AI-supported code and regulatory compliance checking, quality control in design documentation, and the detection of inconsistencies that often lead to RFIs and change orders with downstream operational impacts. Finally, this session will investigate emerging applications of AI in transition and occupancy planning, including operational readiness, staff onboarding, and smoother handoffs from construction to day-one clinical operations. Attendees will gain insights into opportunities to integrate AI into healthcare design workflows today—not as a replacement for professional judgment, but as a powerful planning partner that enhances decision-making, reduces risk, and supports safer, more efficient healthcare delivery.Show MoreClick the title to see all detailsShow More
