BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260715T161118Z
LOCATION:Nassau
DTSTART;TZID=America/New_York:20260323T103000
DTEND;TZID=America/New_York:20260323T110000
UID:HFESHCS_2026 International Symposium on Human Factors and Ergonomics i
 n Health Care_sess107_LEC302@linklings.com
SUMMARY:Beyond the Algorithm: How Systems Thinking Unlocks AI’s Potential 
 in Medical Device Innovation
DESCRIPTION:Annika Hey and ShweThee Kale (Veranex)\n\nArtificial intellige
 nce (AI) continues to dominate the conversation in medical device innovati
 on, yet many promising AI technologies fail to gain traction in real-world
  clinical settings. This presentation explores how systems thinking provid
 es a critical framework for understanding why these failures occur, not du
 e to technical shortcomings, but because of misalignment with the complex 
 healthcare ecosystem. \n\nDespite solving genuine clinical problems, AI-en
 abled devices often falter when introduced into environments shaped by ent
 renched workflows, regulatory constraints, and deeply ingrained patterns o
 f clinical decision-making. These technologies must navigate a landscape w
 here fitting seamlessly into existing trust paradigms, workflows, and inst
 itutional systems is not optional. It is essential for adoption. Systems t
 hinking enables innovators to step back from the technology itself and exa
 mine the broader healthcare context. This perspective reveals how factors 
 beyond the algorithm shape the conditions for success or failure. \n\nIn r
 esearch exploring next-generation cardiac treatment systems, we found that
  the potential acceptance of AI features depends less on technical sophist
 ication and more on the perception of how well they fit into established w
 orkflows and mental models. When algorithmic tools steer clinical actions,
  such as suggesting specific navigation paths for cardiac catheters, clini
 cians stated that they preferred to maintain manual control. They cited mi
 strust in the algorithm's accuracy and the additional oversight they antic
 ipated to avoid mistakes. In contrast, AI that worked behind the scenes to
  simplify existing treatment validation steps by summarizing familiar qual
 ity control data points into a treatment confidence score, was viewed as h
 ighly valuable. It was seen as easy to trust, and even influential in tech
 nology selection. These patterns highlight a critical insight for this pro
 duct: adoption accelerates when AI reinforces clinicians’ sense of control
  and integrates seamlessly into their existing routines. \n\nBy identifyin
 g leverage points within the system, such as workflow design, incremental 
 implementation strategies, and the cultural framing of clinical authority,
  teams can make small, targeted changes that produce outsized effects. The
 se leverage points are not always obvious, but when activated, they can sh
 ift the behavior of entire stakeholder groups, influence institutional nor
 ms, and reshape the conditions for adoption. These systems-level dynamics 
 frequently outweigh technological capabilities, making early ecosystem ana
 lysis essential to avoid costly missteps. \n\nWe introduce a practical fra
 mework based on three zones of influence: \n\nWhat You Can Control (device
  features) \n\nWhat You Can Influence (user interactions) \n\nWhat You Mus
 t Adapt To (regulations, infrastructure, and cultural paradigms) \n\nThis 
 model helps teams anticipate points of friction, align stakeholder expecta
 tions, and design solutions that are both technically sound and responsive
  to the realities of healthcare delivery. It also provides a lens for eval
 uating readiness, not just of the technology, but of the environment it en
 ters. \n\nAttendees will leave with actionable strategies for designing AI
 -enabled devices that work not just in theory, but within the lived realit
 ies of healthcare delivery. They will gain tools to identify feedback loop
 s, activate leverage points, and align innovation efforts with the complex
 , interdependent systems that define clinical practice.\n\nTrack: Digital 
 Health\n\nSession Chair: Cory Costantino (Emergo by UL)\n\n
END:VEVENT
END:VCALENDAR