What You Should Know
- 81% of surveyed CHIME member IT executives consider clinician involvement in the design and deployment of AI “mostly or vitally important,” with zero respondents rating it unimportant, according to a Carta Healthcare survey.
- 77% of technology leaders report seeing better clinical and operational outcomes when AI tools operate collaboratively alongside clinicians, and none reported that collaboration failed to help.
- Executives identify AI hallucination as the primary risk of unsupervised models, ranking it ahead of model drift, algorithmic bias, documentation errors, liability, and protected health information (PHI) exposure.
- Frontline clinician adoption relies on early involvement in software design, seamless integration into existing electronic health record (EHR) workflows, transparent reasoning, and formal governance.
- The survey findings support Carta Healthcare’s “Hybrid Intelligence” model, which pairs advanced AI automation with credentialed clinical abstractors to deliver accurate, auditable clinical data management.
Hallucination Mitigation, Hybrid Intelligence, and Workflow Fit
A market survey of College of Healthcare Information Management Executives (CHIME) technology leaders, released by Carta Healthcare, highlights an industry consensus across health system C-suites: artificial intelligence must operate as a clinician-governed force multiplier rather than an autonomous replacement for human clinical judgment.
The survey illustrates specific operational prerequisites for enterprise AI deployment across health systems:
- Clinician Control Mandate: 81% of IT executives rate clinician involvement in the design and deployment of AI tools as mostly or vitally important, with zero respondents classifying clinician oversight as unimportant.
- Collaborative Performance Impact: 77% of leaders report superior clinical and operational outcomes when AI operates alongside clinicians rather than on its own, establishing human-AI collaboration as a primary framework for measurable value.
- Top Unsupervised AI Risks: IT leaders identified model hallucinations as the single greatest risk of deploying AI without human oversight, outranking algorithmic bias, model drift, legal liability, and protected health information (PHI) exposure.
- Drivers of Frontline Adoption: Successful adoption across clinical workflows requires involving frontline care teams early in tool development, embedding software directly into established EHR routines, ensuring transparent model outputs, and maintaining human validation before executing clinical or operational decisions.
“Health system IT leaders are telling us plainly that AI earns trust when clinicians stay in control,” said Brent Dover, CEO of Carta Healthcare. “That is what holds up under audit, under accreditation review, and in the moment a result has to be defended. Clinicians at the helm, with AI as the force multiplier, is the only model that scales.”
