Medical students may be comfortable using digital tools, but that does not mean they are prepared for the electronic health record demands of residency. New clinicians must handle the EHR to review extensive patient histories, manage orders and document decisions while keeping pace with clinical workflows. New research from CDW explores how artificial intelligence is helping IT teams manage risk and improve resilience, while also highlighting a gap in how future physicians are trained to use these systems.
Early Exposure and Hands-On Learning
Dr. Joel Boggan, an associate professor of medicine at Duke University School of Medicine, notes that students now begin clinical encounters and related EHR work during their first year. Residents complete formal new-user and specialty-specific modules to prepare for these environments. The trend toward earlier exposure means students can accrue more time working in these systems before they join the workforce.
Simulated EHRs allow students to handle records, review and add documentation and enter orders before performing those tasks in patient-care settings. During clinical rotations, professional activities give faculty a framework for reviewing students’ documentation and providing feedback. This approach helps bridge the gap between classroom learning and real-world application.
Changing Skills for a New Era
Dr. Deepak Pradhan, co-director of AI education at NYU Grossman School of Medicine’s Institute for Innovations in Medical Education, says EHR competency now extends beyond learning where to click. He explains that EHR competency is really a clinical competency issue as well. This shift reflects the growing complexity of the systems and the increasing role of data in clinical decision-making.
Dr. Gabrielle Mayer, an internist and co-director of AI education at NYU Grossman, adds that residents must learn to treat EHR use as a complement to the clinical examination rather than a separate, sequential task. The ability to understand how time interacts with EHR use is something you cannot improve until you get to residency. Without this understanding, physicians risk spending more time on documentation than with the patient.
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Ambient listening AI is transforming documentation from a writing task into one that requires clinicians to edit, verify and accept responsibility for AI-generated text. Saiyed calls this the biggest shift in a generation. Physicians are shifting from entering notes to serving as their editor, auditor and final medical decision-maker. Typing speed and note templates are out; clinical judgment and AI oversight are in.
Dr. Salim Saiyed, chief medical informatics officer at the University of Texas at Austin Dell Medical School, explains that this change means clinicians need to critically review the output, detect hallucinations, identify omitted findings and verify and edit it so that it is accurate. The focus is moving toward validation and accountability rather than just data entry. This represents a significant change in the skill set required for modern medical practice.
Understanding the Systems Behind the Screen
Saiyed points out that vendors are responding to the need for deeper training. Epic’s Physician Builder and Informatics tracks are becoming the credentialing path for physicians who will help design EHR systems, not just operate them. This suggests a move toward informaticists who understand the architecture of the systems they use daily.
He also notes that certifications, such as the National Healthcareer Association’s Certified Electronic Health Records Specialist (CEHRS) credential, are primarily intended for EHR analysts, clinical informaticists and revenue cycle professionals. Residents have to complete new-user orientation and train in their specialty environments, but those don’t typically come with a certification. Those are the basic elements for use as a frontline clinician.
One key gap in education concerns the business and platforms behind the screen. We teach residents to chart, but not to see the platforms that they’re charting into. Future physicians need to see those ripples before they act, not after. This includes understanding revenue cycle, scheduling, referral management, analytics, population health and a variety of integrations.
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Beyond documentation, curricula need real fluency in responsible AI use, bias mitigation, data governance and human oversight. The literacy every physician will need in the future must include the ethical implications of automation. Without this foundational understanding, the potential for error increases significantly.
Curricula need to address the reality that AI-assisted charting is becoming the standard. From Mayer’s perspective, students should master unaided documentation before progressing to AI-assisted charting. We think about writing a note without the assistance of ambient AI and developing that skill. Assessment rubrics can then determine whether a learner’s notes demonstrate sufficient clinical reasoning to introduce AI augmentation and verification.
The most effective EHR training often happens when learners encounter a real workflow problem. That’s the moment that the learning is best. When a student faces a system failure or a data inconsistency, the immediate need to solve the problem creates a stronger memory than passive learning. Faculty development is equally important because attending physicians supervise EHR and AI use in clinical settings. You need somebody to really interrogate, investigate and reflect in a safe environment about how we can do better.
As the healthcare setting evolves, the integration of advanced technology and medical practice requires careful oversight. The CMS has recently approved a 2.3% hospital payment increase, which will impact how facilities manage resources and staffing. This adjustment comes alongside ongoing discussions about insulin pricing, such as the recent FTC settlement with Caremark, which aims to address affordability for patients. For those interested in the technological side of these changes, the top 30 healthcare IT influencers to follow in 2025 offer valuable insights into the future of medical technology.