Human Edge in an Automated Era
Dr. Ramsey H. Joudeh, MD, Founder, Artisans of Medicine NY | Adjunct Instructor, NYU Grossman School of Medicine
Interview by Ouissam Brahmi
Professional Perspectives | March 2026
What kinds of tools and technology are you using in your day-to-day clinical work?
Over the last five to six years, the digital tools we use in clinical practice have expanded significantly in both availability and sophistication. When I was a resident about a decade ago, web-based clinical reference platforms were just becoming mainstream. These functioned as living encyclopedias, continuously updated with new guidelines, preventive measures, and published research. As smartphones became ubiquitous, those same tools evolved into mobile applications. What once required logging into a desktop platform became instantly accessible through a search bar on your phone. Applications such as Epocrates, Medscape, and the Sanford Guide allowed clinicians to retrieve evidence-based answers in seconds rather than consulting textbooks. Today, artificial intelligence represents the next major shift. Platforms such as OpenEvidence leverage established clinical databases like UpToDate and use AI to synthesize and tailor information to specific patient scenarios. Where clinicians previously interpreted and applied raw guideline data themselves, AI now assists in organizing and contextualizing that information. While this enhances efficiency, clinical judgment remains essential in determining how best to apply it in real-world care.
Accuracy & Reliability
OpenEvidence sources its data from UpToDate, one of the most widely trusted and rigorously curated clinical references in medicine. Built on peer-reviewed research indexed in PubMed, the central repository for biomedical literature, UpToDate synthesizes vast amounts of evidence into clinically actionable guidance written and reviewed by experts. OpenEvidence then applies AI to extract and tailor that guidance to the specific patient question being asked.
Because the information flows from peer-reviewed research to expert clinical synthesis and finally to AI-assisted summarization, the underlying evidence base remains strong.
No system is entirely free from error. However, in my experience, UpToDate has been consistently reliable, and AI tools built upon that curated foundation benefit from its rigor while increasing speed and accessibility.
Where do current tools fall short or create friction?
From a purely clinical perspective, today’s medical knowledge tools are robust. The greater friction exists on the operational and business side of healthcare.
Many systems fail to integrate seamlessly. Scheduling platforms, billing systems, workflow tools, and electronic medical records often operate in parallel rather than cohesively. This fragmentation creates inefficiencies. For example, while some electronic medical record (EMR) systems previously integrated direct access to clinical references, newer AI tools sometimes pull broadly from the internet, which may reduce reliability if not properly vetted.
Operational systems—particularly in billing and claims management—carry financial risk when inaccuracies occur. In a claims-based model, reimbursement is often delayed six to seven weeks. Errors in coding or billing can significantly impact revenue cycles, payroll, and staffing. In this environment, precision is not optional.
Platforms such as EClinicalWorks and Epic each have strengths. Epic, in particular, is widely regarded as a leader in backend data extraction and reporting. However, even leading systems continue to face challenges in optimizing front-office workflows and administrative efficiency.
What determines whether clinicians adopt new technology or ignore it?
Adoption ultimately comes down to comfort, confidence, and workflow alignment.
Physicians develop practice patterns over many years of training. We rely on what has proven safe and effective in our experience. The same dynamic that influences medication prescribing influences technology adoption. For clinicians to integrate a new tool, it must demonstrate accuracy, speed, and relevance within their existing workflow. If a product introduces friction or uncertainty, it will not be adopted—regardless of its theoretical benefit. Generational shifts will naturally influence this process. Physicians trained in more digitally integrated environments are likely to incorporate AI and emerging tools more fluidly than those trained in earlier eras.
Founder Strategies: Getting Through the Door & Testing a Product
Healthcare is a demanding environment with limited time and tightening financial margins. Founders must be clear about the value proposition.
Patient benefit is essential—but from an operational standpoint, physicians also need to understand how a product improves efficiency. The most compelling offerings reduce time burden, administrative complexity, or staffing costs.
For example, a tool that automates prior authorizations and eliminates 20–30 hours of weekly administrative labor directly impacts operational overhead. Time savings and workflow simplification are powerful incentives.
If you can save physicians time, reduce risk, or improve efficiency, you will earn attention.
Trial Periods and Risk Mitigation
Most clinicians are not interested in beta testing unfinished products. They want reliability.
Structured trial periods—60, 120, or 180 days—allow measurable evaluation.
Given the six-week reimbursement cycle in many specialties, outcomes must be assessed over an appropriate timeframe. Risk mitigation is critical. If founders minimize financial exposure and demonstrate measurable improvement, adoption becomes far more likely.
The Future of MedTech: What Will Remain Fundamentally Human?
AI will influence nearly every aspect of medicine, but its impact will vary by specialty.
Primary care remains one of the most human-centered domains due to its longitudinal relationships. Other specialties, particularly imaging-based fields, may experience more significant automation.
Radiology, for example, is particularly well-positioned for AI integration. Algorithms trained on vast global imaging datasets can enhance speed and pattern recognition. Rather than eliminating radiologists, this shift may redefine their role toward oversight, complex interpretation, and interventional procedures.
Similarly, robotics and AI-assisted surgical systems are already improving precision and reducing operative time. As these technologies mature, the physician’s role may increasingly focus on supervision, complex decision-making, and patient-centered care rather than repetitive procedural steps. The skill sets required in medicine will evolve. Physicians who adapt to AI-integrated workflows will be best positioned for the future.
Closing Advice for Healthcare Founders
Think 10–20 years ahead.
Study durable business models and scaling strategies. Look closely at how resilient ecosystems are built, both in healthcare and beyond, but ground the lesson in healthcare leaders and organizations such as Patrick Soon-Shiong, Atul Gawande, UnitedHealth Group, CVS Health, Teladoc Health, and Flatiron Health.
Technology cycles are accelerating. What once changed over decades now shifts within years. Founders must anticipate friction points before they become crises.
At the same time, preserve human judgment. As AI reduces friction in information and decision support, deep thinking, ethical reasoning, and intellectual rigor become even more essential.
“Ask Yourself,” Says Dr. Joudeh
Where will medicine be in 20 years?
What challenges will arise in 5, 10, or 15 years as AI and robotics mature?
What can you build today that prepares the system for those shifts?
The most impactful founders build not for current comfort, but for future structural stress.
