Transforming Patient Care and Provider Efficiency
Co-authored Cassie McGrath, Morning Brew
September 11th, 2025
Artificial intelligence (AI) is rapidly reshaping the healthcare landscape. From AI powered diagnostic tools to digital scribes that reduce the burden on clinicians, the healthcare industry is on the cusp of a technological revolution. In a recent episode of Transforming Healthcare with electronRx, Cassie McGrath from Morning Brew shared her perspective on the transformative potential of AI, and the challenges that come with integrating new technology into patient care.
The healthcare sector has long been resistant to change, but AI is proving to be a catalyst for innovation. With an ageing population, rising healthcare costs, and increasing demand for services, the need for more efficient and scalable solutions has never been greater. AI offers a promising path forward, but it also raises critical questions about trust, regulation, and the future role of human clinicians.
AI Scribes and Diagnostic Tools
One of the most exciting developments in healthcare AI is the rise of AI scribes, digital assistants that document patient encounters and reduce the administrative burden on clinicians. Cassie highlighted a partnership between AI scribe company Abridge and electronic health record provider Athena Health as a promising step toward more efficient patient care. “AI scribes are already being used to take notes on behalf of clinicians,” Cassie explained. “This not only saves time but also reduces the risk of burnout among healthcare providers.”
Administrative work has long been a major source of frustration for doctors and nurses. According to the American Medical Association, doctors spend nearly 50% of their workday on documentation and administrative tasks, time that could otherwise be spent on direct patient care. AI scribes can automatically capture and transcribe patient encounters, freeing up clinicians to focus on diagnosing and treating patients.
AI is also being used to enhance medical imaging and diagnostics. AI powered tools can scan medical images and identify potential health issues faster and more accurately than human clinicians alone. “It’s like having a second pair of eyes,” Cassie said. “AI can provide an additional layer of analysis that improves accuracy and speeds up the diagnosis process.”
For example, AI tools are now being used in radiology to detect tumours, fractures, and other abnormalities with remarkable precision. Some systems have been shown to match or even exceed human performance in certain diagnostic tasks particularly in detecting lung cancer and breast cancer.
AI is also being integrated into pathology, where it can analyse tissue samples to identify cancerous cells and other diseases. These tools are not designed to replace human pathologists but rather to support them by highlighting areas of concern and reducing the time required for analysis. “The goal isn’t to replace doctors,” Cassie clarified. “It’s to give them better tools so they can make faster, more informed decisions.”
Patient Trust and the Human Touch
While AI holds enormous potential, Cassie noted that patient trust remains a critical factor. Some patients may feel reassured knowing that AI tools are supporting their diagnosis, while others may be wary of relying too heavily on technology. “Trust is key,” Cassie said. “Patients need to know that AI is complementing, not replacing, human expertise.”
Certain demographic groups, particularly those who have historically been underserved by the healthcare system, may be more sceptical of AI driven care. There are concerns about bias in AI algorithms, especially if training data is not representative of diverse populations. For instance, early AI diagnostic tools were criticised for underperforming in detecting skin conditions on darker skin tones because the training data was biased toward lighter skin.
Cassie pointed out that building patient trust requires more than just technological accuracy, it demands transparency and human oversight. AI tools must be integrated into care in a way that respects patient autonomy and allows for meaningful human interaction. “Patients want to know that there’s still a human behind the technology,” Cassie explained. “AI should support care, not replace it.”
Financial Pressures and the ROI Question
AI’s potential to improve efficiency and reduce costs is a major selling point for healthcare providers. But as Cassie pointed out, the financial reality is more complicated. “Implementing AI technology isn’t cheap,” Cassie noted. “Hospitals need to see a clear return on investment, whether that’s through reduced staffing costs, faster diagnosis, or improved patient outcomes.”
The cost of AI implementation includes not only the initial investment in hardware and software but also ongoing maintenance, training, and regulatory compliance. Hospitals and healthcare systems must carefully evaluate whether AI investments deliver the promised benefits, and those benefits may not be immediate.
AI in diagnostics and administrative support is relatively easy to justify financially, but more complex applications, such as AI driven surgical tools or predictive health platforms, require longer timelines to demonstrate ROI. This creates a challenge for hospitals operating under tight budgets and facing pressure to demonstrate short term financial improvements. “Hospitals want to invest in innovation,” Cassie said. “But they need to see results quickly, and that’s not always how AI works.”
AI in Primary Care
Some industry experts have speculated that AI could eventually replace human clinicians in primary care settings. But Cassie remains cautious about this assumption. “It’s possible for high tech, digitally literate patients to engage with AI for basic care,” Cassie said. “But many patients still need the human touch, especially those without broadband access or with complex health needs.”
Cassie highlighted a company called OnMed, which offers a “clinic in a box” model where patients can consult with a remote clinician through a digital interface. While promising, such models still face barriers related to cost, infrastructure, and patient acceptance.
Moreover, AI’s ability to provide personalised care is still limited. While AI can analyse patterns in data to suggest potential diagnoses and treatments, it lacks the ability to understand the nuances of human emotion and context that human clinicians bring to the table. “AI can’t replace empathy,” Cassie said. “And for many patients, that human connection is just as important as the diagnosis.”
AI is not just changing patient care, it’s also transforming the healthcare workforce. Automated documentation and diagnostic tools are reducing the workload on doctors and nurses, allowing them to spend more time on patient care.
However, this shift also raises concerns about job displacement. While AI is unlikely to replace doctors or nurses outright, some administrative and support roles may be at risk. Hospitals and healthcare systems will need to navigate this transition carefully to ensure that AI adoption does not lead to workforce instability. “AI can make healthcare more efficient,” Cassie said. “But it also requires careful management to make sure that the human side of care isn’t lost in the process.”
The Future of AI in Healthcare
Over the next six months, Cassie expects more hospitals to adopt AI tools, particularly in imaging, diagnostics, and administrative support. But she cautions that the healthcare industry moves slowly, and widespread adoption will take time. “Healthcare is complicated,” Cassie said. “AI offers huge potential, but integrating it into everyday care will be a gradual process.”
AI adoption will also depend on regulatory clarity. Current guidelines around the use of AI in healthcare are still evolving, and hospitals will need clear guidance from policymakers to ensure that AI tools meet safety and ethical standards.
AI is not a silver bullet for healthcare’s challenges, but it could be a powerful tool for improving efficiency, reducing costs, and enhancing patient care. As Cassie’s insights reveal, the key to success lies in thoughtful implementation, clear regulation, and a focus on patient trust. AI may not replace human clinicians, but it can empower them to deliver better, more effective care.
