AI is Transforming Every Doctor's Consultation

Artificial intelligence is changing how doctors care for patients, improving the way they make clinical decisions and manage their time. Dr. Rahul Goyal, Clinical Executive for the EMEALAAP region at Elsevier, shares how this technology is reshaping medical practice, from diagnosis to patient interaction, and highlights real examples from his experience(1^✔ ✔Trusted Source
Procurement and early deployment of artificial intelligence tools for chest diagnostics in NHS services in England: a rapid, mixed method evaluation

Go to source). Originally trained as an eye physician, Dr. Goyal always worked with technology in his medical workflow. Later, when he became a general physician, he noticed the lack of digital tools to support decision-making. This realization drew him toward integrating artificial intelligence into clinical practice, helping bridge the gap between medical judgment and digital support.

Evolution of Technology in Medicine

When Dr. Goyal began his medical career, digital tools were rare. The only device he used then was a small handheld personal digital assistant with a formulary installed. There were no online equivalents of resources such as the British National Formulary or NICE guidelines. Over time, technology evolved from being minimal support to becoming an essential part of clinical care.

He believes healthcare has been slow to adopt technology, mainly due to concerns about patient safety, ethics, and data privacy. But advancements in secure data systems and stronger regulations have helped reduce these barriers. According to him, healthcare is now entering a new era of digital transformation.

However, he emphasizes that not every technology is useful, what matters most is how it is used. Clinicians need to see clear benefits in saving time, easing workload, and improving patient outcomes. The best results occur when clinicians co-design digital tools instead of being passive users.

Artificial Intelligence Improving Real-Life Patient Care

Dr. Goyal recalls powerful examples where artificial intelligence directly improved patient outcomes. One case involved an elderly woman with a leg infection, kidney impairment, and several medications. Using an artificial intelligence tool called ClinicalKey AI, he could quickly assess safe treatment options, detect possible drug interactions, and identify warning signs to watch for. The system provided accurate, evidence-based guidance in seconds saving time, avoiding unnecessary follow-ups, and improving patient safety.

In another case, a seven-year-old boy suffered from a recurring limp with no clear diagnosis despite normal tests. When his history was entered into the same system, it suggested testing for tuberculosis based on his travel and family background. The tests confirmed tuberculosis, and early treatment led to full recovery. This experience showed how artificial intelligence can reveal missed possibilities, reduce human bias, and offer fresh clinical perspectives.

1. AI Supports Safer, Faster Clinical Decisions
AI tools like ClinicalKey AI quickly flag drug interactions, guide treatment choices, and surface missed diagnoses leading to safer, faster patient care.

2. AI Helps Reveal Missed or Rare Diagnoses
By analyzing symptoms and history without human bias, AI can suggest overlooked possibilities, as seen in the early detection of TB in a young patient.

3. AI Gives Clinicians More Time for Patients
Automation of notes and speech-to-text tools saves several minutes per consultation, allowing doctors to focus more on explanation, reassurance, and patient education.

4. AI Builds Patient Understanding and Follow-Through
With saved time, clinicians can offer clearer explanations and reliable take-home resources—improving patient comprehension and compliance.

5. AI Adoption Improves with Transparency
Doctors trust AI more when its reasoning is visible. Transparent systems help clinicians see the evidence behind recommendations, making adoption smoother.

6. AI Maintains Patient Trust Through Clinician Oversight
Using AI openly during consultations shows patients that technology assists but never replaces medical judgment, improving trust and communication.

7. AI Enhances Collaboration Across Medical Teams
In multidisciplinary settings, AI summarizes evidence for each specialist and speeds up consensus. Trials show it can help teams make faster, well-referenced decisions, especially in complex ICU cases.

Accelerating Safe Artificial Intelligence Adoption in Healthcare Systems

Dr. Goyal believes that national healthcare systems are well-positioned to implement artificial intelligence responsibly. He emphasizes the need for standardized validation, data quality checks, and regulatory compliance to ensure safe adoption.

Another challenge is improving communication between healthcare trusts and ensuring data interoperability while maintaining privacy. He highlights that collaboration among clinicians, policymakers, and communities builds trust and sets the foundation for ethical and efficient technology integration.

Common Misconceptions About Artificial Intelligence in Healthcare

According to Dr. Goyal, one common misconception is that all artificial intelligence tools are the same. In reality, they differ greatly in design and purpose. Some are generic, while others are specifically created for clinical use with evidence-based decision support. He compares it to mobile phones, one device can be used for both professional and personal tasks, depending on intent.

He also points out that unrealistic hype can lead to failure. Tools that are not grounded in real clinical needs or workflows rarely succeed. The most effective systems are validated and built on peer-reviewed, evidence-based resources. Another major concern among healthcare professionals is the fear that artificial intelligence will replace them. Dr. Goyal stresses that it is meant to assist, not substitute, clinicians, and that doctors should co-own and guide its development to ensure it meets clinical needs.

Advice for Hospitals Beginning Their Artificial Intelligence Journey

For hospitals beginning to use artificial intelligence, Dr. Goyal suggests identifying the most pressing problems in daily workflows, such as documentation or information retrieval. Starting small with one or two high-impact tasks allows healthcare teams to measure success before expanding further.

He also recommends involving all staff levels, doctors, nurses, and administrators, to ensure smooth adoption. Simplifying access with single logins and standardized systems reduces confusion and saves time. Dr. Goyal advises institutions to choose technologies that solve real problems rather than copying others. Successful implementation, he concludes, happens when tools are closely aligned with genuine needs and scaled thoughtfully.

In conclusion, the integration of artificial intelligence into healthcare is creating a new era of efficiency, safety, and collaboration. By combining human expertise with evidence-based digital intelligence, clinicians can make faster, more accurate decisions while dedicating more time to meaningful patient interactions.

Reference:

1. Procurement and early deployment of artificial intelligence tools for chest diagnostics in NHS services in England: a rapid, mixed method evaluation - (https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(25)00414-6/fulltext)

Source-Medindia