Evaluating the Effectiveness of AI-Based Clinical Decision Support Agents in Simulated Medical Consultations to Improve Efficiency and Quality of Care in General Practice

General practice in the United States faces increasing mental demands that make it hard to provide the best care. Primary care doctors often handle complex patient problems and many administrative tasks. This leads to mental tiredness and slows down their work. These problems are worse after hours, when there are fewer staff and resources, but more urgent cases. Studies show that American GPs have similar system problems as doctors in other countries, such as dealing with many complex patients and extra paperwork.

The mental strain on GPs often causes slower decisions, possible mistakes in diagnosis, and unhappy patients. Fixing these issues is important to make healthcare better and keep doctors working well. Tools that help with decisions and improve work flow can reduce pressure and give doctors more time to spend with patients, which leads to better care.

Introduction to NAOMI: An AI-Driven Clinical Decision Support Agent

NAOMI (Neural Assistant for Optimized Medical Interactions) is a project that combines artificial intelligence with clinical decision-making. It was tested using 80 practice patient consultations and uses GPT-4 technology to help with triage, diagnosis, and reasoning. NAOMI is designed to help general doctors handle many tasks during patient visits.

The project was done by researchers including Timothy Hor, Lee Fong, Katie Wynne, and Bert Verhoeven. Their work was published by Elsevier Ltd. in the journal Technovation. They showed that NAOMI works well with many different clinical cases. It helps doctors make better diagnoses and triage decisions while lowering their mental workload.

Key AI Design Principles Underpinning NAOMI’s Effectiveness

• Comprehensive Data Collection and Analysis
  NAOMI collects a wide range of patient information, like medical history, symptoms, and test results. Analyzing all this helps the AI make more accurate diagnoses. This way, decisions are based on a full view of the patient’s condition, not just bits of data. In U.S. general practices, where records can be scattered or incomplete, this helps doctors get better continuous care.
• Clinical Reasoning Transparency
  Doctors need to trust AI tools. NAOMI explains how it makes decisions, so doctors can see the reasons behind its advice. This makes it easier for doctors to use NAOMI without worry. Many U.S. healthcare providers find it hard to accept new tools if they seem like “black boxes.” NAOMI avoids this by being open about its reasoning.
• Adaptive Triage and Risk Assessment
  Deciding which patients need attention first is tricky, especially in busy clinics or after hours. NAOMI changes its triage choices based on what it learns about patients in real time. This helps clinics in the U.S. send help to high-risk patients sooner and use their resources better.

Practical Impact on General Practice: Findings from Simulated Medical Consultations

In 80 simulated patient visits, NAOMI was tested on a variety of cases, from simple problems to complex ones with many symptoms. The study showed important results for U.S. clinics:

• Enhanced Diagnostic Accuracy: NAOMI’s use of full patient data improved correct diagnoses. It also helped with deciding how urgent cases were. This is helpful because American primary care sees many different cases each day.
• Reduced Cognitive Load: Doctors said NAOMI eased their mental tiredness by doing the data review and giving clear steps for decisions. This can help lower burnout, which is common among American healthcare workers.
• Improved Workflow Integration: Because NAOMI clearly explains its choices, it fit well into doctors’ usual work without causing problems. This made it easier for doctors to accept and use the tool.

These results are important for medical managers and IT staff who want to improve healthcare services and worker satisfaction in U.S. clinics.

Relevance for Medical Practice Administrators, Owners, and IT Managers in the U.S.

Administrators and owners in the U.S. must balance quality patient care with smooth operations. Rules, payment policies, and patient needs are changing, adding more paperwork and tasks for healthcare workers. AI tools like NAOMI can help in many ways.

Some benefits for administrators are:

• Lower Staffing Pressures: AI can handle parts of data gathering and patient sorting, so fewer staff are needed just for paperwork.
• Enhanced Patient Throughput: Faster and better decisions mean shorter wait times and improved appointment scheduling.
• Improved Compliance and Documentation: AI can keep patient records more accurate, which helps with billing and meeting U.S. healthcare rules.

IT managers can use AI systems that fit with current work flows and do not require big changes to existing computer setups. Transparent AI also means doctors need less training and use the tools more easily.

AI-Enhanced Workflow Automation: Streamlining Primary Care Operations

AI can improve clinical work by automating routine tasks. In general practice, many repeated and admin duties take up much time that could be spent on patients. AI-based automation has clear benefits:

• Automated Call Handling and Front-Office Support
  In many U.S. clinics, there are many patient calls about appointments, prescription refills, or triage questions. AI phone systems can handle these efficiently without stressing front-office staff. This lowers patient wait time and lets clinical staff focus on more important work.
• Pre-Consultation Data Gathering
  AI can collect basic patient information before visits. This helps doctors have full data ready, making visits faster and avoiding repeated questions. Patients are more satisfied, and consultations save time.
• Dynamic Patient Prioritization
  AI checks patient data and risks constantly. It helps staff find urgent cases quickly. This reduces missed or late care for serious patients.
• Integration with Electronic Health Records (EHRs)
  AI can link with EHR systems common in the U.S., updating patient files automatically. This reduces errors and saves paperwork time.
• Support for After-Hours and Telehealth Services
  AI helps clinics after hours by handling first contacts with patients, collecting information, and setting follow-up priorities. This is useful for rural or underserved areas where care access is harder.

Broader Implications for Healthcare Equity and Workforce Challenges

The high mental load on doctors affects fairness in healthcare and the strength of the workforce. In rural and underserved U.S. communities, few primary care doctors and hard after-hours coverage make access difficult. AI tools like NAOMI can help by:

• Lowering the workload that limits doctor availability.
• Providing steady and good decision support no matter the clinic size or location.
• Helping allocate resources to the most urgent patients, making sure care is timely.

Also, with fewer primary care doctors available in the U.S., AI tools will be important to keep care quality good even when there are fewer human doctors.

Wrapping Up

AI-based clinical decision support systems like NAOMI have shown promise in practice sessions for lowering doctors’ mental work and improving care speed and quality. For U.S. general practices, using these tools can help deal with challenges like after-hours care, complex patients, and heavy paperwork.

Administrators, owners, and IT managers in medical practices should think carefully about how AI decision tools and workflow automation could make operations better, increase doctor satisfaction, and improve patient care. Using AI tools that focus on full data analysis, clear explanations, and changing risk evaluations can strengthen primary care and support better healthcare for communities across the country.