In healthcare, Agentic AI quickly transforms how the medical system diagnoses disease, customizes therapy, and automates clinical workflow. To put it another way, Agentic AI in healthcare utilizes autonomous agents (AI) to analyze medical records and coordinate clinical activities, forecast patient risks, and support clinical decision-making – all with a major increase in precision, efficiency, and quality of care, with little human participation to take actions on patients’ behalf. The introduction of this technology allows for a reduced number of errors, quicker results from clinical decisions, and better results for patients in hospitals.
What Is Agentic AI in Healthcare?
Agentic AI in healthcare uses intelligent systems to continuously monitor medical workflows, researching and planning all of the actions that are typically taken in the care of patients. Contrasting with traditional AI, which only reacts to a specific set of triggers, agentic AI continually looks at the medical data to find new ways of responding to the data. Therefore, the agentic AI can:
- Monitor and assess a patient’s vital signs (examples of WHI)
- Develop a clinical report prior to a patient coming into the office for their visit
- Identify potential health issues based on an abnormal physical assessment of the patient prior to developing any clinical symptoms
- Coordinate a protocol for treatment that includes multiple healthcare professionals, including, for example, referrals to specialists or further diagnostic testing
- Improve the hospital’s ability to manage the administrative element associated with providing health care to patients.
The shift from a reactive model to a proactive model within healthcare will further help reduce delays in patient care and improve the experience of the patient through earlier detection of health risks associated with disease.
How Agentic AI Works in Healthcare
1) Perception: Understanding Medical Data through Interpretation.
Agentic Systems ingest data via:
- Electronic Health Records (EHR)
- IoT Medical Devices
- Laboratory Results
- Imaging Systems
- Clinical Guidelines
As agentic systems constantly solicit data for change, they continuously update their understanding of the patient’s condition.
2) Planning – Generating and Prioritizing Action Items
Algorithmically, agentic AI creates multi-step plans:
- Generating differential diagnoses
- Suggesting lab tests
- Recommending treatment changes
Agentic AI continuously revises these plans when new data arrives.
3) Action -Executing Medical or Administrative Tasks
AI Agents can perform Medical or Administrative functions on
Architecturally based on Technology:
- The agentic AI can automatically update patient medical charts
- The agentic AI can send alerts to physicians regarding patients who are identified as being at-risk.
- Agentic AI can request the transmission of missing clinical data
- Agentic AI can create drafts of discharge summaries for healthcare providers
Agentic AI can coordinate activities with Departments such as Radiology and Oncology.
Key Benefits of Agentic AI in Healthcare
1) Faster, More Accurate Diagnostics
Agentic AI will assist doctors in the identification of certain patterns that may be unattainable by humans.
- Agentic AI detects anomalies in imaging studies
- Agentic AI can analyse decades of medical records in a couple of seconds
- Agentic AI forecasts disease prognosis.
- Agentic AI can recommend evidence-based treatments
Agentic AI can improve the accuracy of medical diagnosis through minimised human error.
2) Proactive Patient Monitoring
The agentic AI continuously monitors the patient for all aspects of health, affirming that a healthcare provider has the ability to intervene more quickly.
The agentic AI alerts healthcare providers about the likelihood of sepsis.
The following can be accomplished by agentic AI.
- Detect the first signs of sepsis
- Predict the likelihood of cardiac events
- Provide glucose monitoring to persons with diabetes
- Notify nurses when patient vitals exceed predetermined limits
This technology enables medical practitioners to quickly respond to patients based on the patient’s status via immediate monitoring.
3. Reduced Clinical Burnout
Through my experience of using technology-driven workflows in the marketing field, I have found that administrative functions account for a high percentage of nursing staff time. The workload involved with completing administrative tasks using traditional methods is greatly reduced with the implementation of agentic AI.
Agentic AI automates the following:
- Charting & Documentation
- Appointment Scheduling
- Assistance with Coding for Insurance Claims
- Results from Lab Testing Follow-Up
- Housekeeping for Transcription of Medical Notes
This allows doctors more time for practicing medicine rather than completing administrative duties.
4. Personalized Treatment Plans
Agentic AI creates individualized treatment plans by using:
- Genetic Information
- Lifestyle Data
- Previous Medical History
- Predictive Risk Model Data
By doing this, agentic AI can update the method of care a patient receives as needed and can automatically inform the healthcare team of any required actions.
Real-World Use Cases of Agentic AI in Healthcare
1. AI Agents in Radiology
Provide automatic interpretation of X-rays and other medical images using AI technology.
AI Agents help:
- Automatically interpret the results of MRI or X-ray scans
- Prioritize urgent scans based on the need for immediate attention.
- Produce initial investigatory reports.
- Notify Radiologists regarding inconsistencies within the images
2. AI Care Assistants for Hospitals
These AI agents coordinate:
- Bed allocation based on patient needs.
- Scheduling patient transfers most efficiently.
- Optimising Nurse shift patterns.
3. Pharmacy Automation
Agentic AI can help with:
- Forecasting medication inventory
- Identifying possible drug interactions.
- Making recommendations on dosage changes.
4. Virtual Health Coaches
AI Coaches assist patients with chronic diseases like:
- Diabetes.
- Hypertension.
- Chronic Obstructive Pulmonary Disease (COPD).
These agents assist patients by sending personalized reminders, providing dietary suggestions, and alerts.
Table: Traditional AI vs Agentic AI in Healthcare
| Feature | Traditional AI | Agentic AI |
| Workflow | Reactive, input-based | Automated & proactive |
| Decision Making | Single-task decision tasks | Multi-step reasoning tasks |
| Updates | Static algorithm updates | Fully automated continuous updates/ learning |
| Clinical Use | Supportive Function | Semi-autonomous Function |
| Value | Enhances process efficiency | Transformation to the clinical user and their practice |
Challenges & Ethical Considerations
1. Data Privacy & Compliance
The information stored in the healthcare industry is some of the most sensitive data. There is an absolute need to have good compliance with HIPAA and GDPR.
2. Transparency of AI Decisions
A physician must comprehend how an AI provides its recommendation, as this will create a basis for trust.
3. Bias & Fairness
AI solutions that are trained on biased datasets will result in disparate outcomes for various demographic groups.
4. Integration With Legacy Hospital Systems
Numerous healthcare institutions still utilize old and segregated systems that are not prepared for automated agents.
TL: DR
Agentic AI represents a major paradigm shift in healthcare. With my background in using AI for Operations Optimization, I feel that the use of agentic AI will reduce the workload of clinicians and automate their workflow in ways I have personally witnessed as the technology evolves. Hospitals that implement agentic AI sooner rather than later will realise a greater value in Clinical Quality and Operational Efficiency than those who do not.
Frequently Asked Questions
1. What is agentic AI in healthcare?
Agentic healthcare AI is an AI system that can independently analyze patient medical records, develop plans to improve the delivery of clinical care, and carry out multi-step tasks to improve the process of clinical care and hospital functioning.
2. Is agentic AI safe for clinical use?
Yes, there will always be a need to ensure that agentic AI systems are developed, regulated, and controlled by healthcare professionals before they can safely be used in a clinical setting.
3. How does agentic AI differ from generative AI?
Generative Artificial Intelligence is designed to produce content (text, images) and is not to be confused with Agentic Artificial Intelligence (AI) that acts independently by performing tasks and making choices using the information that is gathered from medical information/data.
4. Can agentic AI replace doctors?
No. Agentic AI can improve upon existing clinician skill sets, but cannot take the place of medical decisions, compassion, or ethical decisions.
5. What hospitals are already using agentic AI?
Many of the best hospitals are utilizing agentic AI systems to enhance or improve Triage, Diagnostic, and workflow efficiencies.
