How Is AI Used in Healthcare? A Practical Guide for Clinicians

Using AI in Healthcare

One of the primary uses of AI in healthcare is to streamline clinical workflows, particularly for administrative tasks like documentation. Instead of replacing humans, artificial intelligence can help with routine charting in the background so clinicians can focus on patient care.

In this article, you’ll learn where AI fits into everyday clinical work, how clinicians across specialties are already using AI tools like Heidi, and why using AI in healthcare is proving to be a turning point in documentation, care quality, and clinician well-being.

Why AI Usage in Healthcare Matters Today

The truth is that healthcare is overloaded. Manual charting, back-to-back meetings, and nonstop record-keeping contribute to clinician burnout, now recognized by the World Health Organization (WHO) as a chronic workplace issue. According to a recent report on Health Worker Burnout, an estimated 30–60% of clinicians experience burnout, with administrative burden as a major driver.

AI helps tackle this issue at its source. Instead of adding another layer of tech, tools like Heidi works quietly to capture, format, and generate documentation in real-time. With this, there is less time clicking through electronic health records (EHRs) and more time focused on what matters: patient care.

Key Drivers Behind Using AI in Healthcare

• Burnout: AI reduces the administrative overload that contributes to clinician fatigue. By handling repetitive documentation tasks in the background, it enables uptime for direct patient interaction and rest.
• Workforce Pressure: There are fewer doctors seeing more patients. AI makes things run more smoothly by letting you finish notes faster, update EHRs faster, and move between consults more easily.
• Financial Stress: AI is a cost-effective alternative to hiring additional admin or scribe support. Practices can use AI to automate notetaking, letters, and reports instead of hiring more people, and it costs a lot less.
• Clinical Outcomes: When patient records are clear, consistent, and up-to-date, clinicians can easily pass them on. Because there is less room for error and more organized documentation, keeping up with care becomes easier.
• Digital Acceptance: Most clinicians prefer tools that fit naturally into existing workflows. AI delivers this by integrating smoothly into current practices, eliminating the need for retraining or major changes.

4 Practical AI Applications in Healthcare

AI is already transforming the way clinicians work every day in ways that are impactful and sustainable. This is true for both private practice and large hospital systems. Here are four key ways AI is being used in healthcare today:

1. AI in Patient Consultations

AI can securely capture the details of a patient visit and turn them into structured clinical notes without the clinician having to type.

For example, during a routine asthma check-up, the ambient AI listens to the conversation, summarizes key symptoms and treatment adjustments, and produces a complete note ready for the patient’s record. By removing the need for manual note-taking, the consultation stays focused on the patient, setting the stage for smoother workflows after the appointment.

2. AI for Workflow Optimization

Navigating through EHR systems usually entails endless clicks, duplicate data entry, and constant tab-switching. AI removes these bottlenecks by auto-generating well-formatted notes and adding them directly into any EMR.

AI can also streamline coding and billing by automatically identifying relevant codes immediately after the consultation. For instance, an initial consult for unexplained abdominal pain can be coded and billed before they leave, saving clinical time and reducing billing errors. This kind of automation opens the door for AI to assist with other repetitive but important tasks.

3. AI in Administrative Tasks

In the fast-paced and ever-evolving space of artificial intelligence, AI applications can now do even more types of non-clinical admin work. For example, Heidi Tasks uses AI to scan through session notes, detect follow-up actions, and list them accordingly for clinicians to view (all without lifting a finger).

Tasks can be assigned to specific team members as well. With the routine admin already in motion, you can focus on the next consult instead of chasing loose ends.

4. AI for Clinical Documentation

One of the most time-consuming parts of clinical practice is turning consultations into the records, letters, or reports that teams and patients can rely on. AI changes this by taking the details of a single consultation and producing documents such as referral letters, medical reports, or patient instructions that are all in your style and ready to approve.

Imagine, during a hospital ward round, you could finish one review and instantly have a physiotherapy referral, a GP discharge letter, and recovery guidance for your patient, all drawn from the same set of notes. It’s the fastest way to close the loop on care and keep every handoff seamless.

Real-World Examples of AI Use Cases in Healthcare

From small clinics to big hospitals, the healthcare industry is finding more ways to use artificial intelligence. Below are examples that show how different healthcare settings use AI to handle many patients, make it easier for teams to talk to each other, and get paperwork done without having to work after hours.

Example of AI Use in Healthcare - Private Practice

Private practices often face the pressure of balancing high patient volumes with effort-intensive admin tasks. GPs and solo practitioners manage not only patient care but also business operations. Time becomes a limited resource.

AI supports these settings by making documentation faster, more structured, and less mentally draining. It enables clinicians to complete their notes during consultations, rather than after hours, without sacrificing clinical accuracy or face time.

In fast-paced clinics like Tuggerah Family Doctors in New South Wales, this impact is already clear. Clinic founder Dr. Theresa Colina used to manage 15–20 minute appointments with little time left for accurate notes. "Heidi has given me back hours of my week," she shares. "I now finish my notes during consultations, not after."

The ability to use structured templates and tools, like 'Ask Heidi,' has helped her stay present with patients while keeping records compliant, as shared by Dr. Colina, who implemented AI at Tuggerah Family Doctors to streamline documentation in sessions.

Example of AI Use in Healthcare - Clinic Groups

Team-based practices depend on shared processes but also require flexibility. Documentation can easily become a problem at a behavioral health group or psychology clinic, especially when clinicians have many patients to see and EMR limits.

AI allows for standardized templates that adapt to different specialties and workflows. It removes the tradeoff between presence and paperwork, so teams can focus more on clinical collaboration and less on formatting notes.

At Indiana Health Group (IHG), one of the largest behavioral health practices in Indiana, this is precisely what happened. Psychiatrist Dr. Chris Bojrab shares, "Heidi gave us a way to maintain clinical nuance while eliminating hours of admin work."

The team saved over 120,000 minutes of admin time in just five months, as seen in the approach taken by Dr. Bojrab and his colleagues at Indiana Health Group, where AI now supports consistent and timely documentation.

Now let’s move to other groups like outpatient specialty centers, where documentation demands may even be higher.

At Four Wings Psychology in Ottawa, Clinical Director Dr. Sarah Bellefontaine faced the exhausting tradeoff between client engagement and after-hours note completion. "Heidi has transformed my evenings," she says. "Instead of writing notes after dinner, I get to spend that time with my family."

By building templates for therapy sessions, clinical supervision, and team meetings, her practice now captures rich, structured documentation during work hours, as illustrated by Dr. Sarah Bellefontaine’s use of AI at Four Wings Psychology, allowing her team to complete notes during work hours.

Example of AI Use in Healthcare - Hospital Trusts

There are many levels of care in hospitals, and things tend to move quickly. Teams are often made up of people from different fields, and problems with paperwork can slow down discharges, break up continuity, and make people feel burned out.

AI helps hospital teams stay efficient by capturing and structuring information from patient interactions, turning it into intake notes, referral letters, and medical certificates. It adapts to the rapid pace of multidisciplinary settings without adding extra tech steps.

The shift is well underway at Compass House Surgery in the UK, a large NHS practice with over 15,000 patients. Nurse Partner Ian Parsonage recalls, "Before Heidi, we were constantly staying late to catch up on notes. Now, we’re finishing documentation in real time."

The staff uses AI across supervision, in-clinic consults, and telephone triage, as demonstrated by the team at Compass House Surgery, where documentation time has been cut by up to 60%.

The daily grind of manual and fragmented documentation slows everything down for many clinicians. AI not only makes things easier, but it also enhances established systems with automation that works the way clinicians do. Whether you're a solo GP or part of a larger care team, Heidi can help you practice in a smarter way.

Try Heidi: The Smart Way to Use AI in Healthcare

Heidi isn’t just a documentation tool; it’s a clinician-first platform that quietly integrates into your workflow and accelerates everything you already do well. From capturing conversations to structuring summaries, Heidi helps you stay focused without sacrificing compliance or speed:

• Capture consults as they happen: Heidi listens in the background and turns spoken interactions into structured, clinically sound notes.
• Review and approve in seconds: Notes are intelligently preformatted and editable, tailored to your documentation style.
• Push notes into your system: Whether through integrations or simple copy-paste, Heidi gets your notes where they need to be, fast.

Start using AI that works like you do: Heidi is built by clinicians for clinicians.‍

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Frequently Asked Questions about the Use of AI in Healthcare

What types of AI are used in healthcare?

Generally, the five main types of AI used in healthcare include ambient AI, predictive AI, conversational AI, machine learning (ML), and robotic process automation (RPA). For example, a combination of ambient AI and machine learning is used in the healthcare industry to streamline administrative tasks and help clinicians use EHRs more efficiently and effectively.

Is AI safe to use in clinical settings?

Yes, AI can be used safely in clinical settings as long as it complies with regulations and standards that protect patient privacy, ensure data security, and give clinicians documentation control. For example, AI-based systems in the US must adhere to the Health Insurance Portability and Accountability Act (HIPAA), while the General Data Protection Regulation (GDPR) must be followed in Europe. See how Heidi ticks all your compliance and safety boxes.

What AI tools are used in hospitals?

Hospitals are increasingly using artificial intelligence tools like AI medical scribes and ambient voice technology to help keep up with the demands of healthcare in the modern age: patient volumes, staff retention, compliance requirements, and more. These AI tools help ease the administrative burden of documentation while improving care coordination and patient outcomes.