Skip to main content

Master AI Medical Practice Certification · Level 1

AI Foundations for Medical Practices

Build a responsible AI foundation for patient communication, scheduling, front-office work, administrative documentation, revenue cycle, quality improvement, security, technology, governance, and practice leadership.

Enroll in Level 1 Program overview
Level
1
Modules
16
Estimated time
40 hours
Curriculum
Version 2026.4

Six-level pathway

Every level of the MAMPC program

Levels are completed in order. Each has its own modules, knowledge checks, final examination, and certificate; Levels 3 to 5 add a reviewed capstone and Level 6 a teach-back assignment.

  1. Level 1 · Foundations

    AI Foundations for Medical Practices

    40 hours · 16 modules · Open for enrollment

    • Modern Artificial Intelligence for Medical Practice Teams
    • What AI Gets Wrong in Healthcare Work, and Why It Sounds Right
    • Protected Health Information, HIPAA and Where Patient Data Goes
    • Accountability and the Clinical Line: Who Owns What AI Produces
    • Researching Payer Rules, Regulations and Guidance With AI, and Checking Their Status
    • Prompt Engineering for Medical Practice Administration
    • and 10 more

  2. Level 2 · Certified Professional

    Certified AI Medical Practice Professional

    40 hours · 14 modules · Open for enrollment

    • From Foundations to Practice: The Level 2 Operating Model
    • Prompting Architecture for Practice and Payer Tasks
    • The Practice Prompt Library: Ownership, Versions and Retest Triggers
    • Controlled Drafting From a Verified Patient File
    • Reviewing Referrals, Faxes and Outside Records Against a Checklist
    • The Signed Note: Reviewing AI-Captured Documentation Before Signature
    • and 8 more

  3. Level 3 · Advanced Operations

    Advanced AI Practice Operations

    40 hours · 14 modules · Open for enrollment

    • From Task to Operation: Running Practice AI at Scale
    • Mapping the Work Before Automating It: Front Desk, Inbox, Documentation and Billing Office
    • Risk-Tiering Practice AI by Patient Consequence and Reversibility
    • Writing a Procedure With Hard Stops a New Hire Can Follow
    • Building a Practice Knowledge Corpus From Payer Policies, Manuals and Practice Documents
    • Retrieval Failure Modes: Superseded Guidance, Wrong Payer and Vacated Text
    • and 8 more

  4. Level 4 · Master Certification

    Master AI Medical Practice Certification

    40 hours · 14 modules · Open for enrollment

    • What a Practice Owes: Accountability for AI Across a Medical Practice
    • Writing the Practice AI Governance Programme
    • The AI Decision Record and Surviving Staff and Ownership Turnover
    • The Regulatory Map: What Binds the Practice, the Manufacturer, the Developer and the Payer
    • Due Diligence on a Healthcare AI Supplier
    • Validation Evidence, Published Accuracy and the Practice's Own Acceptance Test
    • and 8 more

  5. Level 5 · Automation Specialist

    AI Healthcare Operations Specialist

    40 hours · 14 modules · Open for enrollment

    • What an Automation May Do in a Medical Practice: Authority and Its Limits
    • Orchestrating Intake, Registration, Referrals and Document Requests
    • Orchestrating Recalls, Reminders and Patient Outreach
    • The Integration Map and Data Contracts
    • EHR and Practice-Management Integration: Read First, Write With Approval
    • Claims, Payments, Refunds and Segregation of Duties
    • and 8 more

  6. Level 6 · Certified Instructor

    Certified AI Healthcare Instructor

    40 hours · 14 modules · Open for enrollment

    • Teaching a Practice Team, and Why the Lunchtime In-Service Fails
    • Designing a Session Backwards From the Behaviour at the Desk and in the Exam Room
    • Curriculum Accuracy and Keeping Practice Material Current
    • Facilitating a Mixed Room: Clinicians, Support Staff, Front Desk and Billing
    • Running a Demonstration That Shows the Tool Failing
    • Designing Hands-On Labs on Fictional Patients, Charts and Claims
    • and 8 more

Course outline

Level 1 in detail: what the curriculum covers

Each module connects practical administrative AI capability to patient privacy, minimum-necessary access, qualified review, clinical boundaries, source verification, cybersecurity, auditability, escalation, and accountable decisions.

Module 01

4 lessons

Modern Artificial Intelligence for Medical Practice Teams

What the systems sold as "AI" in a physician practice actually are, and why that changes how you check them. This module separates rules, machine learning and generative AI, explains language models and speech-to-text, opens up retrieval, tools and agents, and maps practice tool categories to the terms, FDA's product line and what physicians report.

  • Rules, Machine Learning and Generative AI in the Practice 35 min
  • How Language Models and Speech-to-Text Produce Their Output 40 min
  • Retrieval, Tools and Agents Inside Practice Products 40 min
  • A Field Guide to Practice AI Tool Categories and Their Vocabulary 45 min

Module 02

4 lessons

What AI Gets Wrong in Healthcare Work, and Why It Sounds Right

Why fluent AI output can be wrong in ways that are hard to see. This module covers confabulated rules and citations, stale guidance, omissions in summaries, elaboration on a planted false detail and prompt sensitivity, shows how to read healthcare AI evidence by what each study actually tested, and builds habits that resist automation bias.

  • Confabulated Rules, Citations and Stale Guidance 35 min
  • Omissions, Planted False Details and Prompt Sensitivity 40 min
  • Reading Healthcare AI Evidence by What Each Study Tested 40 min
  • Automation Bias and the Discipline of Doubt 40 min

Module 03

4 lessons

Protected Health Information, HIPAA and Where Patient Data Goes

What patient information HIPAA protects, in any form including recordings, and where it goes when someone uses an AI tool. This module covers covered entities and Part 2 records, vendor terms, business associates and their agreements, permitted uses and minimum necessary, real de-identification, and a method for deciding what may go into which system.

  • Covered Entities, Protected Health Information and Part 2 Records 35 min
  • Vendor Terms, Business Associates and Business Associate Agreements 45 min
  • Permitted Uses, Minimum Necessary and Real De-identification 45 min
  • Can I Put This Into This System? A Decision Method 40 min

Module 04

4 lessons

Accountability and the Clinical Line: Who Owns What AI Produces

The duties that do not move when an AI tool helps. This module covers the physician accountability that FSMB guidance describes, AMA policy on consent and final review, the line between administrative support and clinical judgment under state examples and Medicare supervision rules, and how staff route every clinical output to a named licensed clinician.

  • The Physician Stays Accountable: FSMB Guidance and What Boards Regulate 35 min
  • AMA Policy on Consent, Final Review and Disclosure, and What It Binds 35 min
  • The Administrative Line: Unlicensed Practice, Diagnostic AI and Supervising People 40 min
  • FDA's Decision Support Line and Routing Every Clinical Output to a Clinician 40 min

Module 05

4 lessons

Researching Payer Rules, Regulations and Guidance With AI, and Checking Their Status

How to research a payer rule, regulation or guidance document with AI as an assistant, not an authority. This module builds a research workflow, verifies every citation at its official source, works through current examples of proposed, superseded and vacated rules, and shows how to record the source, the date checked and the status.

  • A Practice Research Workflow From Question to Verified Answer 35 min
  • Assistant, Not Authority: Verifying Every Citation at the Official Source 40 min
  • Proposed, Superseded or Vacated: Worked Status Checks on Current Rules 45 min
  • Courts, Agency Interpretations and Keeping a Dated Research Record 35 min

Module 06

4 lessons

Prompt Engineering for Medical Practice Administration

How to write prompts for administrative work in a physician practice, and what prompts cannot do. This module sets out a structured prompt, a data check before any prompt, the limits shown by research on planted false details and the jagged frontier, and draft patterns for schedules, letters, forms, policy summaries, training and translation.

  • The Structured Administrative Prompt: Eight Parts Ending in a Reviewer 35 min
  • Before the Prompt: Data Class, Minimum Necessary and Fictional Material 35 min
  • What a Better Prompt Cannot Fix: Planted Details and the Jagged Frontier 40 min
  • Draft Patterns for Schedules, Letters, Forms, Policy Summaries, Training and Translation 45 min

Module 07

4 lessons

Patient Communication With AI Drafts: Messages, Letters, Reminders and Translation

Where AI drafting helps patient communication and where it must stop. This module reads the portal-reply studies by what they measured, routes clinical messages to a licensed clinician, explains California's AB 3030 disclaimer as a state example, and sets limits for reminders, plain-language letters and machine translation.

  • AI-Drafted Portal Replies: What Three Studies Measured and Missed 40 min
  • Sorting Administrative From Clinical Messages and Routing Them to a Clinician 35 min
  • Disclosing AI in Patient Messages: California AB 3030 and AMA Policy 35 min
  • Reminders, Plain-Language Letters and Translation Review 40 min

Module 08

4 lessons

Documentation, Ambient Scribes and the Signed Record

How ambient scribes and AI transcription turn a visit into a draft note, and why the draft is not the record until the clinician reviews and signs it. This module covers what the randomised trials found, Medicare's signature rule for AI-transcribed entries, E/M documentation principles, recordings as identifiable data and the staff role.

  • What Ambient Scribes and AI Transcription Do, and What They Do Not 40 min
  • What the Randomised Ambient Scribe Trials Found 35 min
  • The Signature on an AI-Transcribed Entry: What Medicare Requires and What It Means 35 min
  • Reviewing a Draft Note Before Signature: E/M Principles, Note Length and the Staff Role 40 min

Module 09

4 lessons

AI in Coding, Billing and the Revenue Cycle

Where AI helps with eligibility, claim scrubbing, denials, appeals and code suggestions, and where it must stop. This module covers the HIPAA code sets and documentation-based coding, the coder's judgment, what three surgical coding studies found, and why unreviewed AI codes can create False Claims Act and overpayment exposure.

  • Where AI Helps in the Revenue Cycle and Where It Must Stop 35 min
  • Code Sets, Provider Documentation and the Coder's Judgment 40 min
  • What Three Surgical Coding Studies Found About Language Models 35 min
  • Knowing Submission, Overpayments and OIG's Billing Risk Areas 45 min

Module 10

4 lessons

AI for the Front Office: Scheduling, Phones, Reminders and Records Requests

How to use AI at the front desk without crossing into triage or tripping federal rules. This module covers booking bots and phone agents as administrative support, reminder calls and AI voices under the TCPA, tracking tools and records requests, internal knowledge search, and how to rank front-office uses by risk.

  • Scheduling, Intake and Phone Automation as Administrative Support 40 min
  • Automated Reminders, Recalls and AI Voices Under the TCPA 40 min
  • Tracking Tools, Portals and Records Requests at the Digital Front Door 45 min
  • Front-Office Knowledge Search, Prompt Injection and Ranking Uses by Risk 40 min

Module 11

4 lessons

Building Repeatable Practice AI Workflows

How to turn ad hoc AI use into a controlled process a practice can repeat, review and explain. This module builds a six-stage workflow, designs the checks that stop a wrong output becoming a wrong action, strengthens the review step against automation bias, and sets risk-based monitoring and audit records.

  • From Chatbot to a Staged Practice Workflow 40 min
  • Designing So a Wrong Output Is Not a Wrong Action 40 min
  • Designing the Review Step Against Automation Bias 40 min
  • Worked Workflows, Risk-Based Monitoring and Audit Records 45 min

Module 12

4 lessons

AI Agents and Autonomous Systems in Practice Operations

What changes when an AI tool can act rather than only answer. This module explains agents and their tools, ranks agent uses from reading to submitting, borrows autonomy vocabulary for control points and stop switches, sets Security Rule expectations for anything touching ePHI, and defends against instructions hidden in incoming documents.

  • What an AI Agent Is, and What Changes When It Can Act 40 min
  • Agent Risk Levels: Reading, Drafting, Writing, Messaging and Submitting 40 min
  • Autonomy Vocabulary, Human Control Points and Stop Switches 40 min
  • Instructions Hidden in Incoming Documents, and Defending Against Excessive Agency 45 min

Module 13

4 lessons

Cybersecurity, the HIPAA Security Rule and Vendor Evaluation

How the Security Rule already covers an AI tool that touches electronic patient information: what is required and what is addressable, how the risk analysis is updated when a tool arrives, where the data is actually stored, and how to read a vendor's security claims, authentication and breach reporting terms.

  • The Security Rule as It Stands, and the Rule That Is Only Proposed 40 min
  • Updating the Risk Analysis When an AI Tool Arrives 40 min
  • Where the Data Actually Lives: Cloud Hosting, Offshore Storage and a Texas Rule 40 min
  • Reading Vendor Claims, Choosing Authentication and Knowing the Breach Clock 40 min

Module 14

4 lessons

Practice AI Governance and the Compliance Programme

How a practice turns scattered AI use into governance it can explain: a written policy naming approved tools, prohibited data and acceptable use; AI folded into the compliance programme; frameworks placed accurately as voluntary, policy or binding; and the one governance duty that is a regulation, with the records, incidents and review that keep it honest.

  • The Written Practice AI Policy: Approved Tools, Prohibited Data, Acceptable Use 40 min
  • Fitting AI Into the Practice Compliance Programme 40 min
  • Placing Every Framework, Policy and Standard by Who It Binds 40 min
  • The Governance Duty That Binds: Decision Support Tools, Incidents and Review 40 min

Module 15

4 lessons

Practical Medical Practice AI Lab

Four hands-on labs on fictional practices and patients: find the planted errors and invented content in an AI-drafted letter, reminder script and payer summary; expose a fabricated citation and rebuild the prompt; review a referral extraction and a failed de-identification; then grade a vendor against business associate requirements and write a tool policy.

  • Lab: Find the Planted Errors in an AI-Drafted Letter, Reminder Script and Payer Summary 45 min
  • Lab: Expose the Fabricated Citation, Check the Status, Rebuild the Prompt 45 min
  • Lab: Review a Referral Extraction, Instruction-Like Text and a Failed De-identification 45 min
  • Lab: Grade a Vendor Against Business Associate Requirements and Write the Tool Policy 45 min

Module 16

4 lessons

Capstone: The Medical Practice AI Implementation Plan

Write a sixteen-section implementation plan for one practice task: choose a low-risk, non-sensitive first use with a baseline from your own records, settle the data class, vendor status and risk analysis, set controls, the clinical line and named reviewers, then run a bounded pilot with honest metrics, stop signals and a review cycle.

  • Choosing the First Task and Building a Baseline From Your Own Records 45 min
  • Data Class, Vendor Status and the Risk Analysis Update in the Plan 45 min
  • The Clinical Line, Named Reviewers, Training and the Records the Plan Keeps 45 min
  • The Bounded Pilot, Honest Metrics, Failure Indicators and Improvement 45 min

Learning outcomes

What you will be able to do

  • Evaluate AI tools for medical-practice administrative use cases, limitations, patient privacy, security, vendor risk, and clinical boundaries.
  • Create reliable prompts and verification procedures for scheduling, communication, documents, staff knowledge, reporting, and approved marketing.
  • Improve front-office and revenue-cycle workflows without fabricating codes, payer rules, authorizations, reimbursement guidance, or clinical advice.
  • Design automations with minimum-necessary access, permissions, approvals, exceptions, audit trails, output checks, and human escalation.
  • Plan secure integrations and narrowly scoped agents around approved practice systems, authoritative resources, and responsible owners.
  • Build an AI adoption roadmap with governance, risk controls, workforce training, operational metrics, implementation priorities, and measurable return on investment.

Assessment

Level 1 Final Comprehensive Examination

The final assessment measures how well you apply the curriculum to realistic scheduling, communication, documentation, revenue-cycle, quality, security, technology, governance, and leadership scenarios without crossing into clinical decision-making.

Questions
50
Time limit
90 minutes
Passing score
80%
Maximum attempts
3

Lead responsible AI adoption in medical-practice operations

Start with the vendor-neutral foundations, privacy controls, human-review requirements, and administrative workflows covered across the complete Level 1 curriculum.

Enroll in Level 1 Program overview

Independent professional education

MAMPC is an independent professional education program focused on administrative and operational uses of AI. It is not a medical, nursing, or other healthcare license or professional credential and does not replace physician or nursing judgment, clinical protocols, legal counsel, privacy or compliance review, payer requirements, or applicable law. The program does not teach diagnosis, prescribing, individualized treatment, clinical decision-making, or unauthorized coding and reimbursement guidance. AI-generated content requires qualified human review, and patient information must be handled through approved systems in accordance with applicable privacy and security requirements. The program is not endorsed by any government agency, regulator, healthcare system, medical association, professional organization, or standards body. No professional education hours or approvals are claimed, and no clinical outcome, reimbursement, compliance, patient-experience, operational, or financial result is guaranteed.