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Master AI Medical Practice Certification · Digital course

MAMPC Level 3 — Advanced AI Practice Operations

Self-paced enrollment in Level 3 of the Master AI Medical Practice Certification: Turn individual AI habits into practice operations: workflow maps, written standard operating procedures, governed knowledge bases, controlled integrations with the practice-management system and electronic health record, risk tiering, quality-assurance sampling, escalation ladders, and honest performance measurement.

Modules
14
Estimated time
40 hours
Access
Self-paced

Single-user enrollment

$549.00

One-time purchase

Enrollment includes

Responsible AI training built for medical-practice operations

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.

Curriculum at a glance

From AI foundations to healthcare operations leadership

View all 14 modules
  1. Module 01

    From Task to Operation: Running Practice AI at Scale

    Level 3 opens with the shift from one careful AI-assisted task to work the whole practice runs every day: how volume, handoffs and staff turnover change the risk, who owns an operation while the clinician still owns the note, where this work belongs in the practice compliance programme, and what the published adoption numbers do and do not show.

  2. Module 02

    Mapping the Work Before Automating It: Front Desk, Inbox, Documentation and Billing Office

    Before a practice automates anything it has to know how the work really runs. This module maps a workflow as staff actually perform it, marks every handoff and every movement of patient information, measures a baseline of volume, cycle time, rework and error, and reads the published documentation studies for what they measured and what they did not.

  3. Module 03

    Risk-Tiering Practice AI by Patient Consequence and Reversibility

    A practice cannot review everything to the same depth, so it has to decide what deserves the most attention. This module builds a tier grid from patient consequence, reversibility, data class and verifiability, attaches review depth and reviewer role to each tier, runs the tiering register, and separates tiering from the device question entirely.

  4. Module 04

    Writing a Procedure With Hard Stops a New Hire Can Follow

    How to turn a tiered AI operation into a written practice procedure someone can actually follow on their second week: steps that leave evidence, hard stops nobody can click past, a named owner for every step, a review step designed against over-reliance, and a walkthrough test on a person who has never done the task.

  5. Module 05

    Building a Practice Knowledge Corpus From Payer Policies, Manuals and Practice Documents

    How a practice assembles the reference documents an AI tool is allowed to read: choosing what goes in and refusing what nobody will own, tagging every document by payer type, state, plan year and effective date, protecting the provenance and integrity of the files themselves, and running a review cycle that removes a document instead of letting it rot.

  6. Module 06

    Retrieval Failure Modes: Superseded Guidance, Wrong Payer and Vacated Text

    The ways a grounded, citation-bearing answer still states the wrong rule, each worked on a recorded example: a guidance version replaced weeks after it was issued, a bulletin a court partly struck down, regulation text still displayed after it was vacated, a criterion that binds developers, and documents written to be read by a tool.

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.