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    Audit, Compliance & Risk. Independent eyes.Defensible outcomes.

    Independent audits of coding, clinical documentation and revenue integrity, and standing compliance programs that keep you ready all year instead of scrambling before a review. We apply the same scrutiny to AI and data systems.

    A short call with a senior expert. No patient information needed.

    What gets reviewed

    • Coding & documentation
    • Charges & revenue integrity
    • Policies & controls
    • AI & data systems
    • Vendor risk

    How an audit runs

    1. 1Scope and sample agreed up front
    2. 2Tested against the rules
    3. 3Root cause, not just error counts
    4. 4Corrective actions tracked to close

    What you get

    • Findings you can act on
    • A defensible record
    • Audit-ready all year
    • Risk reduced early

    Audited against the rules that apply to you

    • Official coding guidelines
    • CMS Medicare manuals
    • NCCI edits
    • HIPAA Privacy, Security and Breach Notification Rules
    • False Claims Act
    • OIG compliance program guidance
    • Joint Commission standards
    • NIST AI Risk Management Framework

    Watch 45 seconds

    Audit-ready all year: how audit and analytics work

    Read the film as text
    1. Audit-ready all year.Not just the week before a review.
    2. What gets audited: the work, and the systems around it.Coding and documentation. Charges and revenue integrity. Policies and controls. AI and data systems. Vendor risk. Independent eyes on each one.
    3. How findings feed the next audit: every audit sets up the next one.Scope and sample agreed up front. Tested against the rules. Root cause, not just error counts. Corrective actions tracked to close. Then retest, and the findings shape the next scope.
    4. What gets measured: the numbers behind the findings.Error rate by category. Repeat findings. Time to close actions (illustrative charts). Agree the measure first. Report plainly.
    5. During Health.Know what an audit would find, before one is called. Book an audit-readiness call, or take the free readiness scorecard, at duringhealth.com.
    Industry pulseUpdated Oct 2026

    What is changing in audit and enforcement right now

    Dated facts, each with its source. This part of the page is refreshed regularly; the rest is built to last.

    • 710

      large health data breaches reported to HHS in 2025

      About 36% happened at business associates, the vendors that hold data for providers and plans. Who builds and runs your data layer is a security decision, not just a technical one.

    • 22,000+

      organizations the Joint Commission plans to offer a voluntary AI certification

      With the Coalition for Health AI, it issued guidance on responsible AI use on September 17, 2025, and said governance playbooks and a voluntary certification would follow.

    • $28.8B

      Medicare fee-for-service improper payments in FY 2025 (6.55%)

      Medicare Advantage (Part C) was 6.09%, or $23.67 billion, mostly diagnoses its documentation did not support. Medicaid was 6.12%, or $37.39 billion, and insufficient documentation drives most Medicaid errors, which is generally not a sign of fraud.

    • ~550

      Medicare Advantage contracts CMS says it will audit every year

      Up from about 60 a year, with CMS growing its medical coders from 40 to about 2,000. CMS has been notifying plans of new risk-adjustment audit rounds through 2026, including payment year 2024 on August 28, 2026.

    $6.8B

    False Claims Act recoveries in fiscal year 2025, a record

    More than $5.7 billion related to health care, led by managed care, prescription drugs and medically unnecessary care. A record 1,297 whistleblower suits were filed.

    Book an audit-readiness call

    Every number links to its source.

    Myth vs fact

    What most organizations get wrong about audits

    • Myth

      “We had no findings last year, so we are fine.”

      Fact

      A clean result depends on what was sampled and how. Independent testing finds the patterns an internal check can miss, and shows a regulator that you looked.

    • Myth

      “Compliance is a once-a-year project.”

      Fact

      Regulators ask what you did when you found a problem, and how fast. A standing program with routine testing, training and tracked fixes holds up. A binder assembled the month before does not.

    • Myth

      “Our vendors and AI tools are their problem.”

      Fact

      Business associates and AI systems that touch your data are part of your risk. Contracts, access reviews and monitoring need an owner on your side.

    What we deliver

    Four things you can hold us to.

    • Coding & documentation audit

      Independent review of coding accuracy, documentation completeness and classification validation, with root-cause findings.

      What you get

      • Random and targeted samples across inpatient, outpatient and professional coding
      • Accuracy and documentation findings with root causes
      • Provider and coder education plans
      • Repeat testing to show improvement
    • Revenue integrity audit

      Charge capture, tariff and charge-master review to surface leakage before it becomes recovery work.

      What you get

      • Charge capture and charge-master review
      • Missed and incorrect charge detection
      • Billing tested against payer and CMS rules, including NCCI edits
      • Overpayment findings with a documented process for returning them
    • Compliance programs

      Policies, controls, training and audit-readiness run as an ongoing program, aligned to the regulations and accreditation standards of each market.

      What you get

      • Policies, procedures and a written code of conduct
      • A risk assessment and an annual work plan
      • Training, a reporting line and an investigation workflow
      • Monitoring dashboards for leadership and the board
    • AI & data governance audit

      Review of model oversight, PHI handling, traceability and explainability across agentic and analytical systems.

      What you get

      • An inventory of AI tools and data flows
      • Review of oversight, bias testing and explainability
      • Checks on PHI handling, access and logging
      • Findings mapped to your policies and to the NIST AI Risk Management Framework
    The full map

    Everything we do in audit, compliance and risk

    Ten service areas, from a single coding audit to a standing compliance program. Most engagements start in one and grow into the others.

    • Coding & documentation audit

      Is the record supported, and is the code right?

      • Inpatient, outpatient and professional coding
      • Documentation completeness and specificity
      • Risk-adjustment diagnosis support
      • Provider and coder education
      Read: NCCI edits explained
    • Revenue integrity audit

      Is every charge captured and billed correctly?

      • Charge capture and charge-master review
      • Missed and duplicate charges
      • Billing against payer and CMS rules
      • Leakage and overpayment findings
    • External audit response

      When a payer or contractor asks for records.

      • Additional documentation requests and post-payment reviews
      • Risk-adjustment documentation reviews
      • Appeal support
      • An audit calendar with owners and deadlines
    • Compliance program design & operation

      A program that works between audits.

      • Policies, code of conduct and committee structure
      • Annual risk assessment and work plan
      • Training and reporting line
      • Board and leadership reporting
    • HIPAA privacy & security assessment

      Finding gaps before an incident does.

      • Security risk analysis
      • Access and audit-log reviews
      • Breach response planning
      • Policy and training review
      How we handle sensitive data
    • Risk assessment & monitoring

      Knowing where to look next.

      • Enterprise compliance risk assessment
      • Data analytics to find outliers
      • Continuous monitoring of key measures
      • Issue tracking to closure
    • AI & data governance audit

      The same scrutiny for models and pipelines.

      • AI tool and data-flow inventory
      • Oversight, bias and explainability review
      • PHI handling in AI workflows
      • Alignment with recognized frameworks
      Read: the agentic AI governance checklist
    • Vendor & business associate oversight

      Risk that arrives through your suppliers.

      • Business associate inventory and agreements
      • Vendor security and compliance reviews
      • Access reviews and offboarding
      • Contract clauses that matter
    • Training & culture

      People who know what good looks like.

      • Role-based compliance training
      • Coding and documentation education
      • Leadership briefings
      • Measuring whether training changed behavior
    • Corrective action & remediation

      Proof that the fix worked.

      • Root-cause analysis
      • Corrective action plans with owners
      • Retesting after changes
      • Evidence packages for regulators and boards
    How we start

    How an audit runs: scope it, test it, then prove the fix

    You see the method before the work starts and the evidence when it ends.

    1. Scope

      Agree what is reviewed, the rules applied and how the sample is drawn.

      You get
      A written scope and sampling plan

    2. Test

      Independent reviewers test the sample against the rules and the record.

      You get
      Documented test results

    3. Report

      Findings with root causes, risk ratings and the fix for each.

      You get
      A findings report and a prioritized action plan

    4. Close

      Track the corrective actions, retest and report progress.

      You get
      Evidence the fixes worked, ready for a regulator or your board

    Who it is for

    Who we audit for

    • Hospitals and health systems

      The problem

      Many audit sources at once: payers, contractors, accreditors and your own team.

      A good first project

      A focused coding or revenue integrity audit.

    • Physician groups and MSOs

      The problem

      Fast growth outpaces the compliance program.

      A good first project

      A baseline compliance risk assessment and work plan.

    • Medicare Advantage and risk-bearing organizations

      The problem

      Risk-adjustment documentation must hold up under review.

      A good first project

      A diagnosis documentation audit.

    • Health-tech companies and vendors

      The problem

      Customers ask for proof of security and AI controls before they sign.

      A good first project

      An independent AI and data governance review.

    Checklist

    Are you audit-ready all year?

    If you cannot tick most of these today, the program is the project, before the next audit arrives.

    • You have a written compliance program and a named compliance officer.
    • A risk assessment and an annual work plan exist, and were followed.
    • Coding accuracy is tested on a sample, and the results are shared and fixed.
    • You know your open audits, their deadlines and who owns each response.
    • Overpayments you find are tracked and returned within the required timeframes.
    • Staff training is recorded and tied to the risks you found.
    • Your HIPAA security risk analysis is current and covers every system with PHI.
    • Business associates and AI tools are inventoried, each with an owner.
    Ask your team

    Three questions to ask your team on Monday

    1. 01

      If a payer or regulator asked for 50 records tomorrow, how long would it take to assemble and check them?

    2. 02

      The last time we found an error, what did we change so it would not recur?

    3. 03

      Which vendors and tools touch our patient data, and who reviews them?

    If the answers are slow or different in every room, that is where we start.

    Questions

    Questions we hear most.

    More about how we handle sensitive data in our trust center.

    What makes an audit independent?

    The reviewers do not report to the area being tested, and the sample and method are agreed in writing beforehand. That gives you findings that are harder to dismiss and that a regulator or board is more likely to trust.

    Do you audit AI systems?

    Yes. We review the inventory, oversight, testing for accuracy and bias, handling of PHI and the logs, and map the findings to your policies and to recognized frameworks such as the NIST AI Risk Management Framework.

    What happens if you find overpayments?

    We tell you what we find and document it. Medicare and Medicaid have rules about reporting and returning overpayments within set timeframes, so we organize the evidence to support your decision with counsel.

    Can you help us respond to a payer or government audit?

    We can help gather and check records against the rules and prepare responses. We are not a law firm, and legal strategy stays with your counsel.

    How do you choose the sample?

    We agree it with you in writing. A random sample gives an accuracy rate; a targeted one examines known risks. The size depends on volume and on what you need to be able to say about the result.

    How do you protect PHI?

    Only under a written agreement, including a business associate agreement where HIPAA applies, signed before any PHI is shared. We use the minimum necessary, role-based access, encryption and audit logging.

    How is an audit priced?

    By scope: what is reviewed, the sample and the reporting you need. We agree the scope and the deliverables first, so you know what you are buying.

    Next step

    Find the problem before an auditor does.

    Tell us what worries you: coding accuracy, a pending audit, a new AI tool. We will tell you what an independent review would cover and how we would report it.

    Please do not send patient information. Describe the situation without identifying anyone.