Start Here: Tell Us About Your World

• Roughly how many patient encounters does your organization code per year? Options: < 50k, 50k–150k, 150k–500k, 500k–1M, > 1M
• Which role(s) currently own day-to-day coding operations and final code sign‑off? Options: VP Revenue Cycle, Coding Director, HIM Manager, CDI Manager, Revenue Integrity, Shared/Hybrid, Other
• Which EHR and billing systems are primary in your coding and charge capture workflow? Options: Epic, Cerner/Oracle, Meditech, Allscripts, Athenahealth, NextGen, Custom/Other
• How is your coder team structured (FTE count, onsite vs remote, senior vs junior mix)? Please describe briefly.
• What are the top three operational priorities for coding/revenue cycle this year? Options: Reduce backlog, Increase coding accuracy, Recover lost revenue, Reduce days-in-AR, Lower denials, Improve productivity per coder, Compliance & audit readiness, Other

What's Keeping You Up at 2 AM?

• If you lost 20% of your senior coding capacity overnight, what single risk would surface first? Options: Backlog growth, Increased denials, Revenue loss from undercoding, Compliance exposure, Operational paralysis, Other
• How many charts are currently backlogged, and how is that backlog distributed by age? Options: < 1 week, 1–2 weeks, 2–4 weeks, 1–3 months, > 3 months
• Which stages in your workflow most often slow coding (select up to three)? Options: Incomplete documentation, Chart routing delays, EHR access/navigation, Clinical clarification requests, Disagreement on code assignment, Claims system synchronization, Other
• When backlog or delays occur, how does that effect your team’s morale and turnover? Options: High burnout/turnover, Noticeable stress but stable, Occasional frustration, No significant impact
• Tell us about a recent day when coding felt unmanageable — what happened and who had to cover?

Where Are You Losing Dollars Without Knowing?

• How confident are you that your current process captures all reimbursable diagnoses and procedures? Options: Very confident, Somewhat confident, Unsure, Not confident
• Do you have an estimate of annual revenue leakage from undercoding, denials, or missed bundles? Options: < $100k, $100k–$500k, $500k–$2M, $2M–$10M, Unknown/not estimated
• Which payer problems create the most financial pain today? Options: Post-payment audits, Frequent denials, Underpayments, Complex value-based rules, Late payments
• When you find lost revenue or denied claims, what is the root cause most often identified? Options: Undocumented comorbidities, Incorrect CPT/HCPCS, Missed coding opportunities (add-ons/ modifiers), Clinical documentation gaps, System integration errors, Other
• Describe a recent example where better coding accuracy would have changed the financial outcome—what was the impact?

How Far Are You From Confident Coding?

• If a payer audited a random sample of 500 charts today, do you expect material findings? Options: Likely material findings, Possible minor findings, Unlikely to find material issues, Unsure
• What is your current internal/full-time audit or accuracy benchmark for coding (select closest)? Options: > 98%, 95%–98%, 90%–95%, 80%–90%, < 80%, No formal benchmark
• Which error types appear most in audits or denials (choose up to three)? Options: Diagnosis omitted/under-coded, Procedure mis-mapped, Modifier misuse, Code selection inconsistent with docs, POA/documentation issues, Other
• What tools or processes do you currently use to measure accuracy and trace root causes? Options: Manual audits, Automated audit tools, Third-party auditors, Internal QA team, EHR reports, None
• How much trust do coding leaders and compliance believe they can place in automated code suggestions today? Options: High trust, Some trust with review, Skeptical, Against using automation

Who Holds the Keys — People, Process, and Politics

• Who are the essential decision-makers and influencers for piloting new coding technology, and who could block it? Options: Coding Director, VP Revenue Cycle, CFO, CMO/Quality, Compliance/Privacy, IT/CISO, Procurement, Clinician champions, Other
• What procurement, security, or contract constraints typically slow down pilots or integrations here? Options: Extended legal review, Data residency concerns, No external API access, Required indemnities, Vendor insurance requirements, Other
• How long does it usually take from pilot approval to go‑live for a new revenue cycle tool? Options: < 4 weeks, 4–8 weeks, 8–12 weeks, 3–6 months, > 6 months
• Who would be the day-to-day owner of a pilot (name/role), and who must we train to make it successful?
• Which stakeholder group will judge the pilot as a success first — finance, coding ops, compliance, or IT? Options: Finance, Coding Ops, Compliance, IT, Clinical leadership, Other

What Would Less Chaos Actually Look Like?

• Imagine your backlog is reduced by 80% and accuracy improved—what would that change in your daily operations and outcomes?
• Which three KPIs would you use to prove success for a pilot or rollout? Options: Coding accuracy, Days-to-final-code, Denial rate, Revenue recovered, Productivity per coder, Claims edit reduction, Compliance incidents
• What minimum improvement on those KPIs would you need to see before recommending expansion? Options: Small (5%–10%), Moderate (10%–25%), Significant (>25%), Unsure/Need guidance
• Which coding domains would you prioritize in a pilot (select up to three)? Options: Inpatient ICD-10, Outpatient/ED, PT/OT/SLP coding, Procedure CPT/HCPCS, Observation, Radiology/Imaging reports, Other
• What acceptance criteria or specific test cases should the pilot include to validate readiness for scale?

Barriers That Kill Pilots Before They Start

• When pilots have failed here before, what single issue killed momentum the fastest? Options: Technical integration, No measurable ROI, Poor data quality, Staff resistance, Legal/regulatory hold, Budget constraints, Other
• What level of EHR or billing integration access can you provide for a realistic pilot (select closest)? Options: Full API access + test environment, Limited API + manual extracts, Only de-identified chart extracts, No direct access — vendor on site only, Unsure
• How does your compliance/legal team prefer we handle PHI and audit trails during pilots? Options: Encrypted transfers & BAA, De-identified dataset only, On‑premise processing, Vendor in secure cloud, Other
• What cultural concerns do coders raise about automation, and how have you addressed them historically?
• If we could guarantee a clear audit trail and human-in-loop controls, would that materially change your openness? Options: Yes — much more open, Somewhat, No change, Need to see examples

Small Steps That Prove Big Value

• Would you consider a 4–8 week pilot that uses your real charts to project accuracy and days-in-AR impact? Options: Yes — ready now, Yes — with approvals, Maybe — need more info, No
• What sample size and chart types would you want included to make the pilot credible? Options: 250–500 mixed charts, 500–1,000 focused cohort, 100–250 high-risk charts, Other
• Which pilot objective matters most to you initially (choose one)? Options: Accuracy benchmarking, Days-in-AR reduction, Denial risk identification, Coder productivity uplift, Integration validation, Other
• Who would be the pilot's executive sponsor and the operational lead (name/role)?
• Realistically, what resources can you commit for a pilot (time, FTEs, data access) and when could you start? Options: Immediate (2–4 weeks), Short (1–2 months), Quarter+ (3+ months), Resource-constrained/unsure
• What would your team need to see in a pilot report to sign off on commercial expansion? Options: Detailed accuracy by code type, Productivity uplift evidence, Financial ROI projection, Compliance audit trail, User feedback from coders, All of the above

Final Check: Commitments, Concerns, and Next Steps

• After this conversation, what is the single most important question you need answered before moving forward?
• Which stakeholders should we include in the next meeting to accelerate decision-making? Options: Coding Ops, IT/Integration, Compliance/Privacy, Finance, Procurement, Clinical Leadership
• What timeline would you prefer for a pilot proposal and statement of work? Options: This week, 1–2 weeks, 2–4 weeks, Longer than a month
• Is there any historical context, recent audits, or vendor evaluations we should review before proposing a pilot?
• Would you like us to prepare a tailored pilot plan that includes suggested KPIs, sample selection, and a compliance checklist? Options: Yes — please prepare, Maybe — need more details, No — not at this time

• Pre‑Work & Current State Confirmation
• Baseline Metrics & Consequence Workshop
• Live Chart Validation (Hands‑On Solution Experience)
• Impact Modeling, Acceptance Criteria & Pilot Scope
• Executive Validation & Go/No‑Go

• Have a clear decision path and timeline for moving from validation to a pilot engagement.
• One‑sentence Future State Reminder
• Demonstrate concrete, case‑level proofs that map directly to the customer's prioritized outcomes.
• Obtain explicit validation from customer SMEs that the AI results represent operationally meaningful improvement.
• Identify any exceptions, integration blockers, or documentation gaps that must be addressed to realize the benefits.
• Seller to deliver a case‑by‑case results packet showing suggestions, confidence, and mapped impact for the sample set.
• Customer coders to review and annotate any disputed cases and return feedback within the agreed timeframe.
• Technical owner to note any integration or workflow requirements observed during cases for the Impact Modeling meeting.
• Recap Validated Proof Points
• Agree on a quantifiable pilot model tied to validated proofs with explicit assumptions and sensitivity bounds.
• Define unambiguous acceptance criteria and scope that will be used to evaluate pilot success.
• Introductions & Purpose
• Seller to deliver the pilot statement of work with modeled projections and the acceptance criteria embedded.
• Customer to route pilot SOW for internal approvals and return feedback/approval date.
• Schedule pilot kickoff meeting with technical, coding, compliance, and project owners once SOW is approved.
• One‑slide Current State & Consequence
• Obtain an explicit executive go/no‑go decision and sponsorship for the pilot.
• Ensure executives understand the validated proofs and the measurable expected impact of the pilot.
• Agree on governance and reporting cadence for pilot oversight if approved.
• Customer executive to record and communicate the go/no‑go decision and name executive sponsor.
• Seller and Customer project leads to schedule pilot kickoff or iterate SOW based on executive feedback.
• Prepare a short 'what success looks like' dashboard template for pilot monitoring and share with governance stakeholders.
• Have a single, agreed one‑sentence statement of the current state and who is impacted.
• Confirm a secure list of de‑identified chart examples and baseline metrics to be used in the Solution Experience.
• Assign owners and deadlines for data delivery and any technical access required for pre‑runs.
• Customer to deliver specified set of de‑identified chart samples and baseline metric extracts by agreed date.
• Seller to provide data transfer instructions, data agreement template, and a pre‑run plan for the sample set.
• Assign single points of contact for clinical, coding ops, and IT for the Solution Experience.
• Recap Confirmed Current State
• Convert baseline metrics into explicit, quantified consequences that create urgency for change.
• Agree on and prioritize the specific operational outcomes the customer cares about for the Solution Experience.
• Define 2–3 measurable success signals that the upcoming validation must demonstrate.
• Seller to produce a short consequence model (spreadsheet) using the customer’s baseline metrics illustrating potential revenue, days‑in‑AR, and denial impact.
• Customer to validate and sign off on the baseline numbers and prioritized outcome list.
• Schedule the Live Chart Validation session and confirm which specific sample charts will be used as proofs.
• One‑sentence Current State
• Present Pilot Impact Model
• Live/Pre‑run Case Walkthroughs
• Present Baseline Metrics
• Proof Summary (Key Cases)
• Define Pilot Scope & Duration
• Translate Metrics to Consequences
• Comparison: AI vs Current Coded Result
• Pilot Recommendation & Expected ROI
• Data & Sample Chart Checklist
• Prioritize Outcomes
• Quantify Projected Accuracy and Impact
• Decision & Sponsorship Ask
• Set Acceptance Criteria & SLAs for Pilot
• Metric Baseline Capture
• Pre‑work & Timeline
• Next Steps / Decision Path
• Closeout & Immediate Next Steps
• Validation & Clarifying Questions
• Confirm Success Signals for the Experience
• Capture Exceptions and Operational Notes

• Configure HL7/FHIR integration with EHR and billing
• Deploy automated code suggestion (ICD-10/CPT/HCPCS) with confidence scores
• Train ML models on organization-specific clinical documentation
• Implement automated chart routing by complexity and risk
• Enable documentation gap alerts and denial risk flags
• Integrate auto-coded claims into billing queue for review
• Deploy real-time EHR coding assistant interface
• Provision coder productivity dashboards and scheduled reports
• Configure role-based review workflows and escalation rules
• Process historical backlog with bulk auto-coding
• Provision audit trail and claim traceability logs
• Deploy rules engine for claims quality and compliance

Configure HL7/FHIR integration with EHR and billing

• Which EHR and billing systems do you need integrated? Options: Epic, Cerner/Oracle, MEDITECH, Allscripts, Athenahealth, Surescripts, Custom/Other
• Which data exchange standards are required for your environment? Options: FHIR R4 APIs, HL7 v2.x (ADT/ORU/ORM), CCD/C-CDA, Custom API/webhook, Both FHIR and HL7 v2
• What interface types are needed (select all that apply)? Options: ADT (patient events), ORU (results), ORM (orders), Clinical notes/encounters (FHIR DocumentReference), Billing/claim transactions (837/EDI), Patient demographics/ADP sync
• What is your expected throughput (encounters/messages per day) for integration? Options: <1,000, 1,000-10,000, 10,000-50,000, 50,000-100,000, 100,000+
• Which authentication and network security methods must the integration support? Options: OAuth2 (SMART on FHIR), Mutual TLS (mTLS), VPN/IP allowlist, SAML/SSO, Other
• Are there any required field mappings, transformations, or code set translations we should prepare for? (list specific fields or examples)

Deploy automated code suggestion (ICD-10/CPT/HCPCS) with confidence scores

• Which code sets do you want enabled for suggestions? Options: ICD-10-CM, CPT-4, HCPCS Level II, All of the above
• What initial confidence threshold should be used to surface suggestions to coders? Options: >=95%, 90-94%, 80-89%, <80% (show all), Custom
• How should low-confidence suggestions be handled in workflow? Options: Auto-assign to human reviewer, Show with a caution banner, Suppress until reviewed by model retraining, Prefill but require explicit approval
• What are your acceptance criteria for suggestion accuracy on pilot (e.g., precision or agreement with gold-standard)? Please specify numeric targets if available.
• Should each suggestion include supporting text snippets (citation of clinical text) and explainability notes? Options: Yes - include snippet and rationale, Yes - snippet only, No - codes only
• What latency requirement do you have for returning suggestions in interactive workflows? Options: Real-time (<2s), Near real-time (2-10s), Interactive (10-30s), Batch/Background

Train ML models on organization-specific clinical documentation

• How many labeled/coded charts can you provide for initial training and validation? Options: <5,000, 5,000-20,000, 20,000-100,000, 100,000+
• What historical timeframe should training data cover (e.g., last 1 year, 3 years)? Options: Last 6 months, Last 1 year, Last 2-3 years, Custom
• Do you have a gold-standard annotated dataset (coder-validated) available? Options: Yes - complete dataset, Partial/limited annotations, No - need labeling assistance
• Where must model training and storage occur? Options: Vendor cloud, Customer cloud (BYO), On-premises only, Hybrid (model weights in cloud, data on-prem)
• What target performance metrics (precision, recall, top-1/top-3 accuracy) do you require for a successful training run?
• Who will own labeling, validation, and adjudication of training disagreements? Options: Customer, Vendor, Shared model (vendor validates sample)

Implement automated chart routing by complexity and risk

• Which routing criteria do you want to support (select all that apply)? Options: Confidence score thresholds, Predicted clinical complexity, Payer type, Specialty/clinician, Denial risk flags, Custom business rules
• How do you define complexity tiers (example: Simple / Moderate / Complex)? Options: Use vendor default tiers, Define custom tiers (we will provide rules), Hybrid - start with defaults then customize
• What percent of charts do you expect in each tier (approximate distribution)?
• Where should routed charts appear for coders (EHR worklist, vendor app, third-party queue)? Options: EHR worklist, Vendor coding app/portal, Third-party tasking system (e.g., ticketing), Both EHR and vendor app
• What escalation paths and SLAs should be applied for high-risk or time-sensitive charts? Options: Escalate to senior coder (24h SLA), Escalate to CDI/clinical review (48h SLA), Escalate to compliance immediately, Custom escalation rules
• What acceptance criteria will determine routing accuracy in the pilot?

Enable documentation gap alerts and denial risk flags

• Which denial-risk rules should be enabled initially (select all that apply)? Options: Missing modifiers, Insufficient clinical substantiation, Mismatched diagnosis-procedure, High-risk payer edits, Duplicate billing risk, Other
• What alert severity levels do you want (e.g., informational, warning, critical)? Options: Informational, Warning, Critical / Blocker
• How should alerts be delivered to users? Options: In-EHR popup/notification, Coder dashboard, Email digest, Ticketing system (e.g., ServiceNow)
• Should any alerts automatically hold claims from submission until resolved? Options: Yes - hold until remediation, No - informational only, Conditional hold based on severity
• What thresholds (confidence, severity) should trigger an alert? Options: High (must act), Medium (review recommended), Low (informational), Custom - will provide details
• What remediation workflow do you want when an alert is raised (assign to coder, open CDI task, require clinician addendum)?

Integrate auto-coded claims into billing queue for review

• Which billing / claims systems must receive auto-coded claims? Options: EHR billing module, Billing system (e.g., Cerner Rev Cycle, Oracle BIlling), Clearinghouse, Custom/Other
• How should auto-coded claims be flagged in the billing queue? Options: Auto-coded - review required, Auto-approved for submission, Auto-suggested (do not create claim until approved)
• Do you require a two-step approval process before claims are transmitted? Options: Yes - coder + billing review, Yes - coder + supervisor signoff, No - single-step review
• What volume of auto-coded claims do you anticipate per day to be pushed to billing? Options: <500, 500-2,000, 2,000-10,000, 10,000+
• What reconciliation, sampling, or QA controls do you require before claim submission? Options: Random sampling (X%), 100% review for certain codes/payers, Automated rule checks only, Other
• If a claim is rejected by billing, what rollback or remediation workflow should occur?

Deploy real-time EHR coding assistant interface

• Which EHR UI integration approach do you prefer? Options: SMART on FHIR app, Embedded webview within EHR, Native API integration, Standalone vendor UI linked from EHR
• Should the assistant allow inline editing of suggested codes and documentation notes? Options: Yes - full inline edit, Yes - suggest and require separate approval, No - view-only suggestions
• Who should be able to modify codes in-EHR (roles/permissions)? Options: Coders only, Coders + Clinicians, Clinicians only, Role-based configurable
• What UI training model do you prefer for go-live? Options: Vendor-led classroom/webinars, Train-the-trainer, Self-paced on-demand materials, Blended
• What latency/availability targets must the assistant meet for clinical workflows? Options: <1 second (imperceptible), <5 seconds, <15 seconds, Batch acceptable
• Do you require UI interactions to be captured in audit logs (who changed what and why)? Options: Yes, No

Provision coder productivity dashboards and scheduled reports

• Which KPIs must appear on dashboards (select all that apply)? Options: Charts/hour (productivity), Coder accuracy/quality, Backlog size and age, Days-in-AR, Denial rate and reasons, Top denied codes/payers, Custom metrics
• What reporting cadence do you require for scheduled reports? Options: Daily, Weekly, Monthly, Ad-hoc/on-demand
• Do you need role-based dashboard views (e.g., coder vs manager vs compliance)? Options: Yes, No
• Which export formats or integrations are required for reports? Options: CSV/Excel, PDF, API feed to BI tool, Direct EHR dashboard embed
• Would you like automated alerts for KPI threshold breaches (e.g., productivity drops, accuracy below target)? Options: Yes, No
• Who should receive scheduled reports and at what distribution list or groups?

Configure role-based review workflows and escalation rules

• Which roles should be included in review workflows? Options: Coder, Senior coder/QA, Coding supervisor, CDI (Clinical Documentation Improvement), Compliance/Revenue Integrity
• For which scenarios should escalation be automatic (e.g., suspected overcoding, high denial risk)? Options: Overcoding suspicion, High denial risk, Low confidence suggestions, Priority payers, Custom rules
• What SLA timelines do you want applied to each escalation level? Options: Same day (<=1 business day), 1-3 business days, 3-5 business days, Custom
• How should notifications be sent for escalations? Options: In-app notifications, Email, EHR task, Pager/alerting system
• Do you require automatic handoffs to other teams (CDI, compliance) and if so, what information should be included?
• Should the workflow include SLA tracking and reporting for each role? Options: Yes, No

Process historical backlog with bulk auto-coding

• How many historical charts comprise the backlog you want processed? Options: <5,000, 5,000-25,000, 25,000-100,000, 100,000+
• What is your desired timeline to clear the backlog? Options: 2 weeks, 1 month, 3 months, Custom timeline
• Do you want a phased pilot (sample subset) before full-run bulk processing? Options: Yes - pilot required, No - full-run
• What QA sampling rate or acceptance criteria do you require for backlog auto-coding? Options: 5% random sample, 10% random sample, 100% QA for selected payers/codes, Custom
• How should backlog-processed claims be handled for submission (submit after QA, hold for clinical signoff, or do not submit)? Options: Submit after QA, Hold for clinical validation, Hold until manual review, Do not submit - archive only
• Are there any archival, retention, or audit requirements for processed backlog records?

• Non-Disclosure Agreement (NDA)
• Master Services Agreement (MSA)
• Statement of Work (SOW)
• Pricing & Commercial Terms
• Pilot Agreement / Statement of Objectives
• Service Level Agreement (SLA)
• Data Processing & Security Addendum (DPA / BAA)
• Compliance & Audit Rights
• Integration & Implementation Plan
• Training & Change Management Agreement
• Accuracy Benchmarking & Validation Plan
• Governance & Roles Matrix
• Change Order & Scope Management
• Termination & Transition Plan
• Liability, Indemnification & Insurance

• Success Validation Workshop
• Operational Handoff & Runbook Transfer
• Cadence Setup: Quarterly Governance & Accuracy Review
• Enhancement Prioritization & Continuous Improvement
• Compliance & Audit Readiness Review

• Assign owners and clear acceptance criteria for the top priorities to drive execution in the next cycle.
• Reach a clear decision (Accept / Accept with Remediation / Extend Pilot) and confirm next steps and owners.
• Produce a gap remediation plan (if required) that lists fixes, owners, timelines, expected impact on KPIs, and validation criteria.
• If accepted, prepare and circulate the operational handoff package (runbooks, SLAs, access lists) within 5 business days.
• Identify and tag a set of 100 representative charts (or agreed sample size) for a follow‑up audit and schedule the audit window.
• Handoff Objectives & Sign‑off Criteria
• Ensure the customer's operations team has the runbooks, access, and training necessary to operate the system independently.
• Agree and document SLAs, escalation paths, and RACI for ongoing support and incident response.
• Schedule and confirm a shadowing/overlap window to reduce operational risk during transition.
• Deliver the final runbook package (PDF/Confluence links) and obtain customer sign‑off.
• Provision production access and service accounts to named users and confirm logging and audit settings.
• Schedule the 2‑week shadowing period and assign vendor and customer shadowing owners and daily check‑in times.
• Review Measured KPIs & Improvement Targets
• Produce a prioritized backlog of enhancements tied to measurable outcomes and agreed implementation timelines.
• Agree a controlled model retraining and validation cadence to maintain or improve accuracy without increasing risk.
• Governance Purpose & Cadence
• Publish the prioritized enhancement backlog with RICE (or chosen) scores and assigned owners.
• Schedule the first model retraining window and define the validation test cases and rollback plan.
• Estimate implementation effort for the top three items and commit to delivery windows.
• Audit Trail & Evidence Inventory
• Validate that sufficient audit evidence and traceability exist for external and internal audits.
• Agree retention policies, reporting expectations, and owner responsibilities for audit responses.
• Run a mock audit to confirm evidence pack completeness and identify any gaps to remediate.
• Assemble and deliver a sample evidence pack for an agreed sample of charts and confirm receipt and completeness.
• Document and publish the retention policy and audit response SLAs in the shared compliance folder.
• If gaps are identified, create an audit remediation plan with owners and deadlines.
• Agree a repeatable governance cadence, metrics, thresholds, and sampling methodology for objective accuracy reviews.
• Establish the remediation workflow and escalation steps to ensure timely response to KPI regressions.
• Create and provision the shared communication channel and reporting templates for all future reviews.
• Create the recurring calendar invites and assign owners for pre‑reads and presentations for the next 12 months.
• Configure and share the governance dashboard and the audit sampling plan with the governance group.
• Provision the agreed shared channel and post the governance templates and the SLA thresholds there.
• Introductions & Meeting Objectives
• Validate measured outcomes against each agreed benchmark with evidence sufficient for an acceptance decision.
• Identify and document any gaps, their root causes, and a remediation plan with owners and timelines if acceptance is conditional.
• KPI Definition & Thresholds
• Present Candidate Enhancements & Impact Estimates
• Runbook & Playbook Walkthrough
• One‑Sentence Current State & Consequence Recap
• Compliance Controls & Governance
• Sampling & Audit Methodology
• Prioritization Exercise
• Mock Audit / Sample Review Workflow
• One‑Sentence Future State Reminder
• Roles, RACI & Support Model
• Quantitative Outcome Review (Proof)
• Model Retraining & Validation Cadence
• Monitoring, Dashboards & Alerting
• Remediation & Escalation Workflow
• Retention & Reporting Policies
• Remediation & Escalation for Audit Findings
• Training Completion & Shadowing Plan
• Evidence Walkthrough (Chart‑level Samples)
• Roadmap, Owners & Timelines
• Shared Channel & Reporting Templates
• Schedule Next Reviews & Owners
• Gap Analysis & Root Cause Mapping
• Access, Credentials & Compliance Check
• Decision & Remediation Options
• Next Steps, Owners & Communication