Quick snapshot to get started

• How often does your team run a denial-volume report that leadership reviews? Options: Weekly, Biweekly, Monthly, Quarterly, On demand / irregular
• Tell me about your most recent quarter's denial trend and which figures surprised leadership.
• What percentage of net revenue do you estimate is lost to payer denials today? Options: <1%, 1 to 2%, 2 to 5%, 5 to 10%, >10%
• Who on your team is accountable for proving denial reduction to the CFO? Options: Denial management director, Revenue cycle VP, Billing manager, Controller/finance lead, Other
• Which service lines or departments showed the highest denial rates in your last report? Options: Inpatient, Emergency department, Outpatient surgery, Observation/short stay, Ancillary services (imaging/lab/therapy), Other
• If leadership demanded a measurable reduction within twelve months, what target would they ask you to hit? Options: Reduce write-offs by <$100k/month, Reduce write-offs by $100k–$500k/month, Reduce write-offs by >$500k/month, A percentage reduction (e.g., 25% of denied dollars)

Where denials actually eat your time and dollars

• What single denial driver, when removed, would change your team's day-to-day work most? Options: Prior authorization failures, Coding and modifiers, Coverage and eligibility, Medical necessity denials, Documentation gaps, Other
• Walk me through the three denial reasons that show up most frequently in your billing data and how they are recorded.
• How many denied claims per month does your team reopen or appeal? Options: Fewer than 100, 100–500, 500–1,000, 1,000–5,000, More than 5,000
• When prior authorization requirements increase, which part of your intake or scheduling workflow breaks first? Options: Pre-registration/eligibility checks, Scheduling and authorization routing, Clinical documentation capture, Registration follow-up, Other
• Describe the average elapsed time from denial identification to appeal submission and who performs each step.
• What would have to be true about the root cause analysis for you to commit to a pilot this quarter? Options: Root causes map to specific departments, Root causes are specific within 90 days, Analytics accuracy >70% on historical data, Clear ROI projection within 6 months, Other

Who needs to be at the table to make changes stick

• Which stakeholders outside revenue cycle must be involved to fix root causes, and who has final say? Options: Clinical leadership, Coding/compliance, IT/data governance, Managed care/contracting, Finance/CFO, Other
• Who approves data access across clinical, billing, and payer feeds and how long does approval usually take? Options: IT security (2–4 weeks), Data governance (4–8 weeks), Legal/compliance (2–6 weeks), Multiple groups, timeline varies, No central approver / ad hoc
• Which department typically resists upstream workflow changes aimed at preventing denials, and why? Options: Clinical teams (time burden), Scheduling (throughput concerns), Coding (process change), Front desk/registration (workload), Other
• Tell me about a time when a clinician or service line refused to change documentation that would reduce denials, what happened next?
• If the teams that must change behavior decline to participate, what would you do next? Options: Pull pilot scope back to appeals-only, Escalate to executive sponsor, Delay project until resources are aligned, Stop pursuing external solutions, Other

Clock, money, and competing priorities

• What budget or headcount constraint today would force you to delay any pilot? Options: No budget available, No available technical support FTE, No project manager capacity, Limited budget under $50k, Other
• How many full time equivalents are assigned to denial appeals and prevention versus coding and billing operations? Options: None dedicated, 1–2 FTEs, 3–5 FTEs, 6–10 FTEs, More than 10 FTEs
• Which KPIs does your CFO watch monthly that directly tie to denial performance? Options: Net revenue retention, Denial dollars written off, Days in A/R, Appeal overturn rate, Other
• When a denial-related goal is missed, how does leadership typically react? Options: Reprioritize projects, Request root cause analysis, Increase staff or budget, Set tighter targets, Accept it as seasonal
• If the pilot meets the agreed acceptance criteria, what purchasing process will you use to move to production and who signs the contract?

Is the data a friend or a blocker

• What proportion of your historical denial data is consistently coded and ready to analyze without manual mapping? Options: >80% clean, 50–80% clean, 20–50% clean, <20% clean, Unknown
• Which billing and EHR systems must be integrated for the pilot, and who manages those systems? Options: Primary EHR, Practice management/billing system, Eligibility/clearinghouse, Revenue cycle data warehouse, Other
• Are APIs or scheduled file extracts available for those systems and who controls the credentials? Options: APIs available, IT owns credentials, File extracts available, application owner controls, Limited connectivity, requires custom work, Unknown
• Describe the state of payer remittance and denial reason coding, for example wide use of free text, mapped codes, or mixed approaches.
• What single data gap, if unresolved within six weeks, would stop the pilot from starting? Options: Missing remittance files, Inaccessible EHR encounter data, Unmapped denial reason codes, No access to payer response history, Other

Where projects typically stall and how to avoid it

• What operational or political risk would make you pull the project even if the pilot looks positive? Options: Department nonparticipation, Legal or compliance objection, Unexpected integration cost, Leadership reprioritization, Other
• When automated appeals fail to overturn a denial, what is the usual downstream cost in staff hours or lost revenue? Options: Minimal, Moderate, Significant, Severe but unquantified
• Who in legal or compliance must review automated appeal templates and how long do reviews typically take? Options: Clinical compliance (1–2 weeks), Privacy/legal (2–6 weeks), Coding compliance (1–3 weeks), Multiple reviewers, timeline varies
• Which payer relationships are most sensitive to appeal volume or tone where automated letters might backfire? Options: Medicaid managed care, Large national commercial plans, Smaller regional payers, Government payers Medicare, Multiple payers equally sensitive
• If your compliance team refused to approve automated appeal content, could the pilot proceed with prevention-only scope? Options: Yes, prevention-only is acceptable, No, appeals are required for ROI, Maybe, with limited appeal templates, Unsure

What else are you weighing right now

• What other solutions or internal plans are you actively considering to reduce denials right now? Options: Vendor A (incumbent), Internal in-house build, Staffing increases, Process improvement only, No alternatives
• Which incumbent or internal option would you most likely stay with if it showed comparable results, and why?
• Who proposed solving this problem internally rather than engaging an outside vendor and what was their rationale? Options: IT, Revenue cycle leadership, Finance, Clinical leadership, No internal proposal
• What would have to be true about your current approach for you to keep it instead of switching to an external partner? Options: Consistent results quarter to quarter, Lower total cost than vendor, Less integration work, Fewer compliance questions, Other
• Which of the following evaluation criteria matter most when comparing vendors? Options: Predictive accuracy on historical data, Speed of appeal generation, Integration effort and timeline, Ability to identify root causes by service line, Price and contract terms
• If a competitor promises equal predictive accuracy but requires three times the integration effort, which factor will tip your decision? Options: Total cost of ownership, Time to value, Internal resource availability, Risk tolerance, Other

Measure success the way leadership will fund

• If the pilot delivered a 30% reduction in denied dollars in six months, would that be enough to get executive buy-in? Options: Yes, likely sign-off, Maybe, need more than dollars, No, timeline or other evidence required, Unsure
• Which numerical threshold for denied-dollar reduction would trigger a commitment to production? Options: 10% reduction, 20% reduction, 30% reduction, Specific dollar amount (e.g., $100k/month)
• How soon after pilot completion do you need measurable results to meet your CFO's timeline? Options: Immediately (within 2 weeks), Within 1 month, Within 3 months, Within 6 months
• Who will sign off on pilot acceptance and what evidence do they require (reports, sample appeals, raw data)?
• If the pilot proves the stated metrics but increases appeals workload by 20%, would you still move to production? Options: Yes, if ROI is positive, No, cannot accept workload increase, Maybe, if automation reduces staffing over time, Unsure

Agree next steps that move the clock

• If you decided to proceed, what internal approvals must be in place within 30 days to start the pilot? Options: Data access approval, Budget approval, Executive sponsor commitment, IT schedule slot, All of the above
• Which person on your side will be the day to day owner and what percent of their time can they commit?
• What timeline for data access, mapping, and testing would be acceptable to meet your target go live? Options: 4 weeks, 6–8 weeks, 10–12 weeks, Longer than 12 weeks
• How would you want the seller to share interim pilot results so your stakeholders feel comfortable moving forward? Options: Weekly dashboards, Biweekly executive summaries, Access to raw reports, Live review sessions
• If the seller can prove predictive flags catch 70% of preventable denials on your historical data, what would prevent you from signing within that month? Options: Contract/legal delays, Budget timing, Internal resource constraints, Stakeholder objections, Nothing would prevent signing

• Solution Experience Session — Denial Prevention & Appeals

• Confirm the current state and cost to your team
• Customer confirms the demonstrated predictive flag would have caught the same preventable denials they described in Discovery.
• Run the predictive model against a supplied six-month historical denial sample and deliver a pilot-data readiness report prior to the pilot kick-off.
• Customer confirms the root-cause breakdown isolates the three to five systemic issues driving the majority of their denial volume.
• Map your top denial drivers to existing workflows
• Provide six months of historical denial exports, including payer codes and service-line mappings, and a list of the top 10 payer denial reason codes to include in the pilot dataset.
• Prepare a proposed acceptance criteria sheet mapping KPIs (denial rate reduction, appeal overturn rate, time-to-appeal) to measurable thresholds for pilot sign-off.
• Customer confirms the automated appeal output contains the clinical specificity payers require and meets the quality bar for submission.
• Prove predictive prevention on a representative workflow
• Prove root-cause analytics for the top denial buckets
• Agreement on the pilot acceptance criteria and the specific evidence that will be required for pilot-to-production decision.
• Confirm internal stakeholders and the decision timeline required to approve the pilot and pilot-to-production gates.
• Prove the automated appeal workflow for a real denied claim
• Validate the future state and pilot acceptance criteria

• Solution Experience Session — Denial Prevention & Appeals
• Solution Experience Deck — Denial Prevention & Appeals
• Solution Brief — Denial Prevention & Appeals

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• Load and Normalize Historical Claims Data
• Connect Live Billing System for Real-Time Feeds
• Configure Denial Categorization Rules
• Map Payer-Specific Denial Rules and Logic
• Deploy Predictive Denial Model for Pre-Submit Flags
• Set Thresholds and Alerting for High-Risk Claims
• Run Root Cause Analytics and Trend Heatmaps
• Configure Denial and Write-Off Dashboards
• Generate Automated Appeal Packages with Documentation
• Automate Appeal Workflow and Task Routing
• Integrate Clinical Documentation Retrieval
• Implement Upstream Prevention Workflows and Alerts
• Set Up Continuous Model Retraining and Tuning
• Train Denial Management Team on Platform Workflows

Load and Normalize Historical Claims Data

• Do you have six months of adjudicated claims plus remittance advices (RA/835) available for import to normalize against payer denial codes? Options: Yes, 6+ months ready, Yes, but less than 6 months, No, we require assistance extracting
• Which file formats will you deliver for historical claims ingestion (837/EDI batch, flat CSV export from billing system, extracted database dump)? Options: 837/EDI, CSV/Spreadsheet, Database export (SQL/CSV), Other
• How many unique payer IDs and provider NPI combinations appear in your historical dataset? Options: 1-5, 6-20, 21-50, 51+
• Provide the list of claim-level fields available for mapping (claim ID, patient account, UB-04/837 segment fields, CPT, ICD-10, billed amount, paid amount, CARC/RARC codes, admission/discharge dates).
• Identify the proportion of historical claims that already include discrete denial reason mapping (CARC/RARC or internal denial bucket) versus free-text EOB reasons. Options: >95% discrete codes, 75-95% discrete codes, 50-75% discrete codes, <50% discrete codes
• What acceptance criteria will validate historical data completeness and normalization for the pilot (for example: >95% claim-ID match rate, normalized CPT/ICD mapping coverage >= 98%)?

Connect Live Billing System for Real-Time Feeds

• Do you route live claims through a clearinghouse or submit directly to payers via your billing system's EDI engine? Options: Via clearinghouse, Direct EDI from billing system, Hybrid / depends on payer, Not sure
• Which billing platform and version will provide the real-time submission and adjudication feed (name your billing system or ERP export endpoint)?
• How many claim submissions per day should the live feed support for pilot sampling and alerting? Options: Less than 500, 500-2,000, 2,000-10,000, 10,000+
• Provide the expected maximum latency tolerance between claim submission and when the platform must produce a pre-submit flag (minutes acceptable). Options: Near real-time (under 5 minutes), Fast (5-30 minutes), Same day (under 4 hours), Daily batch acceptable
• List required connection methods for the integration endpoint (SFTP with drop folders, REST API with OAuth2, HL7/CCD feeds, direct database replication). Options: SFTP, REST API (OAuth2), Direct DB/RDS replication, Secure file share, Other
• What acceptance criteria will confirm the live billing feed is functioning for the pilot (for example: 100 sample claims processed with timestamps within SLA and no dropped submission IDs)?

Configure Denial Categorization Rules

• Specify the denial reason code sets you currently use and want the platform to map to (CARC, RARC, internal denial buckets, free-text EOB rules). Options: CARC + RARC, CARC only, Custom internal buckets, Predominantly free-text
• Estimate how many custom denial buckets you want created for the pilot (examples: prior authorization, medical necessity, coding edits, timely filing). Options: 1-3, 4-7, 8-12, 13+
• List example EOB free-text snippets that currently obstruct automated categorization and should be included in rule exceptions.
• Who on your denial team will approve the initial taxonomy and sign off on category-to-process mappings?
• Describe any state Medicaid or commercial payer reporting constraints that require specific denial buckets or codes to be surfaced in reports.
• Are there downstream systems (AR ledger, financial close) that require specific denial category codes to align to an accounting write-off process? Options: Yes, AR ledger mapping required, Yes, finance mapping required, No downstream mapping needed, Unsure

Map Payer-Specific Denial Rules and Logic

• Identify the top payer organizations by denial volume you want payer-specific rules built for during the pilot (provide payer IDs or names).
• Specify payer contract clauses or prior authorization rules that frequently cause denials (for example: service-level prior auth windows, bundling edits, medically necessary criteria).
• Estimate how many payer-specific rules will require bespoke logic rather than generic denial categorization for the pilot. Options: 0-5, 6-15, 16-30, 30+
• Name the internal owner who can provide payer contract excerpts, appeal guidelines, and adjudication examples for each high-volume payer.
• Clarify whether any payers mandate clinical templates or specific attachment types for appeals (for example: operative notes, discharge summary, prior auth forms). Options: Yes, specific clinical templates required, Sometimes, depends on payer, No, free-text allowed, Unknown
• Include any third-party rule repositories, clearinghouse rule lists, or internal rule engines we must align with for payer logic.

Deploy Predictive Denial Model for Pre-Submit Flags

• Rank the claim attributes that should be weighted highest for pre-submit risk scoring (payer, CPT/HCPCS code, diagnosis ICD-10, prior authorization status, patient financial class). Options: Payer, Procedure/Revenue code, Diagnosis, Prior authorization status, Patient financial class, Other
• Estimate the historical training window you want used for the model (number of months of claims and adjudication outcomes). Options: 3 months, 6 months, 12 months, 24 months
• Indicate minimum acceptable performance thresholds for pre-submit flags during pilot evaluation (examples: precision at top decile, recall, AUC).
• Attach systems or feeds available to enrich model features (prior authorization system, EHR orders, registration demographics, lab/imaging metadata).
• Name the role that will approve model thresholds and authorize moving from pilot scoring to production blocking flags.
• Define the acceptance accuracy threshold (for example AUC or precision@top10%) that will confirm the model is ready for live pre-submit flagging during the pilot.

Set Thresholds and Alerting for High-Risk Claims

• Confirm which delivery channels should carry high-risk claim alerts (in-platform task, email digest, EHR inbox, SMS) during the pilot. Options: In-platform task, Email digest, EHR inbox/ADT, SMS/Push notification
• Indicate the initial numeric score threshold above which claims are considered high-risk for triage in the pilot. Options: Top 1%, Top 5%, Top 10%, Custom threshold
• Estimate the number of alerts per analyst per day your denial team can handle without creating a backlog. Options: Less than 10, 10-25, 26-50, 50+
• Name the roles that should receive different alert types (pre-submit review, appeal-ready, upstream prevention notification).
• State any blackout windows or daily schedules when alert delivery must be suppressed (for example nightly batch windows, end-of-day billing cutoffs).
• State SLA expectations for alert acknowledgement and first-action time for high-risk claims. Options: Within 1 hour, Within 4 hours, Same business day, Within 48 hours

Run Root Cause Analytics and Trend Heatmaps

• Select the denial drivers to prioritize in root cause analytics (eligibility, coding, prior authorization, medical necessity, bundling). Options: Eligibility, Coding/Modifiers, Prior authorization, Medical necessity, Bundling / DRG edits, Other
• State which service lines should be included in the initial trend heatmaps (for example: emergency department, radiology, inpatient surgery).
• Confirm the cadence you want for root-cause reports and heatmap refresh during the pilot (weekly, biweekly, monthly). Options: Weekly, Biweekly, Monthly, Ad-hoc on request
• Name sample drill-downs you expect from root-cause analysis (payer-level trends, coder error rates, clinician-order mismatch by location).
• Include external benchmarks to compare against in heatmaps (state Medicaid denial rates, regional averages, national payer benchmarks). Options: State Medicaid benchmarks, Regional averages, National payer benchmarks, No external benchmarks
• Clarify required drill-through links from heatmap tiles into claim-level evidence (link to EOB/RA, clinical notes, prior auth form) for analyst workflows.

Configure Denial and Write-Off Dashboards

• Which KPIs should be present on the denial dashboard for executive view (net denial $ impact, denial rate %, write-off $ by payer)? Options: Net denial $ impact, Denial rate %, Write-off $, Appeal success rate, Days to resolution
• How many role-specific dashboards do you need (executive, denial analyst, clinical leader, revenue integrity)? Options: 1-2, 3-4, 5+
• Provide the required date ranges and filters for dashboard slices (rolling 12 months, YTD, payer, service line, location).
• Name the finance or revenue leaders who must receive scheduled dashboard reports and their cadence (weekly, monthly).
• Detail any GL/accounting write-off mappings that dashboards must export for the finance month-end close (account codes, department allocation).
• Are there regulatory reporting views required (e.g., state Medicaid denials report) that must be derivable from the dashboards? Options: Yes, No, Unsure

Generate Automated Appeal Packages with Documentation

• Which appeal letter templates do you require (clinical narrative, coding justification, prior authorization retrospective submission)? Options: Clinical narrative, Coding justification, Prior auth retrospective, Financial hardship
• How many document types must be auto-attached to appeals for each payer (discharge summary, operative note, imaging report, prior auth form)? Options: 1-2, 3-4, 5+
• Provide examples of payer-specific required attachments or forms that must be included to meet payer submission rules.
• Name the storage location and document access method for clinical attachments (EHR CDT export, document repository, scanned PDF) we will connect to the platform.
• State whether appeal packages should be auto-submitted to payers or routed for analyst review before submission. Options: Auto-submit to payer, Route for analyst review, Mix by payer
• Are there payer portals that require specific file naming conventions or metadata fields when transmitting appeal documentation? Options: Yes, specific naming required, No, generic attachments ok, Depends on payer

Automate Appeal Workflow and Task Routing

• Which internal roles should be included in the appeal workflow and task routing (denial analyst, coding auditor, clinical review, manager approval)? Options: Denial analyst, Coding auditor, Clinical reviewer, Manager approval, Finance reviewer
• How should appeal tasks escalate if unacknowledged (email reminders after set hours, auto-escalation to manager, reassign to backup)? Options: Email reminders, Auto-escalation to manager, Reassign to backup, Notify via EHR inbox
• Provide the SLA for completing an appeal task from assignment to submission during the pilot. Options: Within 4 hours, Same business day, 24-48 hours, Custom SLA
• Name any external systems to update when an appeal status changes (billing system AR notes, EHR problem list, ticketing system).
• Detail conditions for automated appeal closure and accounting actions (successful reversal, payer denial final, aged beyond appeal window).
• Are templates or canned responses required for analyst communications with clinical staff to obtain supporting documentation? Options: Yes, clinical templates required, No, free-text allowed, Some templates only

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• Subscription Agreement
• Order Form
• Master Services Agreement (MSA)
• Data Processing Agreement (DPA) / Business Associate Addendum (BAA)
• Data Access and Authorization Form
• Pilot Acceptance & Success Criteria Agreement
• Pilot-to-Production Decision Gate Addendum
• Service Level Agreement (SLA)
• Change Order Agreement

• Go-live Health Check (weeks 1-4)
• First Measurement Review (weeks 4-10)
• 90-Day Realization Review
• Quarterly Operational Review (ongoing)

• Run a data completeness check for the billing sources and report any discrepancies before the next quarterly review.
• Publish a short user onboarding checklist and identify any missing permission assignments within 48 hours.
• Re-confirm success criteria and ownership
• Review outcomes against Pilot Analysis targets
• Confirm the direction of the three named metrics relative to the Pilot Analysis targets and document remaining gaps.
• Ensure the legacy denial tracking approach is formally retired or retained read-only and archived.
• Establish a prioritized remediation and enhancement backlog with target completion windows.
• Provide a documented archive or migration confirmation for the legacy denial tracking files and systems.
• Publish the prioritized enhancement backlog with estimated effort and expected metric impact.
• Deliver the next 30- to 60-day data slice showing metric movement after agreed remediation actions.
• Quarterly KPI trend review
• Keep denial write-off rate and appeal overturn rate on a documented improvement trajectory toward the Pilot Analysis targets.
• Clear or downgrade at least one persistent blocker each quarter or reassign it to the enhancement backlog with a plan.
• Maintain data quality standards so analytics continue to reflect true operational performance.
• Publish quarterly KPI trend slides and data extracts for the prior quarter within five business days of the meeting.
• Update the enhancement backlog with agreed priorities and target implementation quarters.
• Provide a list of any failed integration attempts and corresponding error logs for the past seven days.
• Confirm end-to-end data flow and connector health for all required billing sources.
• Validate that the core user groups can access the platform and run the primary workflows.
• Document high-priority blockers with agreed resolution dates.
• Schedule targeted training sessions for roles showing low adoption within the first two weeks post go-live.
• Present first outcome data against Pilot Analysis targets
• Determine whether denial write-off rate and appeal overturn rate are moving toward the targets recorded in the Pilot Analysis stage.
• Identify the top 2 payer or process drivers responsible for current shortfalls and document corrective actions.
• Agree a clear remediation timeline and the next data cut date for evidence of improvement.
• Deliver a payer-level root-cause drilldown for the measured period with recommended corrective actions and expected impact.
• Provide the next data extract covering the subsequent 30 days for re-evaluation against Pilot Analysis targets.
• Document the appeal automation exception cases encountered and propose template or content changes to improve overturn rates.
• Root-cause diagnosis by payer and service line
• Deployment and integration validation
• Persistent root-cause and cross-functional blockers
• Prioritize open issues and remediation plan
• Incumbent wind-down and data archiving confirmation
• Early adoption signals and usage patterns
• Enhancement backlog grooming and prioritization
• Appeal automation performance and throughput
• Data quality and monitoring checks
• Enhancement prioritization for sustained revenue recovery
• Open issues and blocker triage
• Agree corrective actions and timeline to the acceptance checkpoint
• Agree immediate remediation actions
• Short sync for low-change quarters