The Moment That Made You Look Up

• Briefly describe the reconciliation result that prompted this conversation (what changed, and when did you notice it?)
• Which contract type and population did the shortfall appear in? Options: Medicare Advantage, Commercial ACO/Delegated, Medicaid MCO, Medicare Shared Savings (ACO), Other
• How large was the variance vs. projection (choose the range that best fits)? Options: <$500k, $500k–$1M, $1M–$3M, $3M–$10M, >$10M, Unsure / don’t know yet
• Who first raised the alarm internally about the reconciliation gap? Options: Chief Medical Officer, VP Population Health, Director Care Management, Finance / Reconciliation Team, Contracting, Other
• How urgent is fixing this before the next reconciliation cycle? Options: Immediate — within 30 days, Near term — 1–3 months, This quarter, Next 6–12 months, No immediate timeline

Are We Underestimating Who Decides?

• Who outside your immediate team can veto a pilot or force a different solution if they don’t see the right evidence? Options: CFO/Finance, General Counsel/Legal, Chief Medical Officer, Chief Nursing Officer, Board/Exec Committee, Payer counterparties, Other
• Across clinical, care management, IT, and finance — who is the single named owner for decisions in each domain? Please list names and roles.
• Which stakeholder’s buy-in is most fragile and why? Options: Clinical leadership skeptical of algorithms, Care management fear of extra work, IT capacity constraints, Finance demands strict ROI, Legal/privacy concerns, Other
• Who will be the ultimate signatory for a pilot that requires data sharing and a proof-of-value clause? Options: CFO, CMO, VP Population Health, General Counsel, Contracting Officer, Other
• If we show projected savings, what is the decision timeline to move from pilot to scale? Options: 30 days after pilot, 60–90 days, Single executive review within 6 months, Board-level approval required, Undetermined

Where Are Your Blind Spots Hidden?

• Which data sources would embarrass you if they were missing or low quality when we run a 12‑month backtest? Options: All-payer claims, EHR encounter data, Pharmacy claims, Labs, Enrollment/eligibility, Social determinants (SDOH), Other
• Describe the most common failure modes you saw in last year’s reconciliation that let rising‑risk members become high‑cost (specific examples please).
• What attribution rules do you currently use to decide which members are 'ours' for value-based calculations? Options: Monthly assignment, Prospective attribution, Retrospective claims-based attribution, Panel-based attribution, Custom hybrid rules, Unsure / need to check
• How often do you receive complete claims for the prior month (select the closest match)? Options: Within 30 days: >90%, Within 60 days: >90%, Within 90 days: >90%, Significant lag >90 days, Varies by payer
• Do you have a recent reconciliation report or sample case we could review in a pilot? If yes, when can you share it? Options: Yes — ready now, Yes — within 2 weeks, Yes — within a month, No — would need time to assemble, No — not available

Who Owns the Problem, Day-to-Day?

• If rising‑risk members are consistently missed today, whose daily job would change the most to stop that from happening? Options: Care managers, Population health analysts, Primary care clinicians, Health plan case reviewers, Data engineering / ETL team, Other
• How do care managers currently receive and action patient lists (select all that apply)? Options: EHR task inbox, Standalone care management platform, Spreadsheets / CSV exports, Paper lists, Email, Other
• Do care managers perform duplicate data entry today? If yes, describe the most painful example. Options: Yes — often, Sometimes, Rarely, No — workflows integrated
• What is the average caseload per care manager and typical outreach cadence for rising‑risk patients?
• Tell us about a recent workflow change you implemented—what worked, what didn’t, and why?

What Would Real, Measurable Success Feel Like?

• Which single outcome would convince your board the platform is worth scaling: admissions avoided, ED visits reduced, net medical spend lowered, or improved reconciliation accuracy? Options: Avoidable admissions reduced, ED visits reduced, Net medical spend reduced, Reconciliation accuracy improved, Combination — please specify
• What target reduction in avoidable admissions or ED visits would you need to see during a pilot to call it successful (choose a range)? Options: <5%, 5–10%, 10–20%, >20%, Unsure / need guidance
• Which financial acceptance criteria would you require for pilot success (select all that apply)? Options: Net savings >$X (specify), ROI within 12 months, Payback within pilot, Achieve reconciliation delta reduction, Other
• Beyond hard metrics, what qualitative signals would make you confident (examples: care manager satisfaction, clinician trust, smoother workflows)?
• What is the minimum pilot population size (members or attributed lives) you consider statistically meaningful? Options: <1,000, 1,000–5,000, 5,000–20,000, >20,000, Unsure

What Would Make Your Team Trust an Algorithm?

• What single feature or validation would most change a clinician’s mind about acting on an automated risk alert? Options: Patient-level exemplars with timeline, Transparent feature importance, Peer-reviewed validation, Low false positive rate, Easy integration into workflow
• How comfortable are you with model recalibration using your 12 months of claims and clinical examples? Options: Very comfortable, Somewhat comfortable, Prefer vendor-only models, Require full governance oversight, Unsure
• Which model characteristics matter most for you (select up to three)? Options: High sensitivity for rising‑risk, High specificity to avoid alert fatigue, Explainability at patient-level, Use of SDOH features, Temporal stability over 12 months, Regulatory transparency
• What false positive rate is acceptable before care managers reject the alerts (give a percent or descriptive threshold)?
• Would clinicians require patient-level narratives/examples from past cohorts before trusting outreach recommendations? Options: Yes — essential, Helpful but not required, No — only metrics matter, Unsure

If We Tried a Pilot Tomorrow, What Would Break?

• What single legal, technical, or operational hurdle would stop deployment this quarter if it couldn’t be resolved quickly? Options: Data-sharing agreement, PHI/Privacy concerns, ETL bandwidth, EHR integration delay, Executive approval, Other
• Which legal or data modules must be in place before data can be shared (select all that apply)? Options: BAA / DPA, Data use agreement (DUA), Business associate addendum, Breach notification terms, Patient consent requirements, Other
• Do you have named technical owners for ETL, API endpoints, and EHR integration? Please provide names and expected availability.
• How quickly can you deliver a one-month sample of 12 months of claims and clinical data for backtesting? Options: <1 week, 1–2 weeks, 2–4 weeks, >1 month, Not available currently
• If initial sample data shows quality issues, what fallback would you prefer: pause, do a partial pilot, or proceed with caution and additional validation? Options: Pause and fix, Partial pilot on clean subset, Proceed with added validation, Other — please describe

How Do We Keep This From Fizzling?

• When early wins are modest or mixed, who in your organization is most likely to fight for continued funding and scale? Options: VP Population Health, CMO, Director Care Management, CFO, Operational sponsor in clinics, Other
• What governance cadence would you want for a pilot (review frequency and attendees)? Options: Weekly tactical, Bi-weekly, Monthly executive, Quarterly review, Other — specify
• If the pilot meets clinical thresholds but misses financial targets by 10%, how should we proceed? Options: Extend pilot, Adjust ROI assumptions and continue, Pause and optimize workflows, Stop — not viable
• What contract or commercial term would be a deal-breaker for you (examples: long lock-in, lack of data portability, excessive up-front costs)?
• What immediate next step would you need from us to make progress in the next 14 days (examples: sample data intake form, technical kickoff, legal template)? Options: Technical kickoff call, Sample data intake template, Draft DUA/BAA, Executive briefing deck, Pilot scope and SOW

Quick Snapshot: Who You Are and What You're Protecting

• In one sentence, how would you describe your organization and the attributed population we should focus on for this review?
• Which stakeholder group do you represent in this conversation? Options: Chief Medical Officer / Medical Leadership, VP/Director of Population Health, Director of Care Management, Value-Based Contracts / Finance, IT / Data Engineering, Other
• Approximately how many attributed members are in scope for your value-based contracts today? Options: <10k, 10k–50k, 50k–200k, 200k–1M, >1M, Prefer not to say
• How many months of clean, accessible claims + clinical data could you reasonably share for an initial test? Options: 3 months, 6 months, 9 months, 12 months, >12 months, Not yet available
• What's the single most important outcome you need this engagement to demonstrate in the pilot? Options: Avoidable admissions reduction, ED visit reduction, Reconciliation delta improvement, Improved care manager productivity, ROI in dollars, Other

Are You Comfortable Missing the Members Who Will Make or Break Your Reconciliation?

• When your last full reconciliation landed below projection, what surprised you most about the missed savings?
• How large was the reconciliation shortfall that triggered this review (ballpark)? Options: <$500k, $500k–$2M, $2M–$5M, >$5M, Prefer not to say
• Who inside the organization felt the greatest pressure once that shortfall became visible? Options: CMO, VP Population Health, CFO/Finance, Care Management Director, CEO/COO, Other
• How has that reconciliation result shifted your priorities or sense of urgency for finding rising‑risk members? Options: Immediate top priority, High priority within 3 months, Important but not urgent, Monitoring only, Unsure
• Tell us about one specific instance where a rising‑risk patient was missed and later became high-cost—what happened and why does it still matter?

Where Does Your Data Live — and Where Does It Fall Apart?

• If I told you one fragmented data feed is driving most missed rising‑risk flags, which feed would you point to first? Options: Primary payer claims, All-payer claims, EHR clinical notes, Pharmacy fills, Lab results, SDoH / community data, Other
• List the primary sources of member data you currently ingest or rely on (claim types, EHRs, pharmacy, labs, SDoH).
• How are claims currently delivered to your analytics team (choose all that apply)? Options: Flat files via SFTP, Direct API to payers, Clearinghouse feed, EHR import, Manual uploads, We don't have a regular feed
• How frequently are feeds refreshed for operational use (e.g., care manager workflows)? Options: Daily, Weekly, Biweekly, Monthly, Quarterly, Ad hoc/manual
• Describe one recurring data quality issue you've seen (timeliness, missing CPT/ICD codes, duplicate members, delayed adjudication) and its downstream impact.
• Have you run a reconciliation or retrospective analysis that maps missed rising‑risk members to specific data failures in the last 12 months? Options: Yes — detailed analysis available, Yes — high level summary only, No, but we have examples, No analysis done

Which Attribution Rules Are Quietly Costing You Money?

• If your current attribution rules were a gatekeeper, where are they letting the wrong members in—or letting the right ones slip out?
• Which attribution model do you use today for your value contracts? Options: Prospective attribution, Retrospective attribution, Panel-based attribution, Visit-based attribution, Hybrid / custom
• How often do attribution disagreements occur between payer and provider partners? Options: Very frequently, Often, Occasionally, Rarely, Never
• Give an example where attribution rules directly caused a rising‑risk member to be outside the scope of outreach—what would have needed to change?
• Who in your organization is the ultimate owner of attribution rules and reconciliation logic? Options: Value-based contracts team, Finance, Population Health, Care Management, IT/Data, Shared governance

How Do Care Managers Actually Work — Not How You Hope They Do

• If I shadowed a care manager for a day, what three tools or screens would they use most?
• Where do care manager tasks and outreach activities originate today? Options: EHR task inbox, Standalone case management tool, Excel/Google Sheets, Email/Calendar, Third-party platform, Other
• How much of a care manager's time is spent on navigation/administrative work versus direct member outreach (best estimate)? Options: >70% admin, 50–70% admin, 30–50% admin, <30% admin
• Describe a typical handoff between referral sources (e.g., utilization team) and care management—where does it break down?
• What would feel unacceptable to your care managers in terms of workflow change (e.g., extra clicks, duplicate documentation, new inboxes)?
• Are there existing care‑manager scripts, risk-stratification thresholds, or outreach templates you expect any new platform to honor or replicate? Options: Yes — we will share templates, Yes — but informal, No — open to new approach, Unsure

When Risk Models Miss the Moment, What Fails Downstream?

• Tell us about a time a model underestimated risk and an avoidable admission occurred—what were the warning signs you wish you'd seen?
• Which of these common failure modes have you observed in your risk stratification? Options: Delayed claims ingestion, Incomplete clinical data (labs/notes), Model not calibrated to local population, Lack of SDoH signals, Over-reliance on threshold flags, None of the above
• How frequently do you recalibrate or validate risk models against known high-cost cohorts? Options: Quarterly, Biannually, Annually, Rarely, Never
• Do you have labeled cohorts (e.g., known rising‑risk that became high-cost) we can use for back-testing? If so, how many examples? Options: Yes — >500 members, Yes — 100–500 members, Yes — <100 members, No labeled cohorts available
• What is the worst-case human impact you worry about when rising-risk members are missed? Options: Preventable hospitalization, ED overuse, Clinical deterioration, Regulatory/quality penalties, Financial loss, Other

If We Could Prove We Found the Missing Members, What Would Change?

• If a test showed we could identify X% of previously missed rising‑risk members, how would that change leadership's appetite for a pilot? Options: Immediate pilot approval, Consider with more evidence, Need finance sign-off, Unlikely to change much
• Which outcome measures would convince you this approach is working (choose up to three)? Options: Avoidable admissions reduction, ED visit reduction, Net reconciliation improvement ($), Care manager outreach completion rate, Time-to-intervention, Member engagement rate
• What minimum improvement in reconciliation delta (in dollars or percentage) would you need to justify scaling? Options: <$250k, $250k–$1M, $1M–$3M, >$3M, Prefer to discuss qualitatively
• If the pilot proves successful, what would be the key elements of your scale decision (e.g., ROI threshold, clinical champion, integration completion)?
• What concerns would you have about operationalizing a system that re-prioritizes members for outreach based on algorithmic risk? Options: Clinical trust / skepticism, Care manager workload, Member consent/privacy, Integration complexity, Attribution disputes, Other

Data & Integration Practicalities — Let’s Test the Hidden Assumptions

• Which EHR(s) and care management systems must we integrate with for a successful pilot?
• Do you have API endpoints or technical contacts ready for integration testing? Options: Yes — APIs & contacts ready, Partial — some endpoints ready, No — will require setup, Unsure
• Which legal or data-sharing constraints could slow sample data delivery (select all that apply)? Options: BAA/PHI concerns, State privacy regs, Contractual payer limits, Internal security review, None
• What cadence of data refresh would you need in production for care managers to act reliably? Options: Near-real-time, Daily, Weekly, Biweekly, Monthly
• Who is your named owner for data engineering or integration work (name & role)?
• Are there specific PHI or data governance checks we should run on sample data before any analysis?

Quick Validation: Can You Show Us the Receipts?

• Can you provide 12 months of claims plus clinical encounters for a retrospective validation? Options: Yes — ready now, Yes — available within 2 weeks, Yes — available within 1–2 months, No — need additional approvals
• What file formats do you prefer or have available for sample extracts? Options: CSV/flat files, EDI/ANSI 837/835, FHIR resources, HL7, Other
• Which retrospective cohort would be highest value for back-testing (e.g., members with unplanned admission within 12 months)? Options: All-cause high-cost, Rising-cost then admitted, Chronic condition cohorts (e.g., diabetes), Behavioral health-related admissions, Other
• Do you have prior 'loss analyses' or reconciliation reports we can compare our test results against? Options: Yes — detailed reports, Yes — summary only, No
• Who would sign off on us using de-identified or limited PHI samples for this validation?

Decision Dynamics — Who Moves the Needle?

• If we deliver evidence that we find the previously missed rising‑risk members, who needs to be convinced to move to pilot and full scale? Options: CMO / Clinical Leads, VP Population Health, CFO / Finance, Care Management Director, IT/Data Leadership, Board / Executive Committee
• What is your typical procurement cadence for pilot-level engagements? Options: Immediate contracting (weeks), 1–2 months, 2–3 months, 3–6 months, Longer / complex
• Where does budget for pilots usually come from in your organization? Options: Population Health budget, Care Management operational budget, Innovation / transformation fund, Finance / Risk reserves, Other
• Who in your team would be the day-to-day sponsor for a pilot (name & role)?
• What are the top three blockers that would stop this pilot from starting on your ideal timeline?

Quick Check — Who's in the Room?

• Who are the primary people we should invite to confirm pre-deployment readiness? Options: Chief Medical Officer, VP Population Health, Director of Care Management, IT/Integration Lead, Data Engineering/BI Lead, Privacy/Security Officer, Finance/Contracts Lead, Other (please name)
• If we need a single day for a kickoff working session, who is the one person who must attend?
• What's your target window for starting technical builds (calendar date or month)? Options: Within 2 weeks, 2–4 weeks, 1–2 months, 2–3 months, TBD
• How urgent is resolving rising-risk identification for your organization on a scale from calm to critical? Options: Critical — reconciliation risk this year, High priority — prevention focus, Medium — planning ahead, Low — exploratory
• Have you run any previous integrations or pilots with external analytics platforms? If yes, briefly describe what went well and what blocked progress.

If This Goes Wrong, What Keeps You Up at Night?

• How confident are you that missed rising-risk members are the primary driver of the recent reconciliation gap? Options: Very confident, Somewhat confident, Not sure, Uncertain — needs analysis
• What is the single worst operational outcome you fear during deployment (e.g., incorrect outreach, data breach, clinician pushback, missed SLAs)? Options: Incorrect patient outreach, Data quality causing wrong stratification, Security/privacy incident, Care manager workflow duplication, Escalation with payers/providers, Other (please specify)
• Tell us about a past integration or pilot that went poorly—what happened and why (people, data, governance, or tech)?
• How much tolerance does your leadership have for initial false positives/negatives in risk stratification during a calibration period? Options: Very low — must be tight from day one, Moderate — expect an iterative period, High — willing to iterate aggressively
• What political or contractual constraints (payer/provider attribution, commercial terms) could derail a pilot if not addressed up front?

Show Me Your Data — Where Does the Truth Live?

• Which of these data sources can you provide access to for a 12-month historical extract (select all that apply)? Options: Medical claims (all payers), Pharmacy claims, EHR clinical data (encounters, vitals, problems), Labs, Social determinants / SDOH, Care management task logs, Enrollment/attribution lists, Other (please specify)
• For each selected source, what is the current method of access you can support? Options: SFTP file drops, Secure API (FHIR/REST), Vendor intermediary connector, Direct DB access (read-only), Manual exports only, Unknown
• Please provide the typical delivery cadence and latency for those feeds (e.g., daily, weekly, 30–90 day claims lag). Options: Near real-time (minutes/hours), Daily, Weekly, Monthly, Quarterly, Ad-hoc/manual
• Do you have a named data steward or owner for each feed? If yes, list role/name and contact for the top 3 feeds.
• What sample size (member count or time range) can you deliver first for our validation tests? Options: Full 12 months for all attributed members, 12 months for a representative pilot cohort, 3–6 months sample, Small proof sample (weeks), Not yet identified

How Accurate Is 'Accurate' for Your Team?

• What level of completeness do you expect for critical fields (diagnosis codes, dates of service, patient identifiers) during initial validation? Options: >98% complete, 95–98% complete, 90–95% complete, Accept lower and iterate
• What are the most common data quality issues you've experienced (pick up to three)? Options: Missing member identifiers, Incorrect dates of service, Claim/diagnosis coding inconsistencies, Duplicate records, Missed SDOH or social history, Other (please specify)
• Do you track formal data quality metrics today (e.g., field-level completeness, duplication rates)? If so, which metrics and typical values? Options: Yes — we have a DQ dashboard, Some metrics reported ad-hoc, No formal metrics today, Other (please describe)
• Share an example story where poor data quality directly impacted patient outreach or financial reconciliation.
• What remediation cadence would you accept during calibration (e.g., daily fixes, weekly patches, monthly backlog)? Options: Daily, Weekly, Bi-weekly, Monthly, Only major issues

Can Your EHR & Workflows Talk to Ours?

• Which EHR(s) and versions are used by the care teams who will receive tasks from the platform? Options: Epic (versions), Cerner/Oracle, Allscripts, Athenahealth, Other (please specify), Multiple vendors across sites
• Do your care managers use a single EHR-integrated workflow today, or do they operate across multiple tools? Options: Single integrated workflow, Multiple tools with manual handoffs, Primarily spreadsheets and email, A mix — explain
• Which technical integration patterns can you support for task and workflow handoffs? Options: FHIR Task/Notifications, HL7 v2 messages, Direct API for task creation, SFTP/CSV inbox for tasks, EHR vendor marketplace app, Other (specify)
• Who owns EHR change control and how long does a typical minor workflow configuration take to approve and deploy? Options: Application owner — <2 weeks, Application owner — 2–6 weeks, Governance board — 6–12 weeks, Lengthy vendor dependency (>12 weeks), TBD
• Describe any SSO, role-mapping, or patient-matching constraints we should plan for during integration.

Who's Driving This Boat — Roles, Decisions, and Escalation

• Who is the executive sponsor for this pilot and what measurable outcome will they use to judge success?
• Which person or committee has final sign-off authority for go/no-go on pilot deployment? Options: CMO/Medical Leadership, VP Population Health, IT Leadership, Joint payer-provider governance, Other (please specify)
• List the named owners (role + name) for: data delivery, integration/ETL, care management operations, and security/compliance.
• How do you prefer to handle escalation when a blocking issue arises during build (daily standup, weekly steering, ad-hoc war room)? Options: Daily standup, Twice-weekly sync, Weekly steering committee, Ad-hoc war room, Email escalation only
• Are there existing KPIs or dashboards the team will use to monitor pilot performance, or should we propose baseline metrics? Options: Existing KPIs in use, We need suggested baseline metrics, A mix of both

What Would Count as 'Safe' to Launch?

• What hard stop conditions would cause you to pause deployment (e.g., >X% misclassification, PHI exposure, EHR task failure)?
• Which security and privacy controls must be demonstrably in place before we begin build (check all that apply)? Options: Business Associate Agreement (BAA), Encrypted data transfer (TLS/SFTP), Role-based access control, Audit logging and SIEM integration, Data de-identification/pseudonymization, Penetration testing/attestation
• What validation threshold for risk-stratification accuracy would you require during the validation checklist to accept the pilot (e.g., PPV, sensitivity targets)? Options: High PPV focus (>80%), Balanced sensitivity/specificity (~70%), High sensitivity to avoid misses, We need to discuss targets
• Do you require a rollback or canary plan that lets us limit outreach volume while monitoring outcomes? If yes, describe preferred limits. Options: Yes — canary by % of cohort, Yes — canary by geography/site, No — full pilot only, Unsure — need recommendations
• Who signs off that controls and testing are sufficient for launch (role/name)?

If Nothing Changes in 30 Days, What Will Break?

• What are the critical milestones you expect in the first 30 days (data handoff, samples validated, API access, model calibration)? Options: Data handoff, Sample validation complete, EHR integration endpoint available, Model calibration started, Care manager training scheduled, Legal/data agreements signed
• Please provide target dates for the top three deliverables you want completed in the next 30 days.
• Who will be available for daily technical check-ins during the initial build window? Options: Integration lead/engineer, Data steward, Care management lead, Project manager, Security/compliance contact, Not available daily
• What resources can you commit from your side for testing and validation (FTEs, environment access, test patients)? Options: 1–2 FTEs part-time, 2–4 FTEs part-time, 1 FTE full-time, Dedicated IT engineer, Limited ad-hoc support
• How will success be signed off at 30 days — who provides acceptance and what artifacts do you need (test report, sample outputs, UAT session)? Options: Formal UAT sign-off, Demo and verbal approval, Written acceptance with metrics, Steering committee review

Confirmations, Attachments, and the Things We Can't Build Without

• Please confirm which of the following you can provide within 5 business days (select all that apply). Options: Sample 12-month claims extract (de-identified), EHR API endpoint documentation / sandbox creds, List of attributed members, Signed data sharing/BAA template, Data dictionary for major feeds, Named owners and contact info
• If any of the items above are not available within 5 business days, specify which and why.
• Please upload or link to any existing reconciliation reports, recent care management performance reports, or prior risk-model validation documents (or describe where they live).
• Are there legal, procurement, or privacy approvals pending that will block access to data or EHR endpoints? If so, what is the expected clearance timeline? Options: No blockers, Minor approvals pending (<2 weeks), Major approvals pending (2–8 weeks), Significant legal negotiation (>8 weeks)
• Is there anything else — political, operational, or technical — we should know now that will change the plan?

Start: The Moment That Made You Look Up

• In one short paragraph, what specific result or event prompted you to explore solutions for finding missed rising‑risk members?
• Approximately how large was the reconciliation gap that triggered this review? Options: <$500k, $500k–$1M, $1M–$3M, $3M–$10M, >$10M, Don't know / need to check
• Who first raised concern inside your organization (role or team)? Options: CMO/Chief Medical Officer, VP Population Health, Director Care Management, CFO/Finance, Risk/Contracting, Other
• How urgent does this feel on a scale from tactical problem to existential threat for next year’s financials? Options: Immediate existential threat, High priority but manageable, Medium priority, Low priority / exploratory
• If you had to name one feeling tied to this moment (e.g., frustrated, anxious, determined), what would it be and why?

When Savings Turned Into Alarm Bells

• What would it mean to your organization if next year’s reconciliation moved you from shared savings into shared losses?
• How have past reconciliation shortfalls influenced leadership conversations about risk‑bearing strategy? Options: Sharpened scrutiny and action, Raised concerns but no change, Triggered structural reviews, Not discussed in leadership
• Which financial/contracting metrics are you most focused on improving as a result (select up to three)? Options: Shared savings capture, Avoidable admissions, ED utilization, Total cost of care per member, Gap closure on quality measures, Other
• How would missing another year of projected savings affect staffing, budgets, or strategic plans?
• Who in your executive chain will be most directly accountable for reversing this trend? Options: CMO/Chief Medical Officer, VP Population Health, CFO, Chief Operating Officer, Board/Committee, Other

Who’s Holding the Reins—and Who’s Getting Left Out?

• To what extent are clinical, care management, IT, and finance aligned on who owns rising‑risk identification and outreach? Options: Fully aligned with clear owners, Mostly aligned with some gaps, Fragmented with unclear ownership, Silos and competing owners
• Which roles would you expect to be named owners for: decision authority, data ownership, pilot governance, and day‑to‑day care management? Please list names or titles.
• What timeline do decision‑makers expect for a pilot decision (months until go/no‑go) and for scale if successful? Options: <3 months, 3–6 months, 6–9 months, 9–12 months, >12 months
• Where have past cross‑functional efforts stalled—policy, risk attribution, data access, or frontline adoption? Options: Policy/governance, Attribution disagreements, Data access/quality, Care manager workload/adoption, Legal/contracts, Other
• How comfortable are your care managers with algorithmic prioritization versus clinician judgment? Options: Very comfortable and curious, Cautiously optimistic, Skeptical but open, Resistant

Where Your Data Might Be Hiding the People You Need

• Tell us about the most important data sources you rely on today to identify rising‑risk members (claims, EHR, pharmacy, labs, social determinants). Which are you confident in, and which worry you?
• What are the typical delays or gaps in the data feeds you use (claims lag, missing payers, incomplete SDoH, etc.)? Options: Claims lag (>30 days), Missing non‑attributed payers, Incomplete SDoH, Sparse lab/pharmacy feeds, Inconsistent encounter data, Other
• Which of the following best describes your current data integration posture for a 12‑month test: single payer claims only, multiple payers consolidated, EHR + claims linked, or other? Options: Single payer claims only, Multiple payers consolidated, EHR + claims linked, Claims + SDoH but not EHR, We don't have a consolidated view
• How frequently do you run reconciliation or retrospective reviews today (quarterly, annually, ad hoc)? Options: Monthly, Quarterly, Annually, Ad hoc / event‑driven, Never
• If we asked for a sample of 12 months of claims + clinical records to test model accuracy, what logistical or compliance hurdles would most likely slow you down? Options: Legal/data agreements, PHI handling concerns, IT availability, Data cleanup required, Other

The Missed Members — Stories That Hurt (and Teach)

• Think of a high‑cost member from last year you wish you'd reached sooner—what was their story and what warning signs were visible earlier?
• How often do your retrospective reviews reveal the same failure modes (e.g., attribution mismatch, mis‑timed risk scores, care manager capacity)? Options: Almost always, Often, Sometimes, Rarely
• Which failure modes have driven the largest missed opportunity in dollars or outcomes? Options: Attribution model gaps, Data latency / claims lag, Risk model thresholds too high, Care manager workflow gaps, Referral or access barriers, Other
• Have you documented specific cases where EHR‑native tools missed rising risk that cross‑payer claims would have revealed? If so, describe briefly.
• How much variability is there across provider groups in identifying and escalating rising‑risk members (consistent, moderate, high)? Options: Consistent, Moderate variability, High variability, Unknown

Workflows That Will Move the Needle—or Get Ignored

• If a new platform added prioritized tasks to your care managers, what would need to change in their day for it to be adopted instead of ignored?
• Which care management tools do your teams use today and where do they prefer workflows to live? Options: Vendor care management platform, EHR native care mgmt module, Spreadsheets / task lists, Other
• How important is embedded, one‑click task creation (with contact info, outreach script, and history) versus a report that requires manual action? Options: Critical, Very important, Nice to have, Not important
• What staffing or training constraints would limit how quickly care managers could take on new outreach from a pilot? Options: Headcount limits, Training time, Workflow change fatigue, Competing priorities, None major
• Describe a recent workflow change that succeeded—what made adoption stick (leadership support, incentives, simplicity, etc.)?

If We Could Guarantee One Outcome—Which One Would You Choose?

• If a pilot could demonstrably prevent a quantifiable number of avoidable admissions or ED visits in 12 months, how would you value that success?
• Which KPIs would you require to declare the pilot a success (select up to three)? Options: Avoidable admissions prevented, Avoidable ED visits reduced, Reconciliation uplift ($), Risk stratification precision/recall, Care manager outreach completion rate, Other
• What minimum magnitude of improvement on your top KPI would justify scale in your view (percentage or absolute number)?
• Which timeframe feels realistic to measure meaningful impact from a pilot (3, 6, 9, 12 months)? Options: 3 months, 6 months, 9 months, 12 months, Longer than 12 months
• What non‑financial signals (clinician trust, care manager satisfaction, member experience) would you want tracked alongside dollars? Options: Clinician acceptance, Care manager workload impact, Member outreach satisfaction, Referral completion, Quality measure improvements, Other

What Would Make a Pilot Unignorable (and Governance You Can Live With)

• If we asked you to sign onto a pilot today, what commercial or legal terms would be absolute deal‑stoppers versus negotiable?
• How do you prefer data sharing and PHI governance to be structured for a test: joint environment, secure vendor environment, or federation of queries? Options: Joint shared environment, Secure vendor environment, Federated query model, Other / hybrid
• Who must sign off on attribution rules and success criteria before a pilot can begin? Options: Finance/CFO, CMO/Clinical leadership, Legal/compliance, Contracting/risk, Care Management Director, Other
• What cadence and format for governance reviews would make you confident in moving from pilot to scale (weekly operational, monthly leadership, quarterly steering)? Options: Weekly operational, Biweekly operational, Monthly leadership, Quarterly steering, Ad hoc as needed
• What is the minimum executive commitment or resource allocation you would need to greenlight a meaningful pilot? Options: Named executive sponsor, Dedicated care manager FTE(s), IT integration support, Budget for data work, All of the above