Starting with Who’s In the Room

• Who will be the primary users, approvers, and sponsors for this program? (List roles/titles) Options: CIO/IT Director, Public Health Informatics Director, Epidemiologist, Laboratory Director, Immunization Program Lead, Procurement Officer, Other
• What is the single most important outcome you want this project to deliver in the next 12 months? Options: Meet CDC reporting requirements, Reduce lab-reporting lag, Consolidate registries, Improve outbreak response speed, Reduce manual reconciliation, Other
• How urgent is this initiative on a scale from needed for compliance to optional improvement? Options: Immediate (compliance deadline ≤6 months), Near-term (6–12 months), Planned (12–24 months), Exploratory/longer-term
• Who owns the budget or funding line that would pay for this work? Options: State health operating budget, Federal grant (DMI/CDC), State capital funds, Local/municipal budget, Hybrid/multiple sources, Unknown
• What recent audit, mandate, or event prompted this initiative?

Are We Sure We Know Who Decides?

• If this project succeeds, who in your organization will be publicly recognized — and if it fails, who will be held accountable?
• Who has final authority to sign contracts and approve budgets for IT projects of this size? Options: CIO/State IT Board, Commissioner of Health, Procurement Office, Grants Office, Legislative approval required, Other
• Which committees or governance bodies will need to review or approve requirements, and how often do they meet? Options: IT Governance Board, Public Health Advisory Committee, Procurement Review Board, Interagency Working Group, None/Ad-hoc
• Who are the technical data stewards (lab systems, immunization, vital records) and how do they prefer to be engaged? Options: Lab IT, Immunization Registry Lead, Vital Records Office, EHR Integration Team, External Lab Partners, Other
• How stable are these stakeholders’ priorities — have decision owners changed recently or are they likely to change in the next year? Options: Very stable, Some turnover expected, Significant change likely, Unsure

Where the Data Stalls — Mapping Current Reality

• Which legacy registries, siloed systems, or vendor products are currently central to surveillance and reporting?
• What lab reporting pathways do you receive today (select all that apply)? Options: Real-time HL7 ELR, Batch HL7, FHIR-based feeds, Flat-file uploads (SFTP), Fax/Scanned PDFs, Manual entry by staff, Other
• List the interfaces you currently maintain (EHRs, LIS, hospitals, regional labs) and the approximate number of partners per interface type.
• How timely and complete are your current data feeds on average? Options: Near real-time and high completeness, Moderate latency (hours–days), some gaps, Significant delays (days–weeks), incomplete, Highly variable by partner
• What recurring failure modes or bottlenecks do you see when trying to modernize these feeds (e.g., mapping drift, partner capacity, vendor lock-in)?

When the System Fails — Pain, Incidents, and Impact

• Tell us about a recent incident where delayed, missing, or incorrect data caused operational or public-health harm (what happened and who was affected?).
• Which of the following impacts have you experienced or fear most from data problems? Options: Missed outbreak detection, Incorrect CDC reporting, Policy/legal exposure, Eroded public trust, Excess staff overtime, Loss of funding
• On average, how many staff-hours per week are spent on manual reconciliation, phone/fax follow-up, or data cleaning related to surveillance feeds? Options: <5 hours, 5–15 hours, 15–40 hours, >40 hours, Unknown
• How do these failures make your team feel — frustrated, burned out, resigned, or something else? Give an example of a recurring frustration.
• When issues occur, who is expected to remediate them and how long does it typically take to resolve critical outages? Options: In-house IT, Vendor support, Partner/hospital IT, Mixed response, Resolution time varies widely

What Would ‘Right’ Actually Look Like?

• If our platform delivered a clear win for your department, what single outcome would convince leadership you made the right choice?
• Which outcomes below should be prioritized for this engagement? Options: CDC-compliant reports, Interoperable ELR and IIS, Faster outbreak detection, Reduced manual work, Consolidated case management, Other
• Please define 2–3 measurable success metrics you would use to accept the implementation (e.g., report latency < X hours, completeness > Y%).
• Are there any absolute constraints that cannot be changed (data residency, specific security certifications, maximum annual spend)? Options: Data residency requirement, Specific security standard (e.g., FedRAMP/HIPAA), Max annual budget cap, Procurement method constraint, None absolute, Other
• Who outside your organization needs to see these results to be satisfied (CDC, local jurisdictions, legislature)? Options: CDC, State leadership/commissioner, Local health jurisdictions, Legislature/oversight committee, Grantors, Other

Can the Platform Fit Your Real Workflows?

• Which real-world workflows do vendors typically underplay but are central to your operations (examples: lookup reconciliation, lab result triage, vaccine inventory matching)?
• Please describe 2 representative data scenarios (source → transformation → destination) that must work exactly as you expect.
• Which interface types must be supported for a successful implementation? Options: HL7 v2 ELR, FHIR (R4), ADT feeds, Flat-file SFTP, API-based integrations, Manual uploads, Other
• What CDC reports and specific formats/versions are required for your jurisdiction (select all that apply)? Options: NNDSS/CDC forms, ELR to CDC, IIS forecasting, Meaningful Use/Promoting Interoperability, Custom state reports, Unknown
• How much historical data must be migrated and what is the minimum acceptable fidelity/date range? Options: No migration needed, Last 1 year, Last 3 years, Full historical record, Selective critical records only

Budget, Timelines, and the Procurement Minefield

• What single procurement requirement is most likely to delay or kill this purchase (e.g., procurement vehicle, vendor certification, budget timing)?
• What is your target go‑live timeframe and are there immovable dates tied to grant cycles or mandates? Options: Immediate (≤3 months), Short (3–6 months), Medium (6–12 months), Long (>12 months), Linked to grant/mandate date
• What funding source(s) will you use and what approval steps are required before funds can be committed? Options: Federal grant (CDC/DMI), State appropriation, Local budget, Hybrid, Unknown
• Which contracting model do you prefer or require? Options: Fixed-price SOW, Time & materials, Subscription SaaS, Hybrid, State master contract/agency vehicle
• What is the expected length of procurement / contracting from RFP to signature under your process? Options: <3 months, 3–6 months, 6–12 months, >12 months, Varies widely

People, Training, and Change Readiness

• If adoption stalls after go‑live, whose responsibility is it to drive ongoing use and how would they be measured?
• What internal teams will support day‑to‑day operations (select all that apply)? Options: State IT/Infrastructure, Public Health Informatics, Laboratory IT, Local jurisdiction IT, Vendor-managed support, Other
• What type(s) of training do your users prefer and expect (classroom, remote live, self-paced, train-the-trainer)? Options: Live instructor-led, Recorded self-paced, Train-the-trainer, Role-based workshops, On-site shadowing, Other
• What level of testing and validation will you require before we can declare acceptance (unit, integration, CDC-specified validation, parallel run)? Options: Unit testing, Integration testing, CDC validation tests, Parallel production run, User acceptance testing (UAT)
• What existing runbooks, SOPs, or governance artifacts must we align with or update during deployment?

What Would You Need from Us to Say Yes?

• What's the smallest, most convincing deliverable we could produce in 60 days to unblock procurement or leadership? Options: Pilot with one lab, Mapping & gap analysis, Interface proof-of-concept, Security/compliance package, Costed implementation plan
• What acceptance criteria must be demonstrably met for a pilot to be considered successful?
• What are the top three risks you fear in this program and how would you like us to mitigate them?
• Who should be on the executive steering list and who is the single person we should brief with updates?
• What is your ideal communication cadence for status updates during discovery and implementation? Options: Weekly, Bi-weekly, Monthly, Ad-hoc for critical issues only

Set the Stage: What Does 'Normal' Look Like Here?

• Briefly describe the core systems, teams, and data flows that make up your surveillance ecosystem today.
• Which core registries and systems are actively used for surveillance and reporting? Options: Case surveillance registry, Immunization Information System (IIS), Laboratory Information System (LIS), Syndromic surveillance system, Vital records, Other
• Who owns or is the primary steward for each system you listed (team or role)?
• How confident are you in the accuracy and completeness of data feeding federal reporting from these systems? Options: Very confident, Somewhat confident, Uneasy about gaps, Not confident at all
• When was the last major upgrade, migration, or vendor change for any of these registries? Options: Within the last year, 1–3 years ago, 3–7 years ago, 7+ years ago, Never
• Name one process or system that actually feels reliable today—and why it deserves that trust.

If Something Breaks, Who Notices First?

• Think back 12 months: what single system failure caused the most operational panic, and why did it escalate?
• Which stakeholders experienced the biggest impact when that failure occurred? Options: Epidemiologists/analysts, CIO/IT operations, Laboratory leadership, Clinical partners, CDC/state reporting team, Local public health officials, Other
• How long did it typically take your team to detect that class of failure? Options: Minutes, Hours, Same day, Days, Weeks
• How long did it take to restore normal operations after that incident? Options: Under an hour, Several hours, Same day, Multiple days, Weeks
• After that event, did your organization change priorities or resources toward modernization? If so, how? Options: Accelerated plans, No change, Deprioritized other work, Added temporary resources, Started procurement
• Are there recurring failure patterns you expect to return? Please describe one such pattern and its downstream impact.

Where Does Your Data Really Live (and Who's Still Trusted?)

• Which legacy registry or data store feels like the single biggest bottleneck to progress—and what makes it so sticky?
• List the legacy products and versions currently in production (e.g., product name + version or year).
• Which data models and storage formats are we working with across registries? Options: Proprietary schema, HL7 v2 message store, FHIR resources, Flat CSV/Excel files, Relational database (SQL), Other
• Are any registries technically decommissioned but still relied upon as the source of truth? Options: Yes, No, Unsure
• If some decommissioned systems are still trusted, which ones and why do people keep relying on them?
• How often do you run deduplication, reconciliation, or manual corrections to keep registries usable? Options: Daily, Weekly, Monthly, Quarterly, Rarely/Never

How Do Lab Results Actually Arrive (The Real Story)?

• If you trace a single positive lab result from the submitting lab to your surveillance dashboard, where are the most fragile handoffs?
• Which lab reporting paths are currently active with your jurisdiction's systems? Options: HL7 v2 over MLLP, FHIR REST API, Flat-file (SFTP/CSV), Fax, Email attachments, Manual entry via portal, Other
• Approximately how many sending labs or facilities still submit results via fax or paper? Options: None, 1–10, 11–50, 51–200, 200+
• When faxed or paper results arrive, who digitizes them and what is the typical turnaround time?
• Do you have automated parsing for flat files and non‑standard feeds, or are they manually processed? Options: Fully automated parsing, Partially automated with human review, Manual processing, No consistent process
• How frequently do missing or malformed lab messages cause CDC or state report delays? Options: Daily, Weekly, Monthly, Rarely, Never

Who Owns the Connectors — and Are They Healthy?

• If an auditor reviewed your interface inventory tomorrow, what single discovery would be most embarrassing or risky?
• Which types of interfaces and connectors are in use across your ecosystem? Options: HL7 v2 over MLLP, HL7 v2 via SFTP, FHIR APIs, Flat-file SFTP/CSV, VPN/Direct secure link, SMTP/email ingest, Fax ingestion, Manual CSV uploads, Other
• How many unique sending partners (hospitals, reference labs, clinics) do you actively manage? Options: 0, 1–10, 11–50, 51–200, 200+
• Who is responsible for daily interface maintenance and triage? Options: State IT team, Vendor/managed service, Local jurisdiction IT, Shared model (state + vendor), Other
• How often do you run end-to-end interface tests that include data being processed through to reporting? Options: Monthly, Quarterly, Annually, Only ad hoc/when issues arise, Never
• What documentation exists per interface (message spec, contact, SLA) and where is it stored? Options: Complete and centralized, Partial and scattered, Sparse, None

Migration Nightmares We Should Know About

• What hidden technical debt or political obstacle would derail a migration if we ignored it?
• Have past modernization or migration efforts failed or stalled? Tell us when, what happened, and why.
• Which of the following blockers have you encountered during previous modernization attempts? Options: Funding gaps, Procurement delays, Staffing shortages, Incompatible data models, Third‑party vendor issues, Stakeholder misalignment, Regulatory/mandate changes, Other
• Do you have test environments, sandbox data, and CI/CD pipelines available for partner integration work? Options: Full test environments and realistic data, Partial test environments, Test environments without real data, No test environments
• How do data governance, privacy, and consent requirements tend to surface as blockers during projects?
• Which fiscal, legislative, or grant timelines must we align with to avoid project stalls? Options: Procurement windows, Legislative sessions, State fiscal year/funding cycle, Grant award cycles, No fixed constraints, Other

What Would a Safe, Fast Modernization Actually Feel Like?

• Imagine modernization succeeded in six months—what would be the single most visible change for your team or the public?
• Which outcomes should we prioritize (select all that matter most)? Options: Timely CDC reporting, Interoperable ELR/IIS, Reduced manual processing, Faster outbreak detection and response, Improved data quality and deduplication, Lower operational cost, Actionable analytics and dashboards, Other
• What non‑negotiable constraints must any solution respect (budget, procurement rules, data residency, no downtime, etc.)? Options: Budget cap/limits, Procurement/contract constraints, Staffing limits, Data residency/compliance rules, No disruption to live CDC reporting, Mandated reporting timelines, Other
• Who must be engaged in governance and sign‑off (roles or specific people)? Options: CIO/IT Director, Epidemiology lead, Laboratory director, Immunization program lead, Legal/privacy officer, Procurement officer, Local health jurisdiction reps, Other
• What measurable success metrics would make you declare a 90‑day win and a 12‑month win?
• Realistically, when could you commit to a one‑week technical discovery workshop with your technical leads and an appropriate sandbox? Options: Within 2 weeks, 2–6 weeks, 1–3 months, 3+ months, Unsure

Getting Grounded: Who's In the Room and What They Own

• Who will be our primary deployment point of contact and who are the 1–2 backups we should plan to loop in? Options: State CIO/Deputy CIO, Informatics Director, Integration/EHR Lead, Lab IT Lead, Program Manager, Other
• Which environments do you currently operate that we must consider during deployment (select all that apply)? Options: Production, Staging / Pre-Prod, Sandbox, Legacy registry environment, Partner test endpoints, None / Unsure
• Please list the legacy registries, lab systems, and reporting endpoints we will need to inventory or migrate from (include system name and owner).
• What internal governance or steering committee meetings already exist that must approve deployment milestones? Options: Weekly executive steering, Biweekly technical working group, Monthly governance board, Ad hoc approvals only, None

What Could Break During Cutover (and Why It Matters)

• If deployment goes sideways tomorrow, what single operational failure would cause the most critical public‑health impact? Options: Loss of ELR feeds, Incorrect CDC report submissions, IIS reconciliation failures, Case management outages, Mass misrouting of lab results, Other
• Tell us about a past deployment or integration that had an unexpected failure—what happened, who noticed it first, and how long did it take to restore normal operations?
• How much downtime (if any) is acceptable for each critical capability during cutover? Options: Zero tolerance (must be live), Under 1 hour, 1–4 hours, Up to 24 hours, Multi-day allowed only with prior approval
• Who needs to be notified immediately (roles/teams) if a cutover incident threatens CDC reporting or hospital operations? Please include contact methods.

Who Holds the Keys: Access, Credentials, and Bottlenecks

• Do any of your systems rely on a single person or contractor for credentials or admin access that would block testing or go‑live if they were unavailable? Options: Yes, one person, Yes, one contractor, No, distributed access, Unsure—need to check
• Please enumerate systems that require privileged credentials for vendor testing (e.g., LIS, IIS admin, SFTP, ADP) and the average lead time to obtain access.
• What is your standard process and SLA for provisioning vendor/test credentials and network access (VPN/IP allowlist)? Options: <48 hours, 3–7 days, 1–3 weeks, Longer / paper process
• Are there any audit, legal, or HR approvals (e.g., background checks, BAAs, state vendor onboarding) that typically slow down access for external teams? Options: Yes—background checks, Yes—state vendor onboarding, Yes—legal/BAA, No major approvals, Unsure

Interfaces: Which Connections Are Fragile, and Who Will Help?

• Which interfaces do you suspect are under‑documented or ‘fragile’ and likely to require custom troubleshooting? Options: Hospital ELR (HL7 v2), Lab LIS connections, EHR ADT feeds, FHIR endpoints, Flat‑file/fax conversions, Statewide IIS interfaces, Unsure
• For each partner system (hospitals, reference labs, commercial labs, EHR vendors), do we have a technical contact and agreed test windows? If not, which partners are outstanding?
• Do you have sample messages (HL7 v2, FHIR resources, flat files) we can use in early validation, and can we get them with real-world variations (e.g., different facility codes, missing fields)? Options: Yes—full samples available, Partial samples available, No samples available, Unsure
• Which message types and versions must be supported during initial interface configuration? Options: HL7 v2.3.1, HL7 v2.5.1, FHIR R4, Fixed-width/CSV flat-file, Other

Data Reality Check: Can the Legacy Data Be Trusted?

• How confident are you that migrated legacy data will be complete and accurate enough to drive reporting without manual reconciliation? Options: Very confident, Somewhat confident, Skeptical, Not confident / expect heavy cleanup
• What known data quality issues should we expect (e.g., mismatched patient identifiers, missing lab result codes, inconsistent timestamps)?
• Do you maintain a data stewardship team or documented data dictionary that we can reference during mapping and migration? Options: Yes—formal data steward/team, Informal stewards across teams, No documented steward, Unsure
• Would you be open to a short joint data profiling run (sample extracts + automated report) before we scope migration effort? Options: Yes—schedule it, Maybe—need approval, No

Test Environments: Where We Fail First (and How to Avoid It)

• Do you have a production‑representative test environment where we can run end‑to‑end validation, including partner endpoints and a realistic volume of messages? Options: Yes—fully representative, Partially representative, No dedicated environment, Unsure
• How often is that test environment refreshed with production data (anonymized) and who owns the refresh process? Options: Daily, Weekly, Monthly, Rarely/never, Unsure
• What level of vendor access to test systems are you comfortable granting (read-only, write/test submits, admin)? Options: Read-only, Write/test submits, Admin access, Limited by request, Unsure
• Which tests would you expect to run in test environments before any production cutover (select all that apply)? Options: Interface connectivity, Message parsing & reconciliation, CDC report generation, IIS reconciliation, Performance/load tests, User acceptance testing (UAT)

People & Timing: Is Your Team Really Available?

• Be candid: during the proposed deployment window, what percentage of your core informatics team can be dedicated to vendor testing and cutover activities? Options: 100%, 60–99%, 30–59%, Less than 30%, Unavailable/unknown
• Which roles will need to be present for technical validation and final sign‑off (e.g., lab SME, epidemiologist, IIS admin, procurement)? Options: Lab SME, Epidemiologist, IIS admin, Clinical informaticist, Procurement/Legal, Other
• Are there seasonal workloads, staffing constraints, or planned public‑health events that would make particular dates risky for go‑live? Options: Yes—seasonal (e.g., flu season), Yes—planned events (conferences, audits), No major conflicts, Unsure
• What training cadence and format helps your users adopt new workflows fastest (role‑based live training, recorded modules, train‑the‑trainer)? Options: Live role‑based, Recorded modules, Train‑the‑trainer, Onsite shadowing, Hybrid

Risk & Rollback: Can We Undo a Bad Day?

• If the new system caused reportable-data issues or an outage, do you have a defined, rehearsed rollback or mitigation playbook we must align with? Options: Yes—documented & rehearsed, Documented but untested, No playbook, Unsure
• What concrete rollback triggers should we agree on (e.g., CDC report mismatch > X%, more than Y failed messages per hour)?
• How do you expect CDC/state reporting continuity to be handled during a rollback or partial outage? Options: Send via legacy processes, Manual interim reporting, Pause non-essential reports, Other
• Who is authorized to declare a rollback or emergency stop (names/roles), and what is the expected notification timeline to partners and stakeholders?

Acceptance & Go‑Live: What 'Good' Actually Means

• Are your acceptance criteria specific, measurable, and assigned to named approvers—or are they still broadly defined? Options: Specific & assigned, Defined but need owners, Broad/vague, Not defined yet
• Which of the following must pass before go‑live (select all that apply)? Options: All ELR messages parsed and reconciled, CDC reports match legacy by X%, IIS reconciliation within tolerance, No critical defects open, User acceptance testing complete
• Who will sign final go/no‑go (title and authority), and what is the expected timeframe for final acceptance after the last test?
• What post‑go‑live monitoring period and criteria do you require before declaring the deployment ‘stable’? Options: 30 days with daily checks, 14 days with targeted checks, 7 days with audits, Other

Commitments That Make Readiness Real

• What's the single, non‑negotiable commitment your organization can make today to reduce the biggest deployment risk?
• Which procurement, legal, or funding milestones must be cleared before we can schedule detailed test windows? Options: Signed contract, PO issued, BAA executed, Budget appropriation, None
• When would you be ready to begin joint pre‑deployment activities (data profiling, test endpoint setup, credential provisioning)? Options: In 2–4 weeks, Immediately, In 1–3 months, Later / unsure
• Who should we schedule a 30‑minute readiness walk-through with (roles) to convert this discovery into an actionable pre‑deployment plan?

Start Here: Quick Snapshot of Your Validation World

• Who is our primary point of contact and final decision-owner for acceptance testing? Options: CIO/CTO, Informatics Director, Epidemiology Lead, Laboratory Director, Project Manager, Other
• Who else needs to be in the room (internal and external) when we run acceptance tests? Options: State epidemiology, Laboratory informatics, IIS manager, Procurement/Legal, Vendor IT/Integration, External lab/hospital partner, Other
• What is your target acceptance-testing window or go‑live date (month/year)? Options: Within 1 month, 1–3 months, 3–6 months, 6–12 months, No firm date yet
• Briefly describe any previous experience running platform acceptance tests (tools used, major gaps, or things that went well).
• Are there non-negotiable external deadlines we must validate against (e.g., CDC reporting cutover, grant milestones)? If yes, name them and their dates.

If This Goes Sideways, What Breaks First?

• What single integration, report, or process failure would cause the most operational harm on day one of go‑live?
• How often have you experienced that failure mode in the last 12 months? Options: Weekly, Monthly, A few times a year, Once, Never documented
• Which known failure modes should we prioritize in testing (select all that apply)? Options: HL7 parsing errors, FHIR mapping mismatches, Flat-file misreads, Missing lab identifiers, Duplicate patient merges, IIS reconciliation mismatches, Report generation timing failures, Other
• How quickly do you typically detect a critical data flow failure today? Options: <1 hour, 1–4 hours, Same day, 1–3 days, Longer / unknown
• Share a recent incident (what happened, impact, how it was fixed) that reveals a validation blind spot we should plan to test against.

How Perfect Does the Data Need to Be?

• Which CDC or state report cannot tolerate more than a tiny error rate—call out the report and acceptable error threshold. Options: ELR (Lab positives), IIS vaccination counts, Reportable conditions totals, Syndromic alerts, Other
• For each selected reporting stream, what numerical error thresholds are acceptable (e.g., 0%, <1%, <5%, <10%, other)? Options: 0%, <1%, <5%, <10%, Depends — explain in next field
• Describe the reconciliation cadence and owner for IIS and ELR discrepancies (how often and who signs off).
• Which data elements are mission‑critical and must be validated end‑to‑end during acceptance (select all that apply)? Options: Patient identifiers (MRN/SSN), Lab test codes/LOINC, Result values, Specimen collection dates, Vaccination lot numbers, Provider facility IDs, Case status fields, Other
• How tolerant is your team of transient discrepancies immediately post‑go‑live (hours/days/weeks) before escalation? Options: Hours, Same day, 1–3 days, Up to a week, Longer — acceptable for now

Prove It: What Acceptance Tests Will Convince You?

• If we ran a single 'make‑or‑break' test that would prove the system is production‑ready, which test would that be and why?
• Select the test types you require as part of formal acceptance (we'll orchestrate these): Options: HL7 v2 message ingestion and parsing, FHIR resource validation, Flat‑file batch processing, ELR to CDC report generation/format, IIS reconciliation and match rates, End‑to‑end case creation from lab result, Load/performance under expected peak, Security/role‑based access tests, Backup/restore and DR failover
• For each required test type, what pass/fail criteria should we use (e.g., matching rate >= X, latency < Y seconds)?
• Do you require synthetic test data, de‑identified production samples, or live partner feeds for validation? Options: Synthetic test data, De‑identified production extracts, Live partner feeds, Combination, Undecided — need vendor recommendation
• Which external partners must participate in acceptance tests (labs, hospitals, IIS vendors)? Please name or describe their roles.

Who Holds the Pens? Governance, Acceptance, and Change Control

• Who has final authority to sign 'Acceptance Complete'—title and organization? Options: CIO/CTO, Informatics Director, Epidemiology Director, Program Manager/Grant Lead, Cross‑functional committee, Other
• What governance steps (review boards, technical validation, legal/procurement) must happen before sign‑off? Options: Technical review, Clinical/epidemiology signoff, Legal/procurement review, Security/compliance review, Executive approval, Other
• Describe the formal acceptance artifacts you require (e.g., test report, reconciliation logs, runbook approvals).
• How will change requests discovered during acceptance be triaged (rapid patch, deferred backlog, block acceptance)? Options: Must be fixed before acceptance, Critical fixes only, Document and defer to backlog, Case‑by‑case with governance
• What is your expected turnaround for sign‑off once passing test artifacts are delivered? Options: <48 hours, 3–5 business days, 1–2 weeks, Longer / depends

Practice, Fail, Learn: Runbooks, Simulations, and Rollback

• Imagine a sudden surge in positive lab results during cutover—what immediate actions must be executable from an agreed runbook?
• Do you already have runbooks for validation, cutover, and post‑go‑live troubleshooting? Options: Yes — complete and tested, Yes — draft only, No — need templates, Unsure
• Which runbook owners or roles must attest they understand the procedures before go‑live? Options: Epidemiology lead, Lab informatics, IIS administrator, Vendor technical lead, Helpdesk/Operations, Other
• What rollback criteria would trigger returning to legacy flows (e.g., data loss, >X% missing reports, SLA breach)?
• How often would you like us to run live drills or simulations before go‑live (to exercise runbooks)? Options: Weekly, Biweekly, Monthly, One full dress rehearsal, None requested

After Go‑Live: How Will You Know It's Working?

• What are the top 3 early‑warning metrics you'd watch in the first 30 days (be specific: e.g., ELR daily volume match rate, IIS reconciliation delta)?
• What dashboarding or alerting thresholds do you want in place for automated escalation? Options: Message parsing failure > X%, Report mismatch > X%, Latency > X minutes, Interface down > X minutes, Other — describe
• Who should be on the incident escalation list for the first 90 days post go‑live? Options: Vendor on‑call, State IT operations, Epidemiology lead, Lab informatics, IIS admin, Other
• How long do you expect the vendor to remain in a high‑touch support mode after acceptance? Options: 30 days, 60 days, 90 days, 6 months, Other
• What ongoing governance cadence would make you comfortable for monitoring and continuous improvements (weekly, biweekly, monthly)? Options: Weekly, Biweekly, Monthly, Quarterly

Documentation and Evidence: What Do We Need To Leave Behind?

• Which formal documents must be delivered and signed as part of acceptance (select all that apply)? Options: Test execution reports, Reconciliation logs, Runbooks and playbooks, Configuration freeze checklist, Security/compliance evidence, Data migration validation report, Other
• Do you require traceable test artifacts that map each test case to acceptance criteria (e.g., test case ID → result → evidence)? Options: Yes, required, Nice to have, No
• Are there any formats or templates your procurement or audit teams insist we use for acceptance documentation?
• Who will archive and maintain acceptance artifacts for future audits, and where will they be stored? Options: State records/IT, Program office, Vendor repository, Shared cloud drive, Other
• Is evidence of successful CDC reporting (sample transmitted reports and confirmation receipts) required before sign‑off? Options: Yes — mandatory, Preferred but not mandatory, No