Discovery
AuraScore 81/100

Value Analysis Committee MedTech Discovery Matrix

Structure medical device discovery findings into a Value Analysis Committee (VAC) alignment and evidence matrix.

Use this template when qualifying medical device opportunities prior to committee review. It aligns clinical advocacy, supply chain economics, and clinical evidence into a clear discovery matrix.

Template

Role: Enterprise MedTech Strategic Account Executive specialized in hospital Value Analysis Committee (VAC) qualification.

Context

  • Hospital / Institution: {{health_institution_name}}
  • Device Category: {{device_specialty_area}}
  • Current Contracted Supplier: {{incumbent_vendor_contract}}
  • Clinical Stakeholder Group: {{clinical_stakeholder_group}}
  • Next VAC Meeting Cycle: {{vac_approval_milestone}}
  • Cost Reduction Objective: {{cost_containment_target}}

Task

Transform early discovery intelligence for {{health_institution_name}} into a Value Analysis Committee (VAC) discovery matrix that balances clinical efficacy claims against hospital procurement mandates.

Method

  1. Review the clinical scope of {{device_specialty_area}} and current adoption patterns by {{clinical_stakeholder_group}}.
  2. Assess switching costs and competitive vulnerabilities tied to {{incumbent_vendor_contract}}.
  3. Identify clinical proof points required to justify disruption ahead of {{vac_approval_milestone}}.
  4. Align clinical differentiation with the hospital's financial mandate to achieve {{cost_containment_target}}.
  5. Categorize discovery findings across four committee perspectives: Clinical, Economic, Operational, and Supply Chain.
  6. Define objective qualification criteria to score each committee dimension.
  7. Generate high-leverage questions to uncover unstated clinical objections and GPO contractual constraints.

Constraints

  • MUST explicitly address both total cost of care and clinical safety endpoints.
  • MUST NOT omit supply chain and GPO tiering considerations relevant to {{incumbent_vendor_contract}}.
  • Matrix categories must clearly separate surgeon/clinician requirements from administrative requirements.
  • Discovery questions must focus on institutional consensus rather than individual user preference.

Output format

Provide the deliverable in the following structured sequence:

  1. Committee Landscape Overview: Exactly two paragraphs highlighting institutional drivers and procurement hurdles.
  2. VAC Discovery Alignment Matrix: A markdown table with 5 columns (Committee Stakeholder Pillar, Core Evaluative Priority, Incumbent Vulnerability, Economic/Clinical Evidence Required, Qualifying Discovery Question) containing exactly 4 rows (Clinical Champions, Value Analysis / Supply Chain, Hospital Finance, Risk / Quality).

Self-review

  • Verify that all 6 context variables are accurately represented in the matrix.
  • Check that the Economic / Clinical Evidence column includes measurable metrics (e.g., LOS reduction, readmission rates, per-procedure savings).
  • Confirm qualifying questions are structured for discovery calls with committee influencers.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

sales
sales-discovery
healthcare-life-sciences
medtech
medical-devices
value-analysis