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Scale PV Case Processing: 5-Step System for Quality & Speed

Master pharmacovigilance case processing at scale

Stop struggling with case backlogs and overtime. This proven 5-step system scales PV operations while maintaining regulatory compliance and quality standards.

Assyro Team
8 min read

Why Pharmaceutical Companies Struggle with Case Processing at Scale

Pharmaceutical companies face an inevitable challenge: adverse event case volumes spike unpredictably, often during the worst possible times—product launches, regulatory inspections, or seasonal surges. Without a systematic approach, teams oscillate between costly overtime and dangerous backlogs, while quality deteriorates precisely when regulatory scrutiny intensifies.

This comprehensive playbook provides a battle-tested framework for scaling pharmacovigilance operations efficiently. You'll implement a dynamic triage matrix, optimize workload distribution across hybrid teams, deploy risk-based quality control, and establish performance monitoring that ensures every case meets regulatory deadlines without compromising safety standards.

The Business Case for Systematic Case Processing

Regulatory Compliance Impact

  • FDA Form 483 findings: 40% of pharmacovigilance citations relate to case processing delays or quality issues
  • EMA GVP non-compliance: Missed reporting timelines trigger immediate regulatory action
  • ICH E2D requirements: Expedited reporting failures can halt clinical trials or market access

Financial and Operational Consequences

  • Overtime costs: Surge periods can increase processing costs by 200-300%
  • Vendor premium rates: Emergency outsourcing typically costs 50-75% more than planned capacity
  • Talent retention: Predictable workloads reduce safety team turnover by up to 35%
  • Signal detection delays: Poor case quality degrades pharmacovigilance signal detection capabilities

Step 1: Engineer an Adaptive Triage Matrix

Core Classification Framework

Develop a multi-dimensional triage system that automatically routes cases based on:

  • Medical severity: Death, life-threatening, hospitalization, disability
  • Regulatory urgency: SUSARs, expedited reports, follow-ups
  • Product risk profile: New molecular entities, high-priority compounds, generic products
  • Reporter credibility: Healthcare professionals vs. consumers vs. literature
  • Geographic requirements: EU EudraVigilance, FDA FAERS, Health Canada timing

Target Processing Times by Category

| Case Type | Initial Triage | Medical Review | Submission Ready | |-----------|----------------|----------------|------------------| | Fatal SUSARs | 2 hours | 12 hours | 24 hours | | Serious Expected | 24 hours | 3 days | 7 days | | Non-serious Spontaneous | 48 hours | 7 days | 15 days | | Literature Cases | 72 hours | 10 days | 15 days |

Implementation Best Practices

  • Reviewer assignment logic: Map medical expertise to therapeutic areas and case complexity
  • Dynamic matrix updates: Quarterly reviews incorporating new products, label changes, and regulatory guidance
  • Training integration: Embed matrix logic into ICSR database workflows and standard operating procedures

Step 2: Optimize Workload Distribution with Real-Time Intelligence

Dashboard Architecture for Case Management

Implement comprehensive visibility across your entire processing ecosystem:

Volume Forecasting Metrics:

  • Rolling 12-week case intake projections
  • Seasonal adjustment factors by therapeutic area
  • Product launch impact modeling

Capacity Management Indicators:

  • Real-time FTE availability across time zones
  • Vendor capacity utilization and queue depths
  • Skills matrix matching for complex case types

Performance Tracking KPIs:

  • Cases aging beyond target by severity tier
  • Resource allocation efficiency ratios
  • Quality scores by processor and case category

Hybrid Team Orchestration

Internal Team Optimization:

  • Language capabilities: Match reporter languages to processor skills
  • Time zone coverage: Implement follow-the-sun processing for urgent cases
  • Expertise alignment: Route complex oncology cases to specialists, routine cases to generalists

Vendor Integration Strategy:

  • Tiered SLA structure: Mirror internal targets with quality-adjusted pricing
  • Quality gating: Implement vendor scorecards with monthly performance reviews
  • Escalation protocols: Clear handoff procedures for cases requiring internal expertise

Step 3: Deploy Risk-Based Quality Control Frameworks

Intelligent QC Sampling Strategy

Move beyond static sampling rates to risk-adjusted quality control:

High-Risk Categories (100% QC during onboarding, 50% ongoing):

  • New vendor processors during first 90 days
  • Cases involving investigational products
  • Reports from new geographic regions
  • Complex drug interaction assessments

Medium-Risk Categories (30% sampling):

  • Established vendor standard cases
  • Routine follow-up processing
  • Literature case assessments

Low-Risk Categories (15% sampling):

  • Experienced internal staff routine cases
  • Non-serious expected events
  • Administrative updates and reconciliations

Quality Metrics That Drive Improvement

Medical Assessment Accuracy:

  • Causality assessment concordance rates
  • MedDRA coding precision and consistency
  • Narrative quality and clinical relevance

Regulatory Compliance Measures:

  • Timeline adherence by case category
  • Completeness of required data elements
  • Accuracy of expedited reporting determinations

Process Efficiency Indicators:

  • First-pass acceptance rates
  • Rework cycles per case type
  • Time to quality approval

Step 4: Standardize Operations with Smart Automation

Template-Driven Consistency

Narrative Writing Standards:

  • Structured templates by event type and severity
  • Medical terminology standardization
  • Regulatory language compliance across regions

Assessment Frameworks:

  • Standardized causality evaluation criteria
  • Expectedness determination workflows
  • Drug interaction assessment protocols

Strategic Automation Implementation

Recommended Automation Targets:

  • Duplicate detection: AI-powered case matching across databases
  • Follow-up scheduling: Automated reminder systems for outstanding information
  • Regulatory deadline tracking: Smart alerts for approaching submission requirements
  • Data validation: Automated checks for completeness and consistency

Human-Centered Decision Points:

  • Medical causality assessments
  • Complex case narrative development
  • Signal evaluation and clinical interpretation
  • Regulatory strategy decisions

Step 5: Establish Performance Intelligence Systems

Executive Dashboard Metrics

Track indicators that demonstrate operational control and regulatory compliance:

Throughput Performance:

  • Cases processed within target timelines (by severity tier)
  • Backlog aging analysis with trend projections
  • Processing capacity utilization across teams

Quality Excellence:

  • QC finding rates per 100 cases (trending)
  • Major vs. minor finding categorization
  • Corrective action implementation timeline

Resource Optimization:

  • FTE hours vs. planned capacity
  • Overtime usage and cost impact
  • Vendor performance against SLA commitments

Regulatory Risk Management:

  • Expedited reporting timeline compliance
  • Authority query response timeliness
  • Inspection readiness scoring

Governance and Continuous Improvement

Weekly Operations Reviews:

  • Capacity planning adjustments
  • Quality trend analysis
  • Resource reallocation decisions

Monthly Executive Reporting:

  • Strategic performance summaries
  • Budget variance analysis
  • Regulatory compliance status

Quarterly Strategic Planning:

  • Triage matrix optimization
  • Technology investment priorities
  • Vendor relationship management

45-Day Implementation Roadmap

Phase 1: Foundation Building (Days 1-15)

  • Week 1: Analyze 6 months of case volume data to identify patterns and bottlenecks
  • Week 2: Conduct stakeholder interviews with safety physicians, operations leads, and vendor managers
  • Week 3: Draft initial triage matrix and escalation protocols

Phase 2: Pilot Deployment (Days 16-30)

  • Week 4: Implement pilot triage system for one therapeutic area
  • Week 5: Deploy workload distribution dashboards for pilot team
  • Week 6: Train staff on new processes and quality control sampling

Phase 3: Full Rollout (Days 31-45)

  • Week 7: Expand system to all therapeutic areas and vendor partners
  • Week 8: Implement automated workflows and performance monitoring
  • Week 9: Conduct first formal performance review and optimization planning

Strategic FAQs for Regulatory Leaders

Q: What's the optimal internal vs. outsourced case processing ratio?

A: Industry best practice suggests 60-70% internal processing for high-risk cases (SUSARs, investigational products, complex assessments) and 30-40% vendor processing for routine volume. This maintains medical oversight while providing flexibility for surge capacity.

Q: How do we handle sudden volume spikes during product launches?

A: Implement a three-tier surge response: (1) Activate cross-trained internal staff from other functions, (2) Invoke pre-negotiated surge agreements with vendors, (3) Temporarily adjust quality sampling for low-risk categories while maintaining 100% oversight for critical cases.

Q: What automation investments provide the best ROI?

A: Prioritize duplicate detection (30-40% processing time savings), automated follow-up scheduling (25% efficiency gain), and regulatory deadline tracking (eliminates 90% of timeline violations). Avoid automating medical assessments, which require human clinical judgment.

Q: How frequently should we update our triage matrix?

A: Conduct formal quarterly reviews with additional updates triggered by: new product launches, significant label changes, regulatory guidance updates, or performance trends indicating classification gaps.

Sustaining Long-Term Excellence

Continuous Improvement Framework

Weekly Tactical Reviews:

  • Performance metric analysis
  • Resource allocation optimization
  • Quality trend identification

Monthly Strategic Assessments:

  • Vendor performance evaluation
  • Technology enhancement planning
  • Staff development and training needs

Quarterly Strategic Planning:

  • Capacity forecasting for upcoming periods
  • Process optimization opportunities
  • Technology roadmap updates

Culture and Recognition

Successful scaling requires cultural transformation alongside process improvement:

  • Performance recognition: Celebrate teams maintaining quality standards during high-volume periods
  • Cross-functional collaboration: Foster partnership between safety, clinical, and regulatory teams
  • Continuous learning: Invest in ongoing training for emerging regulatory requirements and therapeutic areas

The Bottom Line: Predictable Excellence at Scale

Effective pharmacovigilance case processing isn't about managing crisis—it's about building systems that prevent crisis. With this structured approach, your organization can maintain regulatory compliance, ensure patient safety, and control costs even during the most challenging volume spikes.

The pharmaceutical industry's increasing complexity demands sophisticated operational capabilities. Organizations that master scalable case processing gain competitive advantages in market access timing, regulatory relationships, and operational cost management.

Implement this framework systematically, measure results rigorously, and iterate continuously. Your future self—and your regulatory inspectors—will thank you.