import type { Problem } from '@/types/pmr'

export const problems: Problem[] = [
  {
    id: 'prob-budget',
    code: 'MGT001',
    description: '£220M prescribing budget oversight and management',
    since: 'Jul 2024',
    status: 'Active',
    narrative: 'Responsible for managing the £220M prescribing budget for NHS Norfolk & Waveney ICB. Developed sophisticated forecasting models identifying cost pressures and enabling proactive financial planning. This is an ongoing responsibility requiring continuous monitoring and strategic intervention.',
    linkedConsultations: ['deputy-head-2024'],
  },
  {
    id: 'prob-sql-transform',
    code: 'TRN001',
    description: 'Patient-level SQL analytics transformation',
    since: '2025',
    status: 'In Progress',
    narrative: 'Leading transformation from practice-level data to patient-level SQL analytics, enabling targeted interventions and a self-serve model for the wider team. This foundational change will unlock previously impossible analysis at population scale.',
    linkedConsultations: ['interim-head-2025', 'deputy-head-2024'],
  },
  {
    id: 'prob-data-literacy',
    code: 'LEA001',
    description: 'Team data literacy programme',
    since: 'Jul 2024',
    status: 'In Progress',
    narrative: 'Educating colleagues on data interpretation and analytics best practices, improving data fluency across the team through training, documentation, and self-serve tools. Ongoing initiative to build sustainable analytical capability.',
    linkedConsultations: ['deputy-head-2024'],
  },
  {
    id: 'prob-efficiency',
    code: 'EFF001',
    description: 'Manual prescribing analysis inefficiency',
    resolved: 'Oct 2025',
    status: 'Resolved',
    outcome: 'Python algorithm: 14,000 pts, £2.6M/yr',
    narrative: 'Built Python-based switching algorithm using real-world GP prescribing data to automatically identify patients on expensive drugs suitable for cost-effective alternatives. Compressed months of manual analysis into 3 days. Identified 14,000 patients and £2.6M in annual savings, with £2M on target for delivery this financial year.',
    linkedConsultations: ['interim-head-2025'],
  },
  {
    id: 'prob-efficiency-target',
    code: 'EFF002',
    description: '£14.6M efficiency target identification and delivery',
    resolved: 'Oct 2025',
    status: 'Resolved',
    outcome: 'Over-target performance achieved',
    narrative: 'Identified and prioritised a £14.6M efficiency programme through comprehensive data analysis. Achieved over-target performance by October 2025 through targeted, evidence-based interventions across the integrated care system.',
    linkedConsultations: ['interim-head-2025'],
  },
  {
    id: 'prob-blueteq-backlog',
    code: 'AUT001',
    description: 'Blueteq form creation backlog',
    resolved: '2023',
    status: 'Resolved',
    outcome: '70% reduction, 200hrs saved',
    narrative: 'Developed software automating Blueteq prior approval form creation. Achieved 70% reduction in required forms, 200 hours immediate savings, and ongoing 7–8 hours weekly efficiency gains.',
    linkedConsultations: ['high-cost-drugs-2022'],
  },
  {
    id: 'prob-asthma-screening',
    code: 'INN001',
    description: 'Asthma screening scalability',
    resolved: '2019',
    status: 'Resolved',
    outcome: 'National rollout: ~300 branches, ~£1M',
    narrative: 'Identified and shared an asthma screening process that was adopted nationally across the Tesco pharmacy estate (~300 branches). Reduced pharmacist time from approximately 60 hours to 6 hours per store per month, enabling the network to claim approximately £1M in revenue.',
    linkedConsultations: ['pharmacy-manager-2017'],
  },
  {
    id: 'prob-incentive-calc',
    code: 'AUT002',
    description: 'Incentive scheme manual calculation',
    resolved: '2025',
    status: 'Resolved',
    outcome: 'Automated: 50% Rx reduction in 2 months',
    narrative: 'Automated incentive scheme analysis, improving accuracy and targeting precision whilst enabling a novel GP payment system linking rewards to delivered savings. Achieved 50% reduction in targeted prescribing within the first two months of deployment.',
    linkedConsultations: ['interim-head-2025'],
  },
  {
    id: 'prob-hcd-tracking',
    code: 'DAT001',
    description: 'High-cost drug spend tracking gaps',
    resolved: '2023',
    status: 'Resolved',
    outcome: 'Blueteq-secondary care data integration',
    narrative: 'Integrated Blueteq data with secondary care activity databases, resolving critical data-matching limitations and enabling accurate high-cost drug spend tracking across the system.',
    linkedConsultations: ['high-cost-drugs-2022'],
  },
  {
    id: 'prob-pathway-opacity',
    code: 'VIS001',
    description: 'Patient pathway opacity',
    resolved: '2023',
    status: 'Resolved',
    outcome: 'Sankey chart analysis tool',
    narrative: 'Created Python-based Sankey chart analysis tool visualising patient journeys through high-cost drug pathways, enabling trusts to audit compliance and identify improvement opportunities.',
    linkedConsultations: ['high-cost-drugs-2022'],
  },
  {
    id: 'prob-opioid-monitoring',
    code: 'MON001',
    description: 'Population opioid exposure monitoring',
    resolved: '2024',
    status: 'Resolved',
    outcome: 'CD monitoring system: OME tracking',
    narrative: 'Developed Python-based controlled drug monitoring system calculating oral morphine equivalents across all opioid prescriptions to track patient-level exposure over time, identifying high-risk patients and potential diversion—enabling previously impossible patient safety analysis at population scale.',
    linkedConsultations: ['deputy-head-2024'],
  },
]
