Clinical Alert
This patient has identified £14.6M in prescribing efficiency savings across Norfolk & Waveney ICS, with £2M on target for delivery this financial year.
Active Problems
£220M prescribing budget oversight and management
Patient-level SQL analytics transformation
Team data literacy programme
Current Medications
| Drug | Proficiency | Frequency | Since |
|---|---|---|---|
| Data Analysis | 95% | Daily | 2016 |
| Medicines Optimisation | 95% | Daily | 2016 |
| Power BI | 92% | Daily | 2019 |
| Python | 90% | Daily | 2017 |
| Population Health Analytics | 90% | Daily | 2022 |
| SQL | 88% | Daily | 2017 |
| Dashboard Development | 88% | Weekly | 2019 |
| NICE TA Implementation | 85% | Weekly | 2022 |
| Algorithm Design | 82% | Weekly | 2022 |
| JavaScript / TypeScript | 70% | Weekly | 2020 |
Last Consultation
Interim Head, Population Health & Data Analysis
Led strategic delivery of population health initiatives and data-driven medicines optimisation across Norfolk & Waveney ICS, reporting to Associate Director of Pharmacy with presentation accountability to Chief Medical Officer and system-level programme boards.
- Identified £14.6M efficiency programme through comprehensive data analysis
- Built Python-based switching algorithm: 14,000 patients identified, £2.6M annual savings
- Automated incentive scheme analysis: 50% reduction in targeted prescribing within 2 months
Current Appointment
Deputy Head, Population Health & Data Analysis
Current
Driving data analytics strategy for medicines optimisation, developing bespoke datasets and analytical frameworks from messy, real-world GP prescribing data to identify efficiency opportunities and address health inequalities across the integrated care system.
- Managed £220M prescribing budget with sophisticated forecasting models
- Created comprehensive medicines data table with dm+d integration, morphine equivalents, Anticholinergic Burden scoring
- Led financial scenario modelling for DOAC switching programme
- Developed Python-based controlled drug monitoring system for population-scale OME tracking
Resolved Problems
£14.6M efficiency target identification and delivery
Over-target performance achieved
Manual prescribing analysis inefficiency
Python algorithm: 14,000 pts, £2.6M/yr
Incentive scheme manual calculation
Automated: 50% Rx reduction in 2 months
Population opioid exposure monitoring
CD monitoring system: OME tracking
Blueteq form creation backlog
70% reduction, 200hrs saved
Asthma screening scalability
National rollout: ~300 branches, ~£1M