Overview
I built a repeatable decision framework. It translated NHS and ONS datasets into an executable UK market entry plan. The plan defined priority regions, channel strategy, and device-to-consumable planning for Heagital’s PT INR point-of-care solution.
Heagital is a UK MedTech startup. It is developing a connected PT INR point of care testing solution. This solution is for institutional and community healthcare settings. At an early commercial stage, the company lacked an agreed Go To Market direction. It also had no prioritised NHS regions. There were no validated channel assumptions. Decisions risked being driven by intuition rather than evidence.
I designed and implemented a quantitative market sizing framework. It includes opportunity scoring and functions as a decision infrastructure. It is not a static market report.
Core Modelling Layers
TAM model
Top down computation derived from clinical registries, converting patient cohorts into annual PT INR test volumes and adjusting for non AF indications.
Opportunity Score
A weighted, normalised index combining AF register size, prevalence, treatment gap, and Warfarin prescribing as a readiness proxy. The model prioritises executability over theoretical demand.
Serviceable Market definition
Regional opportunity weights were applied to anchor Heagital’s early phase SAM and rollout focus.
Why This Project Is Different
This project goes beyond typical analytics tools in several ways:
Technologies Used
- Python
- Linear Modelling Logic
- Streamlit
- Pandas
Key Outputs
A clinically grounded England TAM of approximately 6.7 million PT INR tests per year
A non obvious outcome where London ranked lowest due to higher DOAC uptake
Identification of three priority adoption regions representing over 53 percent of national executable opportunity
Midlands, South East, South West
Data inputs
NHS England QOF 2023 to 24 AF indicators at Integrated Care Board level
NHSBSA Warfarin prescribing volumes
ONS demographic segmentation including age above 65
NICE clinical guidance for PT INR testing frequency
Insight 