NHS Health Equity: DNA Analysis (Simulated Case Study)
Project Overview
In this simulated public health case study, I analysed 1,200 GP appointment records to investigate patterns behind missed appointments (Did Not Attend - DNA).
Using a deprivation-focused lens (IMD quintiles), I explored how social inequality may influence access to primary care services.
This project replicates the workflow of a Public Health Intelligence Analyst, from raw data cleaning to strategic recommendations.
Note: This dataset is synthetic and created for analytical portfolio purposes. No real patient or NHS operational data was used.
Skills & Tools
- SQL (SQLite): Data cleaning, missing value handling, cohort extraction, rate calculation
- Power BI: DAX measures, financial modelling, inequality visualisation
- Excel: Initial data audit and structural validation
Key Insights
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The Inequality Gap DNA rates in the most deprived quintile (37.5%) were more than double those in the least deprived quintile (14.8%).
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The Financial Impact 328 missed appointments equated to approximately £9,840 in lost clinical value within this sample.
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Concentration of Burden 53% of the total financial impact was concentrated in IMD Quintiles 1 & 2, highlighting a deprivation-driven access gap.
Strategic Recommendation (Case Study Scenario)
Based on the modelled findings, I designed a targeted “Pre-Appointment Advocacy” pilot for high-burden practices within the simulated dataset.
By prioritising patients in the most deprived quintiles, the model demonstrates potential recovery of over £2,800 in clinical capacity across two practices.