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Work that speaks
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Real healthcare organisations. Real data problems. Real outcomes. Here's what happens when clinical domain knowledge meets analytical rigour.

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01
Telehealth · Remote care startup
Clinician-Facing Dashboard for a Remote Rehabilitation Startup
PythonSQLLooker StudioData Engineering
The challenge

A telehealth company delivering remote rehabilitation and wellness programmes was collecting patient data but had no reliable way to measure whether patients were actually improving, or flag those at risk of dropping off. Leadership needed a clear, measurable system: who is adhering to their programme, whose health is improving, and what patterns should drive care decisions.

3+
Clinical KPIs tracked per patient
↓
Patient drop-off reduced within month one
Weekly
Automated reporting replacing manual tracking
How we approached it
Clarity session — defined "adherence" and "progress" in clinical terms aligned to actual care team workflows
Data audit across exercise logs, consultation records, patient goals, vitals, pain scores, and session attendance
Built an adherence scoring framework — turning messy exercise logs into a per-patient, per-week adherence score
Designed a decision-ready dashboard in Looker Studio — built for clinical huddles, not data analysts
Outcomes
✓Clinicians gained full real-time visibility into patient adherence for the first time
✓Manual tracking eliminated — weekly automated reporting replaced the spreadsheet workflow
✓Patient drop-off reduced within first month of dashboard use
✓Programme effectiveness measurably demonstrated — strong foundation for scaling
View full project →
02
Digital health · Wearable tech startup
Sleep Health Prediction Model for a Digital Health Platform
PythonAI / MLPredictive ModellingLooker Studio
The challenge

A wearable tech startup wanted to move beyond generic sleep metrics and offer users personalised, data-backed sleep health insights. The product team needed to understand which lifestyle and health factors most strongly predicted sleep quality — and whether those insights could power a continuous recommendation engine embedded in the product.

4
Key predictive factors identified for sleep health
↑
User engagement potential via personalised insights
Scalable
Methodology reusable with longitudinal data
How we approached it
Data preparation & EDA — demographics, lifestyle variables, BMI, blood pressure, stress levels, sleep patterns cleaned and unified
Composite Sleep Health Score — derived from sleep duration and quality data; used as the predictive target
Regression modelling (linear and polynomial) to identify the factors most strongly driving sleep health outcomes
Interactive dashboard for product, clinical, and wellness stakeholders — surfacing correlations and actionable insights
Outcomes
✓Stress level and diastolic BP identified as strongest negative predictors of sleep health
✓Physical activity identified as the strongest positive predictor — a clear product intervention point
✓Scalable analytics foundation built — extensible to clinical-grade prediction with longitudinal data
✓Product team equipped with a personalised recommendation framework to differentiate in a saturated market
View full project →
03
Public health · NGO · YOHAN Africa
Hepatitis B Awareness & Vaccination Analysis — Multi-Campus Field Study
SPSSGoogle SheetsSurvey AnalysisChi-Square
The challenge

The Youth Health Action Network (YOHAN Africa) ran a Hepatitis B outreach across multiple campuses in Enugu, Nigeria. They had 399 completed questionnaires and needed a public health analyst to turn scattered field data into a clear, evidence-based strategy — identifying high-risk groups, vaccination gaps, and where future campaigns should focus.

399
Questionnaires analysed across multiple campuses
63.9%
Had poor actual knowledge despite 87.5% awareness
6.3%
Vaccination uptake — the critical gap surfaced
How we approached it
Objective alignment with programme leads — defined three specific research questions before touching the data
Knowledge scoring framework — standardised metric to classify every student's actual HBV awareness (good, fair, poor)
Prevention & practice scoring — measured how well knowledge translated into protective behaviour across screening, vaccination, and safe-sex practices
Chi-square analysis to identify high-risk groups by faculty, gender, institution, and income — enabling targeted intervention
Outcomes
✓Insights formed the backbone of a research manuscript and helped YOHAN secure future campus partnerships
✓NGO shifted to targeted, faculty-specific interventions — making every resource count
✓Improved vaccination drive strategy based on clear awareness-to-action gap analysis
✓Dataset now serves as a long-term baseline for monitoring HBV knowledge and prevalence over time
View full project →

More projects in progress

We're completing several new engagements across claims analytics, patient journey analysis, and AI strategy for healthcare organisations. These will be published here as they complete.

Analytics consulting
Claims Denial Prediction & Root Cause Analysis
Pre-submission scoring model and operational dashboard for a healthcare payer — reducing denial rates through predictive analytics.
Coming soon
SQL & data engineering
Patient Journey & Episode-of-Care Analysis
SQL-heavy analysis mapping patient pathways across care episodes using MIMIC-IV clinical data.
Coming soon
AI strategy
CDS Alert Effectiveness Analysis
Evaluating clinical decision support alert fatigue and effectiveness — with an agentic intelligence layer.
Coming soon

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