Portfolio

All Projects

Browse the complete collection of healthcare data science case studies.

Classification

Appointment No-Show Prediction

Missed appointments cost healthcare systems millions annually and leave appointment slots unfilled, reducing access for other patients. This project aimed to identify which patients were most likely to miss their appointments.

Key Metric78% recall on no-show
PythonPandasScikit-learnPower BI
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Operations

Appointment Scheduling Efficiency Study

Inefficient scheduling leads to underutilised clinic time, long patient wait times, and clinician burnout. This project analysed scheduling patterns to identify improvement opportunities.

Key Metric15% improvement in slot
PythonPandasExcelPower BI
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BI

Claims Denial Rate Analysis

High claims denial rates reduce revenue and create administrative burden. This project investigated which claim types and payers had the highest denial rates and why.

Key MetricReduced denials by 18%
PythonSQLPandasPower BI
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BI

Electricity Revenue Loss Analysis (IBEDC ATC&C)

About a third of the revenue from electricity distributed across southwestern Nigeria never makes it back to the distribution company. This project built an end-to-end analytics pipeline to identify exactly where IBEDC's revenue leaks at the feeder level, validate the findings with statistical rigour, and identify which feeder characteristics actually drive the loss.

Key MetricMetering rate explains 90.6%
MySQLPythonPandasScikit-learnSciPyStatsmodelsSeaborn
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Time Series

Emergency Room Wait-Time Analysis

Long A&E waiting times lead to worse patient outcomes and increased pressure on staff. This project analysed patterns in wait times to identify bottlenecks and peak demand periods.

Key MetricIdentified 3 peak bottleneck
PythonPandasMatplotlibPower BI
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Time Series

Healthcare Staffing Demand Forecast

Workforce planning in healthcare is challenging due to seasonal demand variations, turnover, and specialty shortages. This project forecasted staffing needs across key roles.

Key Metric12-month rolling forecast with
PythonPandasScikit-learnPower BI
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Classification

Heart Disease Risk Predictor

Cardiovascular disease is the leading cause of death worldwide, and early risk identification from routine clinical data can guide timely intervention. This project built and deployed a classification model that predicts a patient's heart disease risk from clinical features, with both an interactive web interface and a programmatic API.

Key Metric87% accuracy, 0.952 ROC-AUC
PythonScikit-learnStreamlitFastAPI
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Excel

Hospital Mortality Risk Analysis

A hospital's 30-day mortality rate (3.2%) sits well above the national benchmark (2.1%). Before launching a mortality reduction programme, the Chief Medical Officer needed a statistically rigorous answer to one question: is this gap a genuine patient safety problem, or statistical noise from a riskier patient case mix?

Key MetricGap not statistically significant
ExcelPivot TablesChi-Square TestingMonte Carlo SimulationRisk Adjustment (SMR)
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Operations

Inventory Optimisation for Medical Supplies

Hospitals often face either stockouts of critical supplies or excessive inventory holding costs. This project modelled demand patterns to optimise reorder points and quantities.

Key MetricProjected 22% reduction in
PythonPandasScikit-learnExcel
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Classification

Length-of-Stay Optimisation Project

Prolonged hospital stays increase costs, reduce bed availability, and can expose patients to hospital-acquired infections. This project modelled factors contributing to extended stays.

Key MetricPredicted extended stays with
PythonPandasScikit-learnPower BI
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BI

Medical Coding Accuracy Audit

Inaccurate medical coding leads to claim denials, compliance risks, and revenue leakage. This project audited coding accuracy across departments to identify training needs.

Key Metric92% coding accuracy baseline
PythonExcelPower BI
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Classification

Patient Readmission Analysis

Unplanned hospital readmissions within 30 days indicate potential gaps in care quality and drive up costs. This project identified risk factors for readmission among diabetic patients.

Key MetricTop 5 readmission risk
PythonPandasScikit-learnPower BI
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BI

Patient Satisfaction Score Analysis

Patient satisfaction scores drive quality ratings and reimbursement decisions. This project analysed HCAHPS survey data to identify the strongest drivers of overall satisfaction.

Key Metric3 key satisfaction drivers
PythonPandasScikit-learnPower BI
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BI

Preventive Care Compliance Tracking

Low compliance with preventive care guidelines (screenings, vaccinations, check-ups) leads to worse health outcomes and higher long-term costs. This project tracked and visualised compliance patterns.

Key MetricIdentified 4 underserved population
PythonPandasPower BIExcel
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