Healthcare analytics case study

Why do patients miss medical appointments?

Python code, visualizations, findings, and recommendations from 110,527 public medical appointment records.

Bar chart of missed appointments by weekday
Weekday patternTuesday and Wednesday had the highest missed-appointment counts in this descriptive view.
110,527appointment records
20.19%missed appointments
79.81%attended appointments
6visual views

Problem

Which patient and scheduling factors are associated with missed visits?

The analysis explores appointment attendance patterns across age, gender, SMS reminder status, scholarship status, and weekday. It is presented as descriptive analytics and project evidence, not as a clinical diagnostic tool.

The dataset is not bundled with the website. Local chart exports and code are provided so employers can quickly understand the workflow.

Code and recommendation

Transparent, reproducible analysis.

Python analysis fileExports the local analysis workflow used for this case study.Download code

Project reflection

Lessons Learned

This project strengthened my ability to transform public healthcare data into clear visual evidence, reproducible Python analysis, and operational recommendations while respecting model and data limitations.

Related portfolio links

Continue reviewing healthcare analytics evidence.

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