Umar Ramadan

My hospital readmission and length-of-stay analyses turn healthcare datasets into clear, defensible findings. In a readmission project, I analyzed 500,000 synthetic hospital records and reported an overall 30-day readmission rate of 29.08%, while documenting that the model discriminated weakly.

For my length-of-stay analysis, I created a documented cleaning pipeline for a deliberately messy 50,000-record dataset, producing 48,019 validated records. I found that diagnosis was the strongest driver and compared stays across diagnoses and care settings.

As a Registered Nurse at Jigawa State Government Hospital, I maintain clinical documentation and monitor patient indicators. This clinical work informs my understanding of healthcare data and the importance of its accuracy.

I work with Python, SQL, Excel and Power BI, and apply statistical methods including regression, hypothesis testing and model evaluation. I’m available for global remote contract opportunities and have experience with cross-border digital workflows.