Inspiration

US population living in poverty face unprecedented pressures due to COVID-19. Although the federal government moved quickly to provide relief, more help is needed.

This project was created to help federal agencies and hospital systems help optimize scenario planning for when staff can be shifted around to serve those living in federal poverty areas.

What it does

This project looks at Historical Bed Utilization Rate, Poverty Level, Potential available in Bed capacity, and Hospital type as key features that could help forecast the staffing needs of health workers (doctors, nurses, etc). The staffing needs to a specific hospital type can be scored based on the availability enabling counties in poverty to be better served.

How I built it

I built this using AWS Sagemakre, AWS Dataexchange, AWS S3 and Pandas.

Challenges I ran into

Initial phase of this project ran into multiple challenges including find the right dataset, using appropriate data normalization technique.

As I made my way into the data analysis I found great insights while there were challenges with the tools I chose. AWS services (dataexchange, sagemaker notebooks) helped me through to complete my project.

Accomplishments that I'm proud of

I'm proud of the findings that I have from the data analysis i.e. Historical Bed Utilization Rate, Poverty Level, Potential available in Bed capacity are key features that can help forecast the staffing needs of health workers (doctors, nurses, etc). The staffing needs to a specific hospital type can be scored based on the availability enabling counties in poverty to be better served.

What I learned

I learned AWS best practices, AWS Machine learning, Data Analysis and Data Visualization.

What's next for US Poverty Level impact on Hospital Bed Utilization.

As the next steps, building a machine learning model that helps support and augment health workers where demand exists by integrating with existing staff scheduling system allowing managers to view the model recommendations, allowing healthcare stakeholders to deliver better patient care and improving productivity.

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