Apr 06, 2023
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Service categories
Service Lines
Big Data
Domain focus
Healthcare
Programming language
Python
Frameworks
TensorFlow
Subcategories
Big Data
Predictive Analytics
Challenge
As well as providing healthcare, the NHS is also responsible for the training, professional development, and certification of the country’s doctors, nurses and other healthcare professionals. The NHS takes in junior doctors, who have recently completed a medical degree, and puts them on a training pathway until they qualify in a specialty, such as cardiology, urology, or general practice. It costs around £200,000 and takes about six years to train a junior doctor to reach the grade of consultant or GP. Naturally, the NHS loses money when junior doctors leave the organisation before completing a training pathway.
Higher Education England (HEE), a department of the NHS, needed a way of anticipating and understanding employee attrition.
As well as providing healthcare, the NHS is also responsible for the training, professional development, and certification of the country’s doctors, nurses and other healthcare professionals. The NHS takes in junior doctors, who have recently completed a medical degree, and puts them on a training pathway until they qualify in a specialty, such as cardiology, urology, or general practice. It costs around £200,000 and takes about six years to train a junior doctor to reach the grade of consultant or GP. Naturally, the NHS loses money when junior doctors leave the organisation before completing a training pathway.
Higher Education England (HEE), a department of the NHS, needed a way of anticipating and understanding employee attrition.
Solution
Fast Data Science designed and trained a machine learning model in Azure ML which was able to predict which employees are at risk of leaving the NHS at a given time.
We also provided some upskilling and consultation services in data science for the analytics teams in HEE, introducing some analysts to the power of no-code ML with Microsoft Azure ML.
Fast Data Science designed and trained a machine learning model in Azure ML which was able to predict which employees are at risk of leaving the NHS at a given time.
We also provided some upskilling and consultation services in data science for the analytics teams in HEE, introducing some analysts to the power of no-code ML with Microsoft Azure ML.
Results
We discovered a number of surprising factors behind employee attrition and communicated these back to management where they are being incorporated into the NHS’s future workforce strategy.
You can read more in this blog post: https://fastdatascience.com/predicting-employee-turnover/
We discovered a number of surprising factors behind employee attrition and communicated these back to management where they are being incorporated into the NHS’s future workforce strategy.
You can read more in this blog post: https://fastdatascience.com/predicting-employee-turnover/