Population Health Management is an important tool that is increasingly being used by healthcare providers to manage and control the escalating costs. The crux of Population Health Management is to use data to improve health outcomes. Tracking, monitoring and benchmarking are the three bastions of Population Health Management, aimed at improving clinical and health outcomes while managing and reducing cost.
In this solution, we will be leveraging the clinical and socio-economic in-patient data generated by hospitals for population health reporting. As an example of a machine learning application for population health management, a model is utilised to predict length of hospital stay. It is geared towards hospitals and healthcare providers to manage and control healthcare expenditure through disease prevention and management. You can learn about the data used and the length of hospital stay model in the manual deployment guide for the solution. Hospitals can use these results to optimise care management systems and focus their clinical resources on patients with more urgent needs. Understanding the communities they serve through population health reporting can help hospitals transition from fee-for-service payments to value-based care while reducing costs and providing better care.