People receiving home care all have different health and social care needs.
Although their needs are varied, clinical commissioning groups (CCGs) and local authorities need to be able to develop sustainable solutions for all.
These solutions need to include an integrated approach between both health and social care services.
Due to the lack of interoperability of the different health and social care datasets and systems, clinical commissioning groups and local authorities have limited insight into the populations they are serving and their unique health and social care needs.
This results in those decisions being made in isolation, or requiring extensive manual collaboration across organisations. This can be slow and cumbersome.
In today’s world, data is the essential ingredient to integrating siloed systems and making optimal decisions.
PIPP (Promoting Independence through Prediction and Prevention) is a public-private partnership between the City of Wolverhampton Council, the Midlands and Lancashire Commissioning Support Unit (MLCSU) and data analytics provider PredictX.
Promoting Independence through prediction and prevention
Together their mission is to use data science methodologies and AI to provide improved data-driven insight to support local authorities and health and social care providers.
One of their latest solutions includes PIPP Population Health Intelligence
Healthier individuals with no LTCs
Mental illness and epilepsy
Multiple LTCs but reduced touchpoints
Coping hypertensive patients
Heart, lungs and kidney disease
Well-off hypertensive and cancer sufferers
Talking head of someone at PredictX and then someone from the MLCSU who will give an overview of the product describing the type of data and the dashboards we use.
Using these insights, PIPP Population Health Intelligence uses machine learning models to cluster patients into unique ‘groups’ or ‘profiles.’ These groups each require different health and social care services.
Talking head with someone from Wolverhampton discussing how grouping patients leads to improved service delivery and better outcomes in their populations.
Social care services are thus optimised to provide the best care for each patient - improving patient outcomes within the population.
If you would like to learn more about PIPP and its initiatives to use data science methodologies to improve health and social care outcomes, contact us today.