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Promoting independence through prediction and prevention

A case study with the City of Wolverhampton Council Adult Services.

The City of Wolverhampton Council’s Adult Services aims to improve the commissioning and provision of health and social care using predictive analytics and machine learning.

Page contents

Background

A greater proportion of Wolverhampton’s resident population are identifying as having ‘bad’ or ‘very bad’ health - 7.2% when compared to the average population in England of 5.0% (2011 census). The Healthy Life Expectancy is also lower for males in Wolverhampton at 56.4 years compared to 63.4 years for England and 59.5 years for females compared to 64.1 years in England (Marmot Indicators).

Adult Social Care has been working with Predict X, a company that provides a platform for predictive analysis using machine learning. Over a number of years it has been developing ways to forecast demand for social care services to enable more effective service budget allocation. It's hoped this will assist in targeting interventions to help people remain independent in their own homes for longer and, ultimately, give them healthier lives as they grow older.

What the project involved

Two proof of concept projects were set up.

 

  1. System flow dashboards incorporating existing data sources from social care, health and regulatory bodies were developed. They are now used to identify opportunities to make services more efficient by improving commissioning decisions and budget allocation.
  2. The second project, funded by NHS England, looked at machine learning. The aim was to use data intelligence and predictive analytics to understand the main characteristics of ‘high-risk’ individuals. This will enable interventions to be identified that will reduce both admissions to hospital and the cost of social care packages.

Targeted commissioning

Longer independence

Focused interventions

Benefits of the predictive analytics project

Clinical staff benefit from:

  • identification of conditions which require more support from health care, such as coronary heart disease and cancer
  • better understanding of health trends
  • insights into early intervention and prevention activities

City of Wolverhampton Council benefit from:

  • the ability to better identify needs and forecast demand for services
  • enhanced service planning. 

Social care staff benefit from:

  • improved care planning
  • identifying conditions which require more support from social care
  • better understanding of health trends
  • insight into interventions which may help people to be independent for longer

Patients benefit from:

  • improved anticipation of needs to enable earlier intervention
  • improved support to remain independent for longer
  • successful joining of health and social care to identify where better integrated working can provide quicker and better outcomes

Lessons learned so far

The co-ordination of four partners required strong project management to adhere to key dates and deliver benefits. Communication and information sharing was vital; emails and teleconferences were found to be helpful as well as face to face meetings.

 

Delays in the access to health data had a knock-on effect on the overall project. Applications for access need to be made early on in the project with time built in for potential delays. 

For more information on this project, email: [email protected]

Download the full case study

Last edited: 29 September 2022 4:20 pm