The HICM is designed to support local health and social care system leaders to work together to embed and improve data-driven decision making at all levels, resulting in the delivery of better neighbourhood health outcomes.
Executive summary
The HICM is designed to support local health and social care system leaders to work together to embed and improve data-driven decision making at all levels, resulting in the delivery of better neighbourhood health outcomes.
What is data driven decision making?
Data driven decision making is using facts, metrics, data and feedback to guide decisions at individual/patient, tactical and strategic level that are aligned with Integrated Care System goals. When systems realise the full value of their data, it means that staff from leadership to frontline are empowered to make better decisions every day with data.
Furthermore, it will allow systems to identify, plan, measure and track benefits to ensure that they are being achieved and sustained for individuals and the system.
The solution comes from having a high quality shared data set, and tools that help teams action meaningful change. If you don’t have accurate data that’s visible to everyone in real time, you’ll fall short. But if you’ve got data you can trust, great things are possible...Now, thanks to trusted, real-time data – and incredible collaboration across our ICS – we’ve halved those costs and have the latitude to go further. It shows that by being scrupulous around data – and having a fantastic system to record it on – you can get to a better place.”
- Mark Simmonds, Deputy Medical Director, Nottingham University Hospital
National context
Government and national partner expectations of integrated health and social care systems are to deliver the three big shifts: from hospital to community; from analogue to digital; and from sickness to prevention, against a backdrop of severe resource constraints, whilst empowering individuals and health and care staff.
Policy and guidance
- BCF policy framework 2025 to 2026 (DHSC, MHCLG 2025)
- Neighbourhood health guidelines 2025/26 (NHS England)
- Building an integrated care system intelligence function: purpose and development (NHS England)
Purpose and development
The HICM sets out a series of high impact actions to support systems to work together to develop the data and insights that can then be used for decision making and delivering benefits locally.
Development of the HICM has been sector-led a partnership between the BCF Support Programme and those working in health and social care systems to deliver and improve frontline services. Colleagues have come together to generously share their experiences, contribute best practice, and review, challenge and iterate the model as it comes together to ensure that the content for the model is usable and fit for purpose.
The model is evidence-based, and wherever possible, examples are included of successful applications that have led to improved outcomes for people, more effective operations and greater efficiency.
The work was led by an expert steering group, involving national partners as well as colleagues working in local health and social care systems, and is aligned with national policy.
Challenges
The High Impact Changes have been developed to support systems to overcome the following challenges:
- Data silos - where system partners are storing and managing their data independently, leading to fragmented information that is difficult to integrate and analyse. This stops collaboration and results in missed opportunities.
- Lack of data quality - where incomplete, inaccurate or outdated, data can undermine decision-making and operational efficiency.
- Insufficient data skills - where a lack of data literacy amongst staff and a lack of employees who can analyse and interpret data effectively limits the system’s ability to leverage data for effective decision making.
- Inadequate technology and infrastructure - where old, legacy technology lacks the scalability and flexibility needed to manipulate, manage and analyse large datasets, limiting a system’s capability to leverage data for deeper insights.
- Lack of clear, well-defined integrated data strategy – where a lack of a data strategy, aligned to integrated care system goals, impedes implementation of effective data initiatives.
High Impact changes
1. Co-produce a shared vision, setting out how data and intelligence can support this.
High Impact Change 1: Co-design a shared vision with partners that outlines how data and intelligence can support this decision making across all partners.
2. Bring the right people from across the system together, incorporating service and technical expertise to deliver the vision and support improvement
High Impact Change 2: Establish system-wide intelligence function and communication channels for collaborative, multi-disciplinary working to deliver the vision.
3. Identify and agree key data to record and find methods to make recording it easy and standardised
High Impact Change 3: It is important that leaders and staff identify and agree the relevant data to record for decision-making and make recording part of their daily tasks using digital tools.
4. Decide key data to share across system partners and overcome obstacles to sharing it
High Impact Change 4: Unlock any remaining barriers to sharing data by encouraging a culture where services are responsible for sharing data, have a mature interpretation of the relevant data rules and prioritise myth busting any potential blockers.
5. Invest in the right tools and training to develop effective insights
High Impact Change 5: Staff across all partners need to feel confident in gaining insights from data, using easy-to-use visualisation tools for decision-making, reinforced with training where required.
6. Embed insights into everyday processes and decision-making, and monitor the results of these decisions
High Impact Change 6: Staff across all partners will need to understand where insights can support decision-making and use them to support care and/or service improvement.
7. Embrace AI to improve system-wide decision-making
High Impact Change 7: By analysing large volumes of data across the system, AI can help spot issues earlier, predict future needs, and personalise support.
How to use
Each High Impact Change area is structured in the following way:
- Description: to explain what the change entails.
- Specific actions: to be undertaken to ensure success and help embed the changes.
- Ambition level actions: to support self-assessment and enable systems to understand their progress.
- Case studies: to provide examples and evidence.
For further information, please contact: [email protected]