Effective use of data and intelligence across the health and care system can empower decision making and improve patient outcomes. The safe, appropriate, and proportionate sharing of data is essential in order to provide direct patient care and in enabling intelligence provision for effective service planning and delivery. Effective use of data and intelligence improves timeliness and relevance of information in clinical and professional systems, helping to keep staff, patients, and service users safe.

To support the system in this area we have developed two themes for the purpose of this strategy.

Theme 1: Further develop the joint data and information systems and analytical capability across the Lincolnshire health and care sector to effectively deliver services.

Theme 2: Use our shared data analytical capabilities to improve how we plan, develop, and transform services to improve health outcomes for our population.

In Lincolnshire, we have an advanced, person level, linked dataset bringing together information from a range of partner organisations delivering health and care services.

We will continue to improve data sources and provide intelligence that helps us focus on people in our communities most in need of health and care support, to understand what works, what does not, for whom, and what we might do to improve services.

We will use data, analytics, and evidence to inform the planning and delivery of health and care services with a population health management approach and, in addition, explore how we can adapt these techniques to suit service needs – acting sooner to intervene, prevent poor health outcomes and reduce inequalities.

As a system we are committed to adopting evidence-based decision making into the way we plan and deliver our health and care services.  By investing in the technical infrastructure and capability we have available, we will be ensuring effective processes are in place to automate manual time-consuming processes safely and securely, where it is feasible and cost effective to do so. This will increase performance and release capacity for analytical staff so they can add value to wider system models by focusing on improving the quality and understanding of data sources to help improve the health of the population. The way to do this will be to develop a shared vision for the role of intelligence in decision making, to agree the skills required to improve decision quality, and to support workforce development to upskill analysts and others on this topic.

This will support all partners across the system to:

• target our collective, finite resources to best effect and, where possible, release analytical capacity through infrastructure improvements.
• apply robust information governance to keep our information assets safe and secure.
• maximise the ‘information’ and ‘intelligence’ we achieve from our datasets by exploring the use of data science principles including artificial intelligence.
• ensure that we maximise the value of the intelligence we produce by sharing this in readily available ways with those who need it, including through our publicly accessible Joint Strategic Needs Assessment and the Lincolnshire Health Intelligence Hub website.
• provide information to front line staff in a more timely and effective way to support them to make good quality decisions with regard to the care and support they provide.
• produce actionable insights to inform Population Health Management, Health Inequalities and Personalisation and support partners (e.g. Primary Care Networks) to use the linked dataset to understand needs and disparities across cohorts of the population so we know where, and how, to focus our efforts.
• to continue to improve the quality, understanding and sources of our data to increase our analytical capabilities and better inform decision making.

We will utilise a population health management methodology, to support us in enabling people to improve their health and wellbeing whilst reducing pressure on services. Ensuring the system embeds an ongoing cycle of intelligence generation through facilitated discussion with Multi-Disciplinary Teams. This will enable opportunity identification, population understanding, cohort selection, intervention development and the evaluation of outcomes.

This will support all partners across the system to:

• Understand population needs and future demands to inform service planning, commissioning, and workforce strategies.
• Evaluate the effectiveness of treatments, pathways and prevention activities for the population, and for certain populations groups, informing provision and allowing better targeting of services and interventions.
• Design appropriate models for new services to target the right conditions and risks, in the right way, at the right time.
• Identify those whose needs are not being met and those at rising risk of ill-health so that we can intervene earlier, provide services to prevent illness, avoid escalation of conditions, reduce costs and improve patient outcomes.
• Understand the value of prevention and the role of the wider determinants of health to inform our actions to address these factors and reduce health inequalities.
• Evaluate services and pilot initiatives, expanding those proven to be successful, to enable improved health and care delivery and outcomes.
• Ensure our data is further enhanced by broader intelligence and insights from published evidence, expert opinion, communities, and people. This will provide a holistic evidence base to inform strategic plans and decision making.