This project is investigating how population health management approaches can be applied to diabetes prevention pathways.
Background
Central to the development of local Integrated Care System (ICS), population health management (PHM) is an approach that uses linked data to plan and deliver care that achieves maximum impact on the health and wellbeing of a population. Historical and current data is used to understand the drivers of poor health outcomes in different population groups, to understand current health and care needs, and to predict future ones. This detailed local population insight is in turn used to design new proactive models of care, or target existing ones, to improve health and wellbeing today and in the future. PMH has a strong focus on prevention and the wider determinants of health as well as on the involvement of communities and organizations with a mandate to improve population health.
To build the evidence base for PHM, regional PHM colleagues hosted by East Suffolk and North Essex Foundation Trust, within the Suffolk and North East Essex (SNEE) ICS, have developed this discrete project focusing on the prevention and management of diabetes.
Project Activity
Population health management (PHM) is an approach using linked data to plan and deliver care to achieve maximum impact on the health and wellbeing of a population. It is a critical building block for local Integrated Care System (ICS) development to support improving local population health outcomes for all. Historical and current data is used to understand what factors are driving poor health outcomes in different population groups to support understanding of current health and care needs, predict future ones, and identify groups at increased risk of worse health outcomes. This in turn is then used to inform designing new proactive models of care or target existing models to improve health and wellbeing today as well as in the future, with a strong focus on prevention, involvement of communities and organizations working on improving population health and addressing the wider determinants of health.
Increasing availability and timeliness of linked population health data across organisations provides an opportunity to provide more detailed local population insight. Within Suffolk and North East Essex (SNEE) ICS, addressing diabetes and supporting individuals to have access to the best possible care is a key long-term ambition and priority. To support development of the evidence base around PHM, regional PHM colleagues hosted by East Suffolk and North Essex Foundation Trust within SNEE ICS will undertake a discrete project starting in 2021/22 to apply a PHM approach to the prevention and management of diabetes in SNEE and determine the impact of the approach taken.
To highlight priority areas to focus on, statistical descriptive cross-sectional analysis is being carried out with available aggregate-level routinely collected and nationally reported data and indicators across the diabetes prevention and management pathway by (where information is available) locality, sociodemographic characteristics and time. This includes risk factors for type 2 diabetes, uptake of the NHS diabetes prevention programme, prevalence of diabetes, uptake of structured education, completion of treatment and care processes, and complications resulting in secondary care attendance. This analysis will be used to provide insight on the approach to reporting and monitoring health inequalities to support addressing them within the ICS.
In addition to identifying priority areas, mapping out the insight that can be currently obtained through routinely collected data identifies what population health questions related to diabetes prevention and management can and cannot be answered currently. This will provide recommendations to a) identify what questions can be answered with available data to support its use and insight implementation, and b) identify what questions can only be answered with additional data/linked data to inform local priorities in PHM analysis.
An area of focus is health complications resulting from diabetes which can include lower limb amputations and chronic kidney disease. With locally available linked datasets, multivariable analysis using PHM approaches will be carried out to identify key attributes associated with developing health complications. This can be used to then review existing local care pathways, identify any changes to implement which may support reducing the risk, implement these changes, and evaluate.
Formative and summative reviews will be carried out and findings written up and disseminated.
Who is involved?
- Principal Investigator: Helen Green, Office for Health Improvement and Disparities
- Louise Lafortune, University of Cambridge
Contact
Helen Green, h.green11@nhs.net
