The MONARCH Study
(The Map Of Need Aggregation and ResearCH Study)
Overview
The military community is a unique set of population clusters with distinctive needs that require specific health policies and interventions. Consequently, the development of evidence-based health and social care services for military veterans is imperative and can only be achieved with a comprehensive understanding of how statutory and charitable services across the UK are currently used, this is something that is presently lacking.
The MONARCH study aims to takes forward the Map of Need (MoN) ‘proof of concept’ project to create a national, unified, aggregated dataset of military charity service usage.
Whilst the MoN identified the myriad of different data flows that currently exist, there is a significant scientific need to aggregate these data flows into one dataset to provide a comprehensive, contemporary and dynamic overview of veterans’ needs in order to provide an evidence-base for the coordination of services at a national level. This project will provide a national resource of trusted data for resource planning and provision.
The Northern Hub for Veterans and Military Families Research is a multi-disciplinary research unit at Northumbria University who have established relationships with all data holders (service charities), have been working with this pilot data for 5 years, and undertaken considerable methodological preparation to achieve the outcomes of the MONARCH study over the past 12 months.
Background
The military community makes up almost 8% of the UK population and many, including their families, will require support at some point across their lifespan from a range of different services. Before 2017, there was a poor understanding of how such services were used.
Government departments, health services and the various service charities are required to understand what needs are being met/unmet, and how veterans are using services. Although the MoN project has successfully developed a ‘proof of concept’ to progress and improve accessibility to the data, it is imperative that this concept is put into practice to visualise data flows, provide a dynamic decision-making tool for policymakers, and create a comprehensive trusted dataset for scientific investigation. Our proposed project will implement this concept and make it a reality.
The digitisation of healthcare services is a major resource to inform policy-makers. In order to properly transform data into useful real-time information for healthcare and social services planning, the availability of data and the establishment of a data flow presents new issues to address, such as big data management. The MoN 'proof of concept' project identified the many current different data flows that exist, especially when considering veteran services in the UK. However, there is a need to aggregate these data flows into one dataset in order to provide an evidence-base for the coordination of services at a national level.
Such an aggregated dataset, with specific summary indices and clear early-warning thresholds are imperative for effective service planning. The aggregated dataset will provide an evidence-base for resource allocation and service development, provide a comprehensive understanding of what and where services are used and in what numbers. In addition, understanding service usage is a fundamental step in developing proactive services and overcoming what is currently a predominantly reactive system, which generally relies on the veteran (or family member) seeking help. Proactive data management, early identification of needs, and preventative approaches are not only better for the individual but are also more cost-effective at the public health level and more beneficial for society at a holistic level.
This study is in line with HM Governments policy, Transforming for a digital future: 2022 to 2025 roadmap for digital and data. The MONARCH study will apply the proof of concept developed by the MoN project and create an aggregated dataset of military charity service usage as well as creating a national resource for service planners to engage with that data. We will remove static reporting and lengthy reports and build a fully digital interactive resource where users can interact with the anonymised data in real time, obtaining the information that is important to their needs.
Method
To apply the knowledge and expertise developed in the MoN project, the first step will be to apply the unique individual identifier that has been developed to anonymise individual data with a unique ID code. This provides a means of anonymously identifying individual data, which is imperative in determining the number of problems an individual is receiving help for across different organisations. Having the data presented in this way enables the measurement of phenomena such as complexity of need and, in the future, the cost of need.
Once the aggregated dataset is built we will undertake preliminary analysis to test assumptions from the MoN concept project. The process of aggregation will allow us to identify core variables to orientate policy- and decision-makers, but equally important, to help reduce the number of variables in the datasets to provide more meaningful information which will produce summary scores.
Working with our sector partners, we will collapse factors in preparation for the creation of a second aggregated dataset which could be used in a visualisation software platform. A visual dashboard will summarise the current situation and the populations’ main characteristics and allow for the anonymised aggregated dataset to be searched, from which reports and information can be produced.
Furthermore, we would be able to implement specific early-warning indicators to proactively detect situations that occur in geographic areas (via generic postal codes) across the UK. Our unique algorithm will identify a ‘trigger value’ for each area of need and will relate it to the specific population characteristics and the broad geographical area. This approach will help identify and inform on specific clusters of populations and areas to specifically focus on.
