We focus on four complex health issues more prevalent in urban areas
With the Social Progress Imperative, we've developed the first neighbourhood level, health-focused social progress index of its kind.
With Wellcome Trust
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What being a data-led organisation means to us and how we use data to guide our funding and strategic decisions.
We aspire to be a data-led organisation. In our context, this means that data plays a critical role shaping our strategy, focusing our efforts on the most important issues, informing our operational decisions, and feeding into continuous learning.
Additionally, this means that we use data responsibly. Being aware of bias, in the information and in ourselves, and having processes in place to avoid doing harm is paramount to our practice and a condition to successfully using innovative tools and technologies.
We know urban health issues are complex and impacted by many factors. As a result, we combine our use of quantitative datasets with qualitative methods and lived experience to better understand our place and explore the connections between people’s health and their context.
With the Social Progress Imperative, we’ve created a set of metrics to assess the social progress of our boroughs of Lambeth and Southwark.
The Urban Health Index provides information on 68 neighbourhoods in Lambeth and Southwark and includes the most recent data available. We capture data on 42 indicators relating to basic human needs, foundations of wellbeing and opportunity, viewable as an interactive scorecard for different neighbourhoods.
Explore the ‘Urban Health Index’
We use a range of platforms to visualise our data, including Tableau. Our Tableau Public profile showcases some of our data work and makes this analysis publicly available so others can share our insights. We have also featured on Tableau’s website discussing how we use Tableau (in our old brand name of Guy’s and St Thomas’ Charity).
Explore our Tableau Public profile
Local Insight is a tool that shows neighbourhood-level data. This includes services available – such as schools, GP practices, care homes – as well as demographic and health data. We’ve used Local Insight to explore this data for Lambeth and Southwark.
Visit the Local Insight map
By describing the current situation, we can focus our effort on groups that are most likely to have poorer health outcomes. For example, with the Social Progress Imperative, we’ve created a set of metrics to assess the social progress of our boroughs of Lambeth and Southwark. The result of this partnership is the Urban Health Index.
Sometimes, correlations are not enough to understand how to best impact a complex issue. More comprehensive analyses, such as system mapping are useful to uncover the direct and indirect causes of poor health outcomes. Diagnostic analysis helps us tackle the right part of a complex issue to maximise our impact.
Understanding the current mechanics at play can help us model possible future outcomes. Typical questions include modelling the propagation of information or estimating the impact of new regulations on future health outcomes. For example, using the prevalence of known risk factors we can identify areas where people are more at risk of poor health outcomes in the future.
By modelling the likely effects of an intervention in the years to come, we can inform our current thinking. For example, we commissioned Health Lumen to model the health and economic impacts of both NO2 and PM2.5 exposure under different scenarios.
To build the most exhaustive picture of our place, we need to tap into a broad mix of data. We achieve this both through accessing public data, collecting our own and partnering with organisations.
Open-source data is a fantastic resource. We rely on sources that are available nationally and offer the granularity we need to understand our place in detail:
Sometimes, the data that is available is not enough for us to validate some of the hypotheses that underpin our programmatic work. We then commission collection to specifically plug our knowledge gap. This could be a survey or collecting data from online sources like Twitter to analyse sentiments about a topic or understand how a topic is being discussed online.
Partnering with organisations that share our vision is a great way to enrich both parties’ knowledge bases. In the past, this has allowed us to access and explore data that we otherwise would not have been able to.
We have partnered with organisations to help them develop their product in a way that is also furthering our mission, funded a Data Scientist to be seconded at the Health Foundation to produce insights that respond to both organisations’ research needs or used a partner’s methodology to apply it to our data.
Our approach to partnership is innovative and flexible to allow for the right insights to be surfaced to shape great programmes and policy influencing work.
It is our responsibility as an organisation to ensure our partnerships and the data we use are not putting us or the people we serve at risk. To do this, we have data analysis principles, so that our analysts, consultants and partners have a shared understanding of our approach. We also have a Data Advisory Group that provides us with an external perspective on our work. Our work on data ethics is not set in stone, it’s an evolving toolkit we build on and share to inspire others to use data responsibly.
Our insights are key to shaping our strategies and operational decisions. We aim to support others to use our products to inform their own organisational decisions.
Our Urban Health Index, developed with the Social Progress Imperative, is a great way to move beyond economic indicators as a proxy for health outcomes. We hope that it can inspire more people to use data to focus their interventions.
Get in touch with our Data Partnerships Manager to find out more and find out more about the team.
By 2050, nearly 70% of the world’s population will live in cities. We explore what distinct health challenges and opportunities urban areas have.
We believe we can improve global health by focusing on cities.
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