Public Health England was created from a large number of organisations and we inherited a lot of data tools and profiles, many of which are accessible via our data gateway. The number of resources by broad category is shown in the graph below.
(click on any image to enlarge)
With over 110 tools and data profiles available the challenge for us is to try and improve the accessibility of our data, rationalise the number of tools and make to them easier to use for our users and stakeholders.
We're trying to do this by consolidating our data, converging our technology and improving consistency in accordance with PHE's knowledge strategy.
Given that most of our outputs are web based we are developing a digital health intelligence programme (DHIP) to help us with this challenge. An example is the Fingertips Tool. This is a platform for managing indicators, creating profiles, and visualising data on the web.
It's used to create the public health outcome framework data tool, and the healthier lives application. It also underpins Health profiles, the mental health intelligence network tools, tobacco control profiles, the NCMP Data tool, NHS Health Check, National General Practice Profiles and the children and young people’s benchmarking tool among others.
These tools are proving popular – daily web traffic (pageviews) over the last month across the tools is shown below.
A feature of the Fingertips tool is that it allows users to enter a search term and it will automatically create a data profile and the word cloud below shows the top 50 search terms people have been looking for over the last 10 days. There have been more than 1000 searches.
The cloud shows the popularity of “alcohol” and “obesity” as search terms and that “dementia” is also popular. However there are currently very few indicators relating to dementia in the database. This kind of intelligence can guide us on how to populate the database and where indicator work is required.
Finally - moving away from PHE data tools - in case you haven’t seen it, this visualisation (displayed below) tracking the Ebola outbreak in West Africa is exemplary. Created by Ramon Martinez and updated weekly, it shows the geographical extent of the outbreak, cumulative counts by country and case fatality rates and can be “rolled back” to show how Ebola has unfolded.
Encouragingly, the latest data (as I write in mid-November) appears to show a reduction in the exponential rate of acquisition of new cases in both Liberia and Sierra Leone, and a reduction in case fatality.