The shielding programme was a swift government wide response to identify and protect clinically extremely vulnerable (CEV) people against COVID-19.
Our recent report on Protecting and supporting the clinically extremely vulnerable during lockdown, shows how government quickly recognised the need to provide food, medicines and basic care to those CEV people shielding. This had to be pulled together rapidly as there were no detailed contingency plans.
But there was a problem. In order to do this, government was faced with the urgent task of identifying the people who needed support based on existing, disparate data sources.
Difficulties in extracting and combining data
The urgency of this exercise was recognised by all involved, but difficulties in extracting, matching and validating data from across many different systems meant that it took time for people to be identified as CEV.
At the start of the pandemic, there was no mechanism to allow a fast ‘sweep’ across all patients to identify, in real time, those who fell within a defined clinical category.
It was a major challenge to identify and communicate with 1.3 million people by extracting usable data from a myriad of different NHS and GP IT systems all holding data differently.
This lack of joined-up data systems meant NHS Digital had to undertake the task of accessing and extracting GP patient data, stored in different ways in each practice and holding specific details about people’s medical conditions to merge with their own databases. It took a huge effort by the team to complete this task in three weeks.
Data issues were not resolved by the time of the second lockdown
Government had identified systems were not capable of ‘speaking’ to each other across hospital, primary care, specialist and adult social care services following the first iteration of shielding (March – August 2020), and sought to apply them to the second lockdown towards the end of 2020. However, our report highlighted resolving the data issues was not an area where significant progress had been or could be made.
This reflects the wider issues of data across government
These challenges are examples of broader issues that we have previously highlighted in our report on Challenges in using data across government. People often talk about better use of data as if this is a simple undertaking. But there are significant blockers and constraints that require sustained effort to overcome, which apply to all areas of government trying to use and share data other than for the single purpose it was originally created for.
The basic issues are widely known and acknowledged:
- Huge variability in the quality and format of data across government organisations
- Lack of standardisation within departmental families and across organisational boundaries making it difficult for systems to interoperate
- The extent of legacy IT systems across government further compounding the difficulties
- Ownership and accountability aren’t easily agreed where a shared dataset of personal data is brought together and has equal value to different services.
It’s unclear to us how calls to establish and enforce data standards are going to work in practice if existing systems can’t be modified to support them and there is no firm timetable, road map or funding commitment for replacing them.
In our report Digital transformation in the NHS, we reported that 22% of trusts did not consider that their digital records were reliable, based on a self-assessment undertaken in 2017. The average replacement cycle for a patient records system is something in the region of once every 15 years so this change isn’t going to happen overnight.
Our aim is to support government in tackling these issues, and not to be critical of past failings, because we recognise that it is hard. We set out a number of recommendations in our data report and they are summarised in our accompanying data blog.
Some are aimed at the centre of government and others are steps that individual organisations can take. Our cross-government recommendations were primarily around accountabilities, governance, funding and developing rules and common ways of doing things.
Our recommendations for individual organisations are:
- Put in place governance for data, including improving the executive team’s understanding of the issues associated with the underlying data and the benefits of improving that data
- Set out data requirements in business cases. This should include an assessment of the current state of the data, and the improvements or new data that are necessary. These assessments should have an explicit consideration of ethics and safe use
- Implement guidance for front-line staff for handling data, including standardisation, data ethics and quality.
Organisations that hold a cohesive view of their citizen/patient data must address this issue in a managed and incremental way, rather than having to resort to one-off costly exercises which have to be repeated when the next need arises. This will require sustained effort and perseverance.
Unfortunately, there are no easy shortcuts, but with a will to put in the necessary effort progress can be made one step at a time.