• Jessica Booth, Director |
6 min read

To drive up the delivery and quality of the public services on which citizens rely, it is key to have reliable, joined-up data. In this way, different parts of the public sector can access and share essential information that generates better insights, drives efficiency and ultimately improves citizens’ lives.

If we could integrate data from across society, including health and social care, education, policing, demographics, transport, weather and housing – imagine the benefits that could be derived.

Best practice building blocks

Is this an impossible dream? I don’t think so. It may be hard to achieve, but the building blocks are there. It is a case of embedding best practice, adhering to a number of key principles, and driving consistency across channels and touchpoints.

Firstly – best practice. There is a wealth of this to follow and build upon in the UK, including:

  • The Data Management Association (DAMA) has an established Data Strategy Framework of which Data Integration and Interoperability is a key component.
  • There is a Data Sharing Governance Framework, part of the National Data Strategy, backed up by the FAIR principles that should be applied to government data – findable, accessible, interoperable, reusable.
  • The Central Digital and Data Office (CDDO) has set up a Data Marketplace to share government data across departments.
  • The Integrated Data Service (IDS) is a new government-wide initiative, established by the Office for National Statistics (ONS), which will create a step change in the way data about our society and economy are made available for vital research and decision making.

There are a number of technical best practices and accelerators that can also be harnessed. APIs (Application Programming Interfaces) allow different software programs to talk to each other and share data. In the healthcare domain, FHIR (Fast Healthcare Interoperability Resources) is a global standard for passing healthcare data between systems. Meanwhile rail interoperability and standards, published by DfT ten years ago, supports safe and technical compatibility of trains and infrastructure. Similarly, Open Standards principles are important government standards for integration – the gov.uk website, for example, is based on these.

To achieve these enhancements, infrastructure is of course an important factor. Enterprise data infrastructure usually has a data lake or warehouse at its core, with ETL processes (extract, transform, load) helping migrate data from legacy systems to the ideal infrastructure, enabling interoperability and integration between different data types. Automation and AI are bringing new possibilities as well, including making the ETL process faster, easier, and more accurate. For example, AI can support the extraction phase by automating the identification and retrieval of data from many sources. AI algorithms can apply patterns or rules to transform data into a consistent, usable format, and can improve data quality in the process. AI tools can support the load process too, by automatically mapping transformed data to a target system. In an international example, this type of innovation has been applied to integrate legacy legal data of different types from many regional courts into one secure cloud system, and can similarly be applied throughout the public sector.

Early wins

There are some excellent live examples of data interoperability in action. For example, the Bus Open Data Service (BODS) which sees over 450 bus operators supplying high quality, standardised, accurate data for c. 8,500 combined local bus services around England. This required a modern open source infrastructure technology platform to collect and openly share national bus data, including information from local authorities (such as disruptions messaging to the bus service), and supports digital transformation. The BODS service integrates timetables, fares and real-time location data (GPS data) for around 32,300 buses and has enabled the creation of new passenger and operator apps that improve the bus passenger experience across 4.5 billion annual journeys.

Another example of integration, from the healthcare domain, is Patients Know Best (PKB). PKB health records fully integrate into the NHS App and Login, allowing patients with a PKB health record to directly access their combined dataset from within the NHS App interface. The PKB platform includes health information generated from GPs, hospitals, community and mental health services as well as data collected directly from the patient, including any connected wearable devices. This integration enables patients to access their care plans, exchange information with health professionals, track and monitor symptoms, and share information with carers and other professionals. PKB operates under FHIR (Fast Healthcare Interoperability Resources) APIs using CareConnect across the NHS ecosystem. These nationally-defined interoperability standards mean that PKB APIs easily integrate across NHS trusts and other organisations. PKB supports 20 languages, and is used at more than 60 hospitals around the world. For thousands of people in the UK it is modernising the way they interact with the NHS, reducing unnecessary admissions to hospital and trips to the doctor, and empowering them with health information at their fingertips.

Embedding the approach

If the building blocks are there, and some success stories are emerging, what needs to happen to embed best practice on a much wider and more pervasive basis?

Firstly, each organisation within the public sector needs to ensure that it is following the data standards and rules that have been created. In practice, this requires:

  • A real commitment to doing so, which will come from understanding the many benefits to be gained through specific use cases.
  • A clear data governance operating model for the organisation including agreed owners, roles and responsibilities.
  • Buy-in and funding from leadership, and understanding of the change and accountability for data processes.
  • Data quality needs to be monitored and managed, including more automated tools for data entry.

Supporting and engaging data users

Another key aspect is the users of data – in other words, staff. Organisations can’t expect change and uplift without supporting the staff who collate, use, monitor and manage data. So there needs to be training for staff in continuous improvement approaches, including agile methods. There also needs to be incentivisation to integrate data. Often the end user benefiting from the service is not the person needing to invest in integration efforts. This is often why cross-governmental projects fail. It’s essential to make people realise that if everyone makes the effort to integrate data, they will eventually benefit themselves at some point when someone else’s data is there for them to use. It’s about recognising that everyone is ultimately part of one larger ecosystem and improving for one, improves for all.

Communication is also critical. Communicating clearly and regularly to staff about the importance of data best practices creates a drum beat and shows them why it matters. Understanding builds engagement. User forums can be highly effective too; establishing communities of practice where users share thoughts, tips and guidance so that the topic becomes much more real.

Carrying the momentum forward

There is a long way to go – but I am encouraged by the foundations that have been laid and the early wins we are already seeing. If organisations across the public sector can proactively take up the baton, embedding best practice internally and collaborating with others, we could see great strides being made in the coming years – with citizens benefiting from more efficient, unified and user-friendly services as a result.