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12 May 2023
by Justin Hassall

The Importance of Ensuring Quality and Trust in Data for Healthcare Settings (Guest blog by Informed Solutions)

Guest blog by Justin Hassall, Transformation Director at Informed Solutions

Use of data was at the forefront of the world’s fight against a two-year global pandemic. The advances in data analytics seen during COVID-19 showed the potential for data platforms to address long-term challenges vital to the future of health and social care.

The scale of the opportunity (and the challenge) can be seen in Ben Goldacre’s report, which set out 185 wide-ranging recommendations for better use of digital technology and data in healthcare settings. This report flags critical data privacy and inclusion issues, and although there are huge opportunities for better use of data, there is also an urgent need to be careful with the use of patient data. This must be guided by ethical frameworks for the provision of access to personal information, as well as systems designed to reduce inequality of healthcare access and provision.

Accelerating Care Delivery – For All

The need for acceleration of care delivery is evolving across different care settings beyond that of the hospital, driven by a public demand for access to care in environments most appropriate to individuals and their specific needs. 

While some care providers and local authorities are trailblazers in the use of data and technology, social care still lags behind. Improving the quality of data is of critical importance, as the title of the Department of Health and Social Care 2022 strategy states: Data Saves Lives.

Underpinning any transition to an intelligence-led health service is the need for the exchange of high-quality data, using information transferred within and between Integrated Care Systems (ICSs) to make vital decisions about what care is delivered and where.

Building Confidence and Trust

To ensure high data quality, public confidence in sharing and providing access to personal information must be increased. This trust will come from building confidence in the way their data is used so that it streamlines and accelerates access to the care and treatment they need. If the data is not accurate or ‘decision grade’, then its ability to do this is greatly reduced.

Putting the patient at the centre of the data collection and accuracy challenge is important, but this must be done efficiently. In November 2020, the Department of Health and Social Care published a report on excessive bureaucracy in the health and social care system, which evidenced data collection directly impacting the provision of care. While not disputing the importance of high-quality data, this also serves as a warning that data collection must be efficiently designed into processes so as not to damage the care it seeks to improve.

The mapping of demographics and housing has enabled the delivery of care where it is most needed, building models to inform the structure and size of cohorts, such as to provide vaccinations or supply medicines to mitigate localised outbreaks of disease.

The global health care sector was already using new technologies and processes to extend care delivery outside the hospital setting when COVID-19 forced providers to transform operations and adopt virtual consultations and remote monitoring.

This enforced shift in patient engagement and care delivery has brought many opportunities and benefits, not least the potential to deliver physical and virtual care in a meaningful and integrated way that delivers better patient experiences and outcomes.

The Integration Key

To make this vision an effective reality, the NHS and the whole supplier community must provide the integration, collaboration, and information sharing needed to serve the needs of a growing body of patients that require care in remote settings. This care will be delivered by multi-disciplinary teams collaborating remotely to deliver a whole system approach.

With existing levels of fragmentation and divergence across the NHS, interoperability remains a fundamental building block for new digitally enabled integrated care services.  A truly interoperable ecosystem will provide a unified infrastructure that uses technical standards, policies, and protocols to enable seamless capture and utilisation of health information, with appropriate controls to ensure effective use. Alongside this, the reshaping of legacy systems with platforms that talk to each other, and work better together will be used to more effectively access and share data.

This ecosystem must also better meet the challenge of sharing unstructured data, for example by employing Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) techniques to discover and provide relevant information at the point of use.  However, to meet this challenge the development of new data science models must come together with an improvement of the quality of data sets to account for diversity and equality.

Making it Happen

As a two-time Queens Award innovation winner for our ability to accelerate and de-risk digital business change, we see several solutions to the challenge of data quality across the NHS, including addressing data validation and support for the cleansing, matching and validation of address data. There is the potential to use ML to improve demographics data quality, leading to better management of data quality streams.

The acceleration of care delivery, evolving across different care settings, is being driven by the demand for access to care in environments most appropriate to individuals and their needs.  Hospitals and social care without walls – for everyone.  Quality, decision grade data is the key to making this promise a reality.


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Authors

Justin Hassall

Justin Hassall

Transformation Director, Informed Solutions