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Identifying the role of Digital and IT in the safety of Healthcare

Safe People

Organisation name

NHSE/I Transformation Directorate

Organisation sector

Government Agency (Health and Adult Social Care)

Applicant name(s)

Kelsey Flott

Funders/ Sponsors

Erik Mayer

DEA accredited researcher?

Unknown

Sub-licence arrangements (if any)?

No

Safe Projects

Project ID

NIBDAPC_2022_0013

Lay summary

Patient safety is a national priority and an important part of any quality health system. The National Patient Safety Strategy explains that improving safety will save lives and save costs. Improving safety across the whole NHS, however, is a challenging and long term task that requires collaboration between national organisations, local healthcare providers and patients. Improving safety also requires us to measure safety: we cannot improve what we cannot measure. This is why we need to use patient safety data like incident reporting, complaints, and other forms of patient and staff reported feedback to understand where the safety issues are and identify areas for improvement. Specifically in this work we are concerned with the digital aspect of patient safety. Following the pandemic, the increase in the use of digital technologies across the health service has been extreme. Now it is much more common for any patient to use a digital technology to interact with the health service, whether it is in booking their appointment, having a virtual consultation or simply accessing their records. There is also a growing use of technologies for healthcare staff who use digital systems to care for patients, record data and manage things like medicines, imaging, care plans and more operational things like their own workflow. All of these technologies can help in building safer systems, but they also come with risks to safety. In addition to understanding what the most prevalent safety issues are, we need to know whether digital systems are contributing to safety risks and also where they could be used to support safety improvements. In order to address these issues, we plan to work between NHS England (NHSX), Imperial College Healthcare NHS Trust and NHS Resolution to analyse patient and staff reported data about safety. It is critical to ensure data comes from both staff and patient perspectives. We will also be working with patients to ensure we are using patient safety data appropriately and properly considering patient perspectives.

Public benefit statement

The research question is a priority area, and could provide the following benefits to patients and the public: Knowledge creation and intelligence generation: In the first instance, this project is intended as a fact finding exercise, the results of which may help to guide future research, policy, and service evaluation. There are currently a range of data sets (including but not limited to incident reporting data, Friends & Family Test data, complaints data, and claims data), each of which are of great instructive value, but currently operate in silos with little coordination between them. Triangulating these myriad datasets and analysing them for patient safety and Health IT insights will improve the quality of care provided by preempting, preventing, and mitigating adverse events. A root cause analysis of key patient safety incidents may help to catalyse quality improvement projects (QIPs) in a manner that is systematic and needs-driven, rather than the piecemeal approach to QI we see today. Blueprinting and scaling learning: We recognise the importance of QI initiatives that are sustainable and scalable throughout the healthcare system, instead of being patchy and anecdotal. As such, we are keen to use Imperial College Healthcare NHS Trust as the pilot site, through which to refine methodologies and blueprint best practice to take elsewhere. We acknowledge that Imperial is uniquely positioned to participate in this project by virtue of its data science resource power and expertise, and may also experience patient safety and Health IT incidents that are unique to the local health economy. To that end, whilst the methodologies used here cannot simply be transplanted elsewhere, this project, and the blueprint/approach used herein, could certainly be of interest to the wider Trust and ICS community. Patient outcomes: Using the insights generated and delivering targeted QI initiatives may have the potential to reduce the burden of unsafe care, from an individual patient, organisational, and health system wide perspective. By identifying and proactively implementing mitigations in the highest priority areas, adverse patient outcomes (such as deteriorations in care and avoidable escalation to more specialised units, prolonged lengths of stay, and failed discharges and frequent readmissions) can be reduced. Financial benefits: In the longer term, improved clinical outcomes stand to also benefit the organisation and health system as a whole. Cost savings from frequent readmissions and delayed discharges, as well as reducing the number of claims made against the NHS (and, in turn, the amount paid out), can increase the availability of resources for trusts to reinvest in ongoing quality and safety initiatives. Patient empowerment and improving the patient experience: Patients and the public currently contribute vast amounts of data and information to the NHS, the aim of which is to improve the quality of care offered. Nevertheless, there currently does not exist a feedback mechanism for patients to be made aware of improvements in their local service, as a result of suggestions made (e.g. ‘you said, we did’). This project aims to improve demand signalling for the highest priority areas, in turn empowering patients (and healthcare professionals), and providing the confidence that resources are being directed where the system is most in need of them. Through publishing patient facing communications, for example, it is hoped this project will facilitate a sense of buy-in and trust in the NHS. Furthermore, it is hoped that this project could set the wheels in motion for an improved patient experience when navigating the care pathway, and increased confidence and satisfaction with the system.

Request category type

Public Health Research

Other approval committees

Latest approval date

13/06/2022

Safe Data

Dataset(s) name

ICHT NHSX Research Dataset

Data sensitivity level

De-Personalised

Common Law Duty of Confidentiality

Not applicable

National data opt-out applied?

Not applicable

Request frequency

One-off

Safe Setting

Access type

TRE

Safe Outputs

Link to research outputs