Vascular Data Analyst and Clinical Governance Coordinator

University Hospitals Sussex NHS Foundation Trust
Brighton
21 hours ago
Create job alert
Overview

View all our vacancies across our hospitals in Sussex. Search, find and apply for a job with us today.

Vascular Data Analyst and Clinical Governance CoordinatorBand 5

Main area vascular   Grade Band 5 Contract Permanent Hours Part time - 33 hours per week (4 days per week) Job ref 279-7553501-JAN26

Employer University Hospitals Sussex NHS Foundation Trust  Employer type NHS Site Royal Sussex County Hospital Town Brighton Salary £31,049 - £37,796 pro rata Salary period Yearly Closing 22/02/2026 23:59

At UHSussex we’re proud to be at the heart of the NHS. As one of the UK’s largest acute trusts, we’re a leading example of the excellence, the ambition and the values that have embodied the NHS for over 70 years.

Our hard-working, talented and dedicated people work together towards a common goal – to deliver Excellent Care Everywhere for our patients, our people and our communities. Whatever your role here at UHSussex you will play a part in driving us forwards and in improving the lives of patients across Sussex.

At UHSussex, diversity is our strength, and we want you to feel included to help us deliver Excellent Care Everywhere. Your uniqueness and experiences will be part of our creative and innovative community where everyone is encouraged to succeed. We have a range of staff networks to help break down barriers, and can offer a buddy to help new members settle in. We’re proud to be a Disability Confident Employer (Level 3) and a Veteran Aware Trust.

We value compassion, inclusion and respect as our core values. We treat our patients and staff with the same compassion and empathy we expect for ourselves. We’re here for them when they need us, and we go above and beyond to meet their needs. This can be seen in our wellbeing programme for staff which is extensive and designed to support you when you need it, including where possible, flexible working to support work life balance - because we know that to look after others we must first look after ourselves.

As a university trust and a leader in healthcare research, we value learning, teaching and training so that we can be the best that we can be. From the moment you start with us and throughout your career we will help you to grow and develop. We hope that in choosing UHSussex you are choosing a long and happy career where you will be able to see the difference you make and feel valued for all that you do.

As part of our commitment to access for all, please see the different ways you can access the application form: https://apps.trac.jobs/accessibility?_ts=1

We look forward to receiving your application and the start of your journey with UHSussex.

Job overview

The purpose of the Vascular Service across Sussex is to provide high quality Vascular and Interventional Radiology (IR) services to patients within Sussex, which are compliant with NHSEngland national service specifications. The Network/Service comprises a single ‘hub’ Arterial Vascular Centre based at RSCH, supporting ‘spoke’ Non-Arterial sites at Princess Royal Hospital, St. Richards Hospital, Worthing Hospital, East Sussex Healthcare NHS Trust and Surrey and Sussex Healthcare NHS Trust.

The post holder will contribute to the upkeep of the National Vascular Registry (NVR) and to support local audits, local clinical databases, Clinical Governance and research within the vascular department and the collation and accurate and timely inputting of data for the vascular team.

The post holder will assist the department in maintaining local databases by capturing accurate, complete and timely patient data to support the submission to the National Vascular Registry and participating in producing reports using this data to demonstrate achievement of performance and quality indicators. They would also support clinicians in local audits and reporting for Clinical Governance.

The post holder must have excellent communication skills, and be able to work on their own initiative, within the supportive team.

Main duties of the job

The purpose of this role is to further the development of the Vascular Network across Sussex. The post holder will do this by:

  • Ensuring the timely submission of accurate and comprehensive clinical data to the National Vascular Registry (NVR), Vascular Services Quality Improvement Programme (VSQIP) and National Consultant Information Programme (NCIP).
  • Analyse and disseminate NVR and NCIPs Vascular reports and prepare reports and presentations on the key findings.
  • Support the development of Vascular clinical information reporting systems, currently Dendrite, Vascular Network.
  • Plans of work will be developed in conjunction with key clinical staff to ensure the fulfilment of Trust requirements. Other national or local projects may be developed; they will support communication to the wider multi-disciplinary team especially regarding the results of the national audits.
Working for our organisation

At UHSussex, diversity is our strength, and we want you to feel included to help us always deliver Excellent Care Everywhere, as shown in our Outstanding for Caring CQC rating. Your uniqueness and experiences will be part of our creative and innovative community where everyone is encouraged to succeed. We have a range of staff networks to help break down barriers, and can offer a buddy to help new members settle in. We’re proud to be a Disability Confident Employer (Level 3) and a Veteran Aware Trust.

Detailed job description and main responsibilities

Please note: This role does not meet the minimum criteria for visa sponsorship under the current UK immigration rules, which set specific salary and skill thresholds. As such, we are unable to provide sponsorship for this post. Applicants will therefore need to already have the right to work in the UK to be considered. We include this information at the outset to provide clarity and avoid unnecessary inconvenience for applicants.

Communication

Interrogate, analyse and present the Vascular and NVR data to internal and external parties to support a programme of continuous improvement in the care of Vascular patients.

As the Trust’s principal point of contact with NVR and clinical and external groups, keep up to date with NVR and other Vascular registry and audit issues, and ensure that the Clinical Outcomes & Effectiveness Team and Vascular Network are kept apprised of relevant developments.

Establishing and maintaining good working links with pre-hospital services (NAAASP, local screening) and local and regional Vascular units.

As the Vascular Audit representative, prepare for and attend regular Trust meetings to review and update the audit progress. To deputise at the meeting in the absence of the Clinical Governance Lead or Lead Vascular Nurse Specialist.

Communicate with patients to capture patient consent giving permission to be part of the national audits and capture audit data.

Service Delivery and Improvement

To be aware of NVR and CQUIN Best Practice tariff and ensure all eligible Vascular patients are identified and captured.

To identify gaps in data collection and design protocols to capture data for both clinical outcome improvements.

Interpret national and local policy to determine the implications for the collection and reporting of data. Ensure senior clinicians and managers are adequately briefed on all new publications and changes to national, regional and local policies and guidance.

Supporting Research and Audit

Validate and review submitted data reported quarterly to NVR to improve quality and accuracy of data thereby achieving maximum Best Practice Tariffs payment.

The postholder will be expected to provide expert audit advice, to contribute to and facilitate clinical governance meetings, including room bookings, minutes and maintaining compliance with Trust requirements. This will include meetings with external partner organisations, e.g. as part of the Vascular Network.

To have a specialist input into the design, collection, analysis, report preparation and dissemination of results.

To monitor and investigate data quality issues, ensuring problems are brought to the attention of the appropriate manager.

Administration

Identify patients who meet the NVR audit criteria, review their case notes and other relevant information held electronically (e.g. on the Patient Administration System, MediViewer, Bamboo) and on paper, and submit these data to the NVR audit programme. Considerable emphasis is placed on the submission of timely, accurate and comprehensive data.

Entry of patient data into the clinical systems (currently Dendrite) will also be an important element of this post and as such supports the robust entry of data into the NVR.

Data submission to NVR currently involves manual data entry through the web-based portal. However, the piloting of the current clinical system (Dendrite) is supporting the exploration of alternative means of reducing manual and duplicate data entry. The post holder will be expected to support these developments, for example by identifying opportunities for streamlining processes across the range of his/her responsibilities.

Person specificationQualifications, skills and experience
  • Educated to degree level or equivalent experience
  • International Computer Driving Licence (ICDL)
  • Audit training course
  • Data interpreting and analysis skills
  • The Research, Audit and Quality Improvement program Knowledge of the structure and working of the NHS
  • Knowledge of Clinical Governance initiatives within the NHS
  • Current or previous registration in a regulated health profession
  • Postgraduate qualification involving advanced data extraction/manipulation and statistical analysis
Equality, Diversity and Inclusion
  • Evidence of having undertaken own development to improve understanding of equalities issues
  • Evidence of having championed diversity in previous roles (as appropriate to role)

Important information for applicants:

A Note on AI Use in Applications We value the individuality and authenticity that each candidate brings to the application process. While AI tools are increasingly accessible, we strongly discourage their use in completing your application. Your responses should reflect your own voice, experiences, and motivations—elements that are essential to a fair and accurate evaluation. Applications that rely heavily on AI-generated content may misrepresent your abilities and could result in your application being rejected. We encourage you to take the time to present your genuine self, as this helps us better understand your potential and ensures a transparent selection process.

Closing Adverts Early: In the event of exceptional interest, we may close adverts earlier than specified.

Flexible Working: If you would like to explore potential options regarding flexible working please speak with the appropriate recruiting/line manager.

DBS Checks: As part of our commitment to a safe working environment, we undertake a Disclosure and Barring Service check on all new employees where the role is eligible for a criminal record check. We make offers in line with the Rehabilitation of Offenders Act 1975.

Skilled Worker Visa: Applications for Skilled Worker sponsorship are welcome for the roles that meet the Visa and immigrations eligibility criteria. For further information please visit the gov.uk website searching for Skilled Worker. It is your responsibility as the applicant to ensure that you meet this criteria.

UHSussex reserves the right to close the role early if we receive a high volume of applications

Further Information

For help with the application process for Nursing vacancies, please email .

For help with the application process for Non-Nursing vacancies, please email .

Employer certification / accreditation badges

The postholder will have access to vulnerable people in the course of their normal duties and as such this post is subject to the Rehabilitation of Offenders Act 1974 (Exceptions) Order 1975 (Amendment) (England and Wales) Order 2020 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service to check for any previous criminal convictions.

Application numbers

This advert has been capped for a limited number of applications; therefore, it will close once the cap has been reached. We therefore encourage you to submit your application as soon as possible if you are interested in this post to prevent you from missing out on applying for this opportunity.

Name Jason Clark Job title Lead Vascular Nurse Specialist Email address Telephone number

Additional information

Head of Nursing Emma Gillingham ()


#J-18808-Ljbffr

Related Jobs

View all jobs

Vascular Data Analyst and Clinical Governance Coordinator

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.