An evaluation of the clinical efficacy and risk profile of routine spinal operations performed in the National Health Service
Background
Back pain affects the majority of people at some point in their life, costing the United Kingdom approximately £12 billion per year. It worsens quality of life through loss of function, pain and its psychological effects. We do not currently know the outcomes of routine spinal surgery performed in the National Health Service to help relieve back pain. Most research has been poor with not enough patients to draw conclusions from.
In the United Kingdom data is routinely collected from patients treated in National Health Service (NHS) to allow each hospital to get paid for their work. This is recorded in a database called Hospital Episode Statistics and includes information about each hospital visit. The British Spine Registry is another database which started collecting data in 2012 for routine spinal surgery. We intend to link databases to allow us to accurately assess the outcomes of spinal surgery using large datasets.
This will allow us to better understand the outcomes of spinal surgery, the risks and benefits of surgery, whether surgical or patient factors affect outcomes and how cost effective each procedure is.
Aims & Objectives
We will analyse data routinely collected hospital data to;
- Check the accuracy of the British Spine Registry
- Assess how successful spinal surgery is by assessing postoperative pain, function and the need for further procedures
- Assess what causes successful or unsuccessful surgery by studying patient, surgeon hospital factors.
Compare different spinal surgery procedures to see which is most effective
Datasets used
The study will look back at data on patients who underwent spinal surgery from the year 2000 onwards. The datasets we will be analysing are;
- British Spine Registry (BSR) collects information on all spinal surgery performed each year in both public and private hospitals
- Hospital Episodes Statistics Admitted Patient Care (HES) records information on all patients admitted to NHS hospitals in England.
- Hospital Episodes Statistics Patient Reported Outcome Measures (PROMs).
We will link the data from the British Spine Registry to data from Hospital Episodes statistics. This will allow us to investigate our project aims.
How will our research help clinical practice?
Our research will validate the British Spine Registry and highlight the clinical outcomes of routinely performed spinal procedures for the first time using large datasets. We will be able to study what influences the outcomes of surgery including patient, surgeon and hospital factors. This will help provide more tailored patient care, potentially reduce repeat surgeries and improve pain and functional outcomes, whilst empowering patients to make more informed decisions. In addition, our work will help develop evidence-based guidelines on the surgical interventions with the best outcomes. We aim to publish our findings, present our work internationally and provide evidence based national guidelines on the best surgical treatments for back pain.
Privacy and fair processing notice
Research is a task that we perform in the patient’s best interest. Queen Mary University of London, as sponsor, is the data controller. This means that we, as Queen Mary University of London researchers, are responsible for looking after your information and using it properly. We will use the minimum personally identifiable information possible.
The study has been approved by North East – Newcastle & North Tyneside 1 Research Ethics Committee (Reference 23/NE/0109). The legal basis for the processing and storage of personal data for this study is that it is ‘a task in the public interest’ (article 6(1)(e)) and, that sensitive personal data is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes (article 9 (2) (j), based on Article 89(1)).
Large datasets from the British Spine Registry (BSR) alongside Hospital Episode Statistics (HES) will be used during this study. The BSR holds information about patients who have had spinal surgery and agreed to participation in their data audit. The BSR will send identifiers (pseudo anonymised study ID, NHS number, date of birth, sex and postcode) to NHS England. NHS England will link this data to Hospital Episode Statistics, Office of National Statistics and Patient Reported Outcome Measure datasets using these identifiers. NHS England will then remove personal identifiers except the pseudo anonymised study ID. This pseudo anonymised data will then be securely transferred to Queen Mary University of London. The BSR will separately securely transfer their data with pseudo anonymised study IDs to Queen Mary University of London. The information received from NHS England and the BSR will be imported into a database held securely by Queen Mary University of London and used solely for academic research purposes. Importantly, whilst the information received is specific to individuals, no individual person will be identifiable in any publication arising from this work. The research team will then use the pseudo anonymised study IDs be used to link the datasets. This will prevent either the BSR or NHS England holding all the records for each patient. In addition, this protects the confidentiality of patients and means that the data can be processed in such a way that researchers will not be able to identify patients.
We have special permission to conduct the study “An evaluation of the clinical efficacy and risk profile of routine spinal operations performed in the National Health Service” without study-specific consent (i.e. link, transfer, process and analyse the data) from the Confidential Advisory Group. This permission is given under Section 251 of the National Health Service Act 2006 and its current regulations, the Health Service (Control of Patient Information Regulations 2002) (CAG reference number: 23/CAG/0067).
Data definitions
Identifiable data – Data which can potentially identify an individual e.g date of birth, NHS number, postcode.
Psuedo anonymised data – Data in which identifiable data has been removed and each patient is allocated a unique non identifiable number for analyses.
Data linkage – Merging of two different datasets to allow analyses.
How long do we keep your data?
Queen Mary University of London will hold the data until 01/01/2029 for the sole purposes of the study.
What to do next?
If you decide you do not want your data to be linked in this way you can withdraw from this follow-up, without affecting your current medical care. More information and the ability to opt out of data collection is available at https://www.nhs.uk/your-nhs-data-matters/ . NHS Digital will not provide us with data for anyone who has withdrawn consent.
If you wish to withdraw your consent from the British Spine Registry then you may communicate this to them directly via email at customer.support@amplitude-clinical.com
Data protection regulation provides you with control over your personal data and how it is used. Further information about your rights with respect to your personal data is available at https://arcs.qmul.ac.uk/governance/information-governance/data-protection/ . If you would like to contact our data protection officer directly for more information about how we process and protect data collected for research, please email: data-protection@qmul.ac.uk
If you have further questions or are not happy with the way your data has been handled, please contact the study team using the contact details below. Alternatively, you can contact the study sponsor on 020 7882 7275 or research.governance@qmul.ac.uk. You have the right to lodge a complaint with the Information Commissioner’s Office (0303 123 1113 or www.ico.org.uk).
Additional information links
For more information about how the BSR and NHS Digital use patient information, including how it is collected and how patients can opt out, follow the links below:
Principle
Investigator
Mr Hasan Mohammad, Queen Mary University of London
Chief
Investigator
Professor Xavier Griffin, Queen Mary University of London
funded by
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