Is travel burden associated with differences in health outcomes for patients diagnosed with breast, lung, prostate, colorectal or oral cancers living in Yorkshire & Humberside and the North East Regions.

University of Hull requires access to NHS England data for the purpose of the following research project: "Is travel burden associated with differences in health outcomes for patients diagnosed with breast, lung, prostate, colorectal or oral cancers living in Yorkshire & Humberside and the North East Regions?"

The following is a summary of the aims of the research project provided by University of Hull:

"This study plans to examine the associations between travel times and travel distances and differences in outcomes for cancer patients. It also seeks to examine in direct response to the Chief Medical Officers call in 2021 to investigate potential differences in cancer outcomes for cancer patients living in coastal communities" www.gov.uk/government/publications/chief-medical-officers-annual-report-2021-health-in-coastal-communities.

The following NHS England data will be accessed:

• Cancer Registration – needed to compare the 5 different cancers.

• Hospital Episode Statistics Admitted Patient Care - needed to provide more information for the statistical models that will be focusing on treatment received for cancer (focusing on surgery and time spent in hospital).

• National Cancer Patient Experience Survey (CPES) - needed to provide additional information on the support that patients perceived that they received and how that is associated with the key outcomes. Waves 9 and 10 requested relate to years 2019 and 2020 and are the most recent questionnaires completed by cancer patients following treatment. The study wishes to assess for levels of support in the models and to use the most recent results.

• Radiotherapy dataset (RTDS) – needed to provide more information for the statistical models that will be focusing on treatment received for cancer (focusing on radiotherapy).

• Systemic Anti-Cancer Therapy Dataset (SACT) – needed to provide more information for the statistical models that will be focusing on treatment received for cancer (focusing on chemotherapy).

• NDRS Cancer Pathway - Necessary to support a more complete assessment of travel burden across the cancer care pathway. While SACT and RTDS datasets capture chemotherapy and radiotherapy activity, they do not include hormone therapy or the full volume of healthcare interactions. The Cancer Pathway dataset provides additional coverage of patient contacts, including outpatient and A&E attendances, and enables identification of both provider and activity levels required to estimate number and location of trips. Inclusion of this dataset is therefore necessary to ensure a comprehensive and clinically informed analysis, while avoiding duplication by using each dataset only for the variables it uniquely contributes.

The level of the data will be pseudonymised.

The data will be minimised as follows:

• Limited to data for adults greater than 17 years old;

• Limited to data for cancers diagnosed between 01 January 2013 to 31 December 2020.

• Limited to the following data for patients residing in the following geographical boundary codes for the cancer alliances: Northern Cancer Alliance (E56000029), Humber Coast and Vale Cancer Alliance (E56000026), West Yorkshire and Harrogate Cancer Alliance (E56000030), South Yorkshire and Bassetlaw Cancer Alliance (E56000025)

• Limited to conditions relevant to the study identified by specific ICD or OPCS codes;

- Breast Cancer (ICD10 C50)

- Lung Cancer (ICD10 C33, C34 and C45)

- Colorectal Cancer (ICD10 C18, C19 and C20)

- Prostate Cancer (ICD10 C61)

- Oral Cancer (ICD10 C00 – C14)

• Only waves 9 and 10 are requested from the CPES dataset

University of Hull is the research sponsor and the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest on the basis of research and statistical purposes. Firstly, this research study is directly addressing a known deficiency in the evidence available on the cancer outcomes of communities living on the coast. This was highlighted by the Chief Medical Officers report on coastal communities published in 2021 (health in coastal communities). The hypothesis is that there are inequalities in cancer treatment and access to healthcare for those who live in coastal communities compared to those in non-coastal communities, which result in inequalities in outcomes. This data will test this hypothesis and provide evidence on cancer cases in coastal communities. Secondly, existing research has identified that travel burden (measured by distance/ travel times to healthcare) is associated with inequalities in access to treatment. The hypothesis is that living further from healthcare facilities (e.g. GP, radiotherapy centres) is associated with poorer healthcare outcome (e.g. survival) and inequalities in treatment received (e.g. not having palliative radiotherapy). University of Hull has worked closely with a patient public involvement (PPI) group to plan the proposed research and ensure that what is being proposed is in the public’s interest and will directly answer key questions that are relevant to patients diagnosed with cancer.

The funding for the data cost and staff time to undertake the analysis comes from the principal investigators (PI) fellowship funding (funded through a Yorkshire Cancer Research Career Development Fellowship). The funding includes the described study, as part of a programme of research. The funder will have no ability to suppress or otherwise limit the publication of findings. The Yorkshire Cancer Career Development Fellowship funding runs until May 2024 at which point the PI will transfer to being a Lecturer at the University of Hull.

AIMES Management Services Ltd are the data processors. They are responsible for the University of Hull Data Safe Haven.

There are no other organisations involved.

Data will be accessed by substantive employees of the university and by PhD students enrolled at University of Hull. Individuals have completed mandatory data protection and confidentiality training and is subject to University of Hull’s policies on data protection and confidentiality. The PhD students accessing the data will do so under the supervision of a substantive employee of University of Hull. University of Hull would be responsible and liable for any work carried out by the individuals. The PhD students would only work on the data for the purposes described in this Agreement.

The Project has an established Patient and Public Involvement and Engagement approach through the University of Hull’s INVOLVE Hull group, which includes around 50 members with lived experience of cancer or screening. This group has been actively involved in shaping the research, and its development and input have been formally documented. In addition, PhD students linked to the project run their own funded PPIE activities to ensure public perspectives are embedded throughout the study design, delivery and interpretation. Efforts have been made to include a diverse range of voices, including people from coastal areas and more deprived communities. The proposed data use has been discussed with the group, and the focus remains clearly on understanding travel burden and cancer outcomes. A knowledge comic book documenting the growth of the group and how expertise have been utilised can be accessed online via https://heyzine.com/flip-book/f1c5a34015.html#page/1

No data will flow to NHS England for the purposes of this Agreement.

Data will be transferred directly from NHS England to the University of Hull Data Safe Haven (DSH). Data related to this project will be stored and processed exclusively within the DSH with no touchpoints on wider University of Hull infrastructure.

NHS England data will provide the relevant records from the HESAPC, Cancer Registry, RTDS, CPES , Cancer Pathway and SACT datasets to the University of Hull. The data will contain no direct identifying data items but will contain a unique person ID.

Data is stored within the University of Hull Data Safe Haven (DSH). This is a trusted research environment hosted by AIMES within their data centre in Liverpool. Data storage and analysis will be undertaken exclusively within the data safe haven with no touchpoints outside. Researchers will access the data via virtual machines, again hosted within the data centre

Data for each project is logically separated meaning there is no ability to access or link to datasets from other projects within the DSH. When working within the environment users have no way to move data from within the DSH to any device outside of it. All data enters and leaves through a digital airlock which is linked to the above authorisation workflow.

Data is backed up with the AIMES data centre using processes and systems exclusive to AIMES. There is no third party involved and no transfer of data outside the data centre.

Researchers access the environment via a secure VPN connection from University of Hull managed devices with 2-factor authentication. As such no data will leave the data centre and nothing will sit on the end users’ machine.

The data will not leave England/Wales at any time.

All processing / analysis is restricted to researchers who are employees of the University of Hull who have authorisation from the Principal Investigator and PhD students enrolled at the university who hold an honorary contract.

AIMES Management Services Ltd is not permitted to access or process the data for purposes beyond the provisioning, securing and back-up of the project environment.

AIMES have system administrative access to the system but act on the instructions of University of Hull DSH admin. AIMES are processor for the purposes of provisioning, securing and back-up of the service.

Research staff complete NHS Data Security training along with DSH specific training prior to being granted access to the environment. Additionally, staff are trained on how to access and work within the DSH. This is all auditable. Staff also sign user terms and conditions prior to receiving access.

The datasets provided will not be linked to any other data outside of the scope of the agreement.

A database file has been created that has the travel times and distances for each LSOA (geographical variable) and OA (geographical variable) in the Yorkshire and Humber and North East Regions to each possible healthcare facility (GPs and hospitals). These have been calculated using the Visography TRACC software (https://basemap.co.uk/tracc), the UK road network, healthcare locations from NHS England and output areas and LSOA areas from the office for national statistics. In addition to the travel times and distances the LSOA (geographical variable) areas have been categorized as either coastal or non-coastal. This file will be added to the data safe haven at the University of Hull. This file will be merged with the data provided by NHS England in the data safe haven. It will be merged using the LSOA/OA geographical variable identifiers contained in both sets of data providing the travel times and travel distances needed and classification of coastal or non-coastal location. Once merged a working dataset will be created with the LSOA/OA geographical variables removed from it.

There will be no requirement and no attempt to reidentify individuals when using the data.

Researchers from the University of Hull will analyse the data for the purposes described above.

The expected outputs of the processing will be a submission to peer reviewed journals and publishing of academic papers.

All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide (NHS Digital (2019) HES Analysis Guide).

All outputs from the logistic regression and Cox proportionate Hazard Models will be coefficients and 95% Confidence Intervals.

Outputs will be in the form of peer-review publications and conference presentations accessed by academics, policy makers, commissioners and clinicians, with lay summaries made available for service users and the public. Summaries of findings will be used to inform patient and public involvement (PPI) and clinical staff groups.

Publishing academic papers that report on the findings from the association between living further from a healthcare facility and outcomes for cancer patients (stage at diagnosis, survival, and differences in treatments in academic journals) is targeted for between 2023 and 2026.

This purpose directly supports the research that explores whether living in a coastal community is associated with differences in health outcomes from lung cancer. This directly meets the call from the Chief Medical Officers report in 2021 that evidence on cancer outcomes are lacking when looking specifically at coastal areas and there is a need for more evidence on coastal outcomes.

The potential impact of living further from a healthcare facility on a patient’s cancer outcomes and treatment choices will be disseminated based on the data is analysed.

Depending on the findings it is expected that this can be used as evidence to provide guidance on extra support to patients who may have to travel further or who have difficulties getting to the healthcare facilities for their treatment and diagnosis.

University of Hull work closely with the funders (Yorkshire Cancer Research) to communicate directly the findings. University of Hull work closely with the Hull Involve PPI group to disseminate the findings directly to the people who have helped shape and guide the research. University of Hull are also working closely with the local Cancer Alliances (e.g. Humber, Coast and Vale Cancer Alliance) to actively promote the research and findings for this region.

The results of this study were presented at a number of conferences. It has formed the basis of a PhD students' PhD thesis focusing on lung cancer outcomes in coastal communities. A research paper on this is about to be submitted for publication. This PhD research is informing the issue of later stage diagnosis of lung cancer for patients living on the coast and providing evidence for where to put mobile lung health checks. This has fed directly into work completed by the local Cancer Alliance. The data will form the basis for a new PhD study that is focusing on hub and spoke models of delivering healthcare for cancer patients.

Access to this data has supported research examining inequalities in healthcare access and health outcomes among people diagnosed with cancer, with a particular focus on geographical variation and deprivation. Recent presentations have explored whether proximity to GP services is associated with stage at diagnosis for major cancers, and whether lung cancer outcomes and access to specialist services are poorer for people living in coastal communities.

The data has formed the basis of a PhD study, funded by Yorkshire Cancer Research and submitted for examination in April 2026, using mixed methods to investigate lung cancer in coastal populations, including stage at diagnosis and survival outcomes. Papers arising from this work are planned, including studies defining coastal populations and examining how coastal residence is associated with differences in lung cancer diagnosis and survival. The data is also supporting a new PhD project assessing associations between geographical location, cancer diagnosis through screening programmes, stage at diagnosis, and survival. This PhD will develop a tool to inform where mobile screening units should be in order to target areas with lower screening uptake.