NHS Digital Data Release Register - reformatted

Health Iq Ltd projects

447 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

THE CREPE STUDY: Outcomes and treatment pathways for Castration Resistant Prostate Cancer in England: A Real-World Data Study (ODR1920_232) — DARS-NIC-656866-V3H6X

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: No (Commercial)

Sensitive: Sensitive

When:DSA runs 2023-09-08 — 2024-09-07 breached contract — audit report.

Access method: One-Off

Data-controller type: HEALTH IQ LTD

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked DIDs
  3. NDRS Linked HES AE
  4. NDRS Linked HES APC
  5. NDRS Linked HES Outpatient
  6. NDRS National Radiotherapy Dataset (RTDS)
  7. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

The objectives of this study were to:
• To describe the demographic and clinical characteristics of men with metastatic castration-resistant prostate cancer
• To quantify the treatments used and to describe the treatment among men with metastatic castration-resistant prostate cancer
• To describe clinical outcomes, in terms of progression-free survival and overall survival, among men with metastatic castration-resistant prostate cancer
• To describe healthcare resource use in men with metastatic castration-resistant prostate cancer

Health iQ Ltd wishes to retain the previously disseminated data, which at the time of receipt was supplied by Public Health England, for the purposes of the above objectives and processes data under this agreement under Articles 6(1)(f) and 9(2)(i) of GDPR.

While planned analysis for the above objectives has been completed, the results are being used in the funder of the research Advanced Accelerator Applications (AAA) responses to NICE following their submission for Pluvicto. Therefore, retaining access to the data to respond to data queries from NICE is essential. Health iQ Ltd is continuing to process the data in support of this NICE review, to allow policymakers to make informed decisions for the optimal delivery of the healthcare of prostate cancer patients, and hence of benefit to the patients.

In addition, peer review publication of key results is planned. In order to produce a complete manuscript, including the incorporation of reviewer feedback, retaining access to the data is beneficial.

All outputs are aggregated with small numbers suppressed in line with NHS England requirements.

Yielded Benefits:

Data inclusion in a NICE submission to add the assessment group’s decision-making with regards to the clinical and cost effectiveness appraisal of Pluvicto. Engagement of a wide group of clinical experts in the results generated.

Expected Benefits:

This project aimed to describe the real-world demographic and clinical profile of men with metastatic castration-resistant prostate cancer in England, as well as the treatment provided to these patients and the clinical outcomes experienced by the patient group. In addition, the study captures a description of the NHS secondary care resource use associated with metastatic castration-resistant prostate cancer.
Referring back to the stated Outputs, the benefits derived from these outputs are listed below.
1. NICE submission: The inclusion of these data in a NICE submission aids informed policymaking decisions, with real-word data now seen as key for inclusion in health technology assessment decision-making. The inclusion of data in the NICE submission is ongoing as responses to NICE queries are made.
2. Presentation to clinical experts: facilitates clinical engagement with real-world evidence generation and ensures clinically relevant results are generated. Updates to analysis methodologies can be made from clinical review of results i.e., defining lines of therapy. This was completed in summer 2022.
3. Manuscript: disseminates up-to-date real-world data results to a wide clinical and public health audience, the aim is to submit to a peer reviewed journal by the end of 2023.

Outputs:

1. Summary aggregate outputs (no small number suppression required as no small numbers resulted from the aggregate outputs generated) were included in AAA's (funder of the research) NICE submission for Pluvicto in 2022 to provide real-world data on castration-resistant metastatic prostate cancer epidemiology and treatment in England. Further aggregate outputs (with small number suppression if needed) are to be included in the AAA resubmission in June 2023 following NICE's feedback.
2. Aggregate data (with no small numbers included) will be included in a peer review publication for which drafting will commence in July/August 2023. Several leading consultant oncologists will be involved in this publication to ensure clinically relevant information is produced and suitable dissemination of findings through the relevant medical community is achieved.
3. To date, these clinicians have inputted into validating the results generated through a presentation of aggregate summary findings (given via Teams using a powerpoint presentation) presented to them by Health iQ and AAA in the summer of 2022, with feedback on how the results fit with clinical practice. The study team aim to have the peer review publication submitted by the end of 2023. The focus of this publication will be to describe treatment patterns among the study population as well as survival.

Processing:

No further data will be requested under this version of the Agreement.

The Data will never be linked to any external dataset, nor will it ever be re-identified.

Any and all outputs of any kind visible to 3rd parties will always be in an aggregate, non-identifiable form and with small numbers double-suppressed.

The Data protection policy is enforced as follows:
1. The record level data (pseudonymised, non-identifying) will only be stored in the Amazon Web Service (AWS) Data Warehouse and the Ironkey encrypted hard-drive, stored at the registered office location.
2. All Health iQ Ltd staff are instructed not to download any record level Data to local PCs, laptops or any non-encrypted device, and this is enforced by Health iQ Ltd’s Data Security policy (note only approved staff will have physical access anyway, this instruction is an additional measure for approved data-handlers to ensure data is never taken off the server, which is the only location on which it can be analysed).
3. Health iQ Ltd developer and analyst teams use PC/ laptops with encrypted drives only.
4. All data transmission must be encrypted to minimise the risk.
5. Pre-defined reports are exportable, in CSV and PDF formats. All reports are of aggregate data with small numbers suppressed in line with the HES analysis guide.
6. All staff who have access to the raw record level data are Health iQ Ltd staff, and this function is never outsourced to anyone else.

Processing the data:
1. Data was downloaded to an encrypted AWS Workspace, by a named individual (the ‘Data Receiver’).
2. Standard QC checks are run against the data, and some additional calculated fields added.
3. Both raw and the processed data are uploaded to an Ironkey encrypted hard-drive for backup, which is stored in secure environment in Health iQ Ltd registered office.
5. Health iQ Ltd analysts will access record level data via the AWS Data Warehouse using a secure VPN (with 2FA) connection only.

Processing for analysis:
All outputs will be in an aggregate, non-identifying data with small numbers double-suppressed form.
Health iQ has strict access controls based on a 'need to know' basis. Access to data is restricted to a small subset of Health iQ employed users who perform analysis on the data. All users complete mandatory training on information governance and data protection that are required annually for all employees of Health iQ.
Health iQ actively logs and monitors user access and behaviour and uses industry-leading security tools.
Health iQ is closely aligned to the DSPT, GDPR, ISO 27001, ISO 27017 and ISO 27018 frameworks.

AWS AS A DATA PROCESSOR
Amazon Web Services is, strictly, a data processor in the sense that the data are hosted and manipulated on their infrastructure. By design, AWS themselves cannot access or read any of the data in Health iQ that are hosted on their infrastructure, nor can anyone else who is not specifically granted individual access to the data (including Health iQ employees).
Amazon Web Services UK are compliant with many standard security frameworks, including DSPT toolkit, ISO 9001, 27001, 27017, 27018; the Cloud Security Alliance certification and UK Cyber Essentials Plus.

Health iQ - Benchmarking and reporting — DARS-NIC-15293-R6V2H

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(b)(ii), Health and Social Care Act 2012 – s261(2)(a),

Purposes: Yes (Commercial)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2021-07-01 — 2022-06-30 2017.06 — 2024.09. breached contract — audit report.

Access method: Ongoing, One-Off

Data-controller type: HEALTH IQ LTD

Sublicensing allowed: No

Datasets:

  1. Hospital Episode Statistics Accident and Emergency
  2. Hospital Episode Statistics Outpatients
  3. Hospital Episode Statistics Admitted Patient Care
  4. Hospital Episode Statistics Critical Care
  5. Emergency Care Data Set (ECDS)
  6. HES-ID to MPS-ID HES Accident and Emergency
  7. HES-ID to MPS-ID HES Admitted Patient Care
  8. HES-ID to MPS-ID HES Outpatients
  9. Hospital Episode Statistics Accident and Emergency (HES A and E)
  10. Hospital Episode Statistics Admitted Patient Care (HES APC)
  11. Hospital Episode Statistics Critical Care (HES Critical Care)
  12. Hospital Episode Statistics Outpatients (HES OP)

Objectives:

Health iQ is a provider of data-based insight, who produce tools and reports used by health and social care to achieve the following broad aims:
1. Understand and quantify the burden of disease.
2. Support service improvement in terms of treatment and efficiency of service.

Health iQ wishes to provide such insight to Healthcare Providers and the Life Sciences industry.

Health iQ will use the data solely for the following purposes:

1. Vantage System and Related Support
Vantage is an online system that produces aggregated, small-number suppressed, non-sensitive, non-identifiable HES-based dashboards and reports to support the delivery of healthcare. It supports the delivery of a range of key healthcare strategic priorities, including delivering the Five-Year Forward-View, Quality, Innovation, Productivity and Prevention (QIPP) targets and Joint Strategic Needs Assessment (JSNA) targets.
Vantage enables users to:
• Plan healthcare provision with the support of real world data.
• Benchmark performance against peer groups.
• Pinpoint areas of inefficiency.
• Validate the impact of a service improvement programme or new pathway model.

The users of Vantage are limited to the following:
1. NHS users (Provider Trusts, GPs, Commissioners including new NHS commissioning organisations/collaborations such as Vanguards and STPs, Area Teams, Strategic Clinical Networks (SCNs)).
2. Commissioning Support Units (CSUs).
3. Governmental organisations (NHS England, Department of Health (DH), NICE, Academic Health Science Networks (AHSNs)).
4. Social care (Local Authorities, Health & Wellbeing Boards).
5. Charities and not-for-profit organisations.
6. Life Sciences organisations (Pharmaceuticals, Medical Technology, Biotechnology).
Though the users of Vantage can be from any of the above listed groups, it is made clear that the allowed purposes of use are restricted to those mentioned in this document, with the ultimate beneficiary being healthcare as a whole. This is enforced through sub-license agreement between Health iQ and users.
Life Science organisations are a user of Vantage exclusively for the purpose of providing benefit to healthcare. As with all user groups, they will only ever have access to aggregated outputs and are bound by sub-license agreements which ensure the usage of the data is in line with this document. In addition, Health iQ insist that all users of the tool undergo information governance training by a Health iQ trainer, and all reports produced by the tool come with a pre-written disclaimer statement.

2. Reports
Health IQ will produce reports either as responses to specific data requests, or as part of wider projects. These reports will take the form of suppressed, aggregated, non-sensitive and non-identifiable data tables. As these reports will be constructed in response to a specific need, the content will vary, though all conform to all the restrictions outlined in this document. Examples of such reports could be:
• A report by Hospital on total activity which falls within a Best-Practice Tariff (BPT) area, and the proportion of such activity which achieved the BPT.
• A report of the tariff cost of Irritable Bowel Syndrome (IBS) patients by CCG, including all related symptoms and associated conditions to produce a ‘true burden’ analysis of the cost of IBD (Irritable Bowel Disease) to the healthcare system.
To be absolutely clear, reports will never:
• Relate or link HES data to the use of commercially available products, such as the prescribing of an individual pharmaceutical product.
• Present data in a way which patient or clinician identity can be identified, even by linking to other datasets.
• Break suppression rules.
The potential users of reports are:
1. NHS users (Provider Trusts, GPs, Commissioners, Area Teams, Strategic Clinical Networks).
2. Commissioning Support Units (CSUs).
3. Governmental organisations (NHS England, DH, NICE, AHSNs).
4. Social care (Local Authorities, Health & Wellbeing Boards).
5. Charities and not-for-profit organisations.
6. Life Sciences organisations (Pharmaceuticals, Medical Technology, Biotechnology).
Though the users of reports can be from any of the above listed groups, it is made clear that the allowed purposes of use are restricted to those mentioned in this document, with the ultimate beneficiary being healthcare as a whole. This is enforced Health-IQs license agreement, which is signed between Health iQ and any client.

3. Public Access ‘Health iQ Insight’ Reports
These are reports based on aggregated, suppressed, non-sensitive, non-identifiable HES data with the aim of:
• Highlighting trends in demand and activity in a disease area.
• Raising awareness of a disease area.
• Providing high-level analysis of the management of a disease area.
These reports are being made publically available, including being viewed on a dedicated area on the Health iQ website. The first of these (Care cost and activity in MS and Neurology in the Greater Manchester area) has been published.

Yielded Benefits:

Health iQ has provided examples below of how the data has been used, including the benefits to healthcare that have resulted from this use. These are typical of the type of usage their customers offer to the NHS. Health iQ have listed some of the main benefits, and will continue to provide (on renewal of the data) further examples of what specific benefits have been given through the use of the data. Relating to Objective 1: (Vantage System and Related Support) A growing user base across NHS and non-NHS, hence a greater number of users benefiting from the intelligence provided by the tool. Relating to Objective 2: (Reports, Studies and Analysis) 1. Co-authored a poster titled ‘Health-Care Resource Utilization following Trabeculectomy: An Analysis of English Hospital Episode Statistics (HES) Data’. The study helped to demonstrate the value of new interventions with comparable interocular pressure and less resource burden. 2. Worked with Salford Royal NHS Foundation Trust to analyse the pathway of MS patients and compare to the NICE recommended standard, hence identifying any deviation from best practice. 3. Developed a ‘Mortality Risk Predictor’ algorithm for patients undergoing a range of surgical procedures, based on criteria such as age, co-morbid conditions and procedure type. This allowed Health iQ to produce a risk index which can be used to guide decision-making prior to surgery. 4. Conducted a study titled ‘Characterisation of Atrial Fibrillation and Bleeding Risk Factors with Chronic Lymphocytic Leukaemia’. The aim was to identify risk factors for AF or bleeding for CLL patients, to support the treatment of these patients with appropriate medication. Relating to Objective 3: (Public Access ‘Health iQ Insight’ Reports) Reports published in 2017 (http://www.healthiq.co.uk/public-reports): Report of Market Intelligence for NOAC Market: analysis of the growth in NOAC usage, relative to AF/Stroke burden of care in hospitals. Report on DVT Activity in Hospitals: analysis of the burden of care due to DVT in hospitals across England. Report on MS and Neurology Activity in Manchester (http://www.healthiq.co.uk/images/reports/Report%20on%20Multiple%20Sclerosis%20and%20Neurology.xlsx).

Expected Benefits:

• Vantage was used by a trust that was conducting a service evaluation in order to support a case for change to optimise the pathway in Neuroscience. Their work allowed them to understand the variation of care in the region, and make recommendations to standardise care to an optimal pathway across the region and develop a more integrated care pathway.

• The West Midlands Epilepsy SCN use Vantage on an ongoing basis to focus and review its main project of reducing non- elective admissions in the locality (see details at http://www.wmscnsenate.nhs.uk/strategic-clinical-networks/our-network/mental-health-dementia-and-neurological-conditions/current-projects/epilepsy/).
Stated benefits have included (and are anticipated annually):
- A West Midlands wide template care plan for epilepsy patients (March 2015)
- Development of a care pathway to optimise care and reduce repeat admissions (March 2015)
- Information pack provided to CCG commissioners (May 2015)
- 5% Reduction in non elective admissions within 14 days where epilepsy is the primary reason for admission (Sept 2015)
- 100% of patients presenting at A&E with a primary diagnosis of epilepsy will either be referred to a first seizure clinic or epilepsy specialist following a non-elective presentation.

• Vantage data is used at Parkinson’s Excellence Networks and SCN's on an ongoing basis to review regional services and variation. The data continues to be presented to hospital departments and large scale regional meetings to demonstrate evidence of need to change.

Health-IQ has provided three examples above of how the tool will be used, including the benefits to healthcare that will result from this use. These are typical of the type of usage our customers offer to the NHS. Health-IQ have listed some of the main benefits, and will provide (on renewal of the data) further examples of what specific benefits have been given through the use of the tool.

Outputs:

With significant growth in the number of NHS clients using Vantage, two case studies of use of the Vantage system producing aggregate reports in the last 6 months are listed below:

Case study 1: London based provider trust:
The trust was conducting some research into clinical effectiveness of the Open-Angle Glaucoma pathway. They used Vantage to look into prescribing patterns at a CCG level, and compare with hospitalisation outcomes for diagnosed patients. They effectively replicated a study done in the US, which allowed them to make a robust case for changes in the pathway.

Case study 2: Manchester based provider trust:
The trust was conducting a service evaluation in order to support a case for change to optimise the pathway in Neuroscience. They used Vantage to look at referrals for a range of diagnosis (eg Motor Neuron Disease) from different sources. They wanted to understand where the patients came from, what type of site they were treated in and what the main outcomes were. They then benchmarked all local trusts to see how the service model varied. It allowed them to understand the variation of care in the region, and make recommendations to standardise care to an optimal pathway across the region and develop a more integrated care pathway.

Other examples of on-going uses of the data over the past 12 months are included below - as with all outputs, all of these will be small-number suppressed according to an agreed methodology (which at minimum ensures suppression in line with the HES Analysis Guide), aggregated, non-sensitive and non-identifiable:

• Vantage data used to produce ‘Burden of Hospitalisation’ paper in Parkinson’s disease. This is now cited by Parkinson’s UK, and has also been quoted to support business cases for new Parkinson's nurses in a number of NHS Trusts (including Addenbrookes, Hertfordshire and Staffordshire) and to support new Parkinson’s pathway /guidelines standards (at Trusts such as Ipswich and Dudley).
• The West Midlands Epilepsy SCN’s annual report on reducing epilepsy-related non- elective admissions in the locality.

Other outputs not from the Vantage system will only contain data suppressed in line with the HES Analysis Guide, and will be ad hoc reports for the customers outlined in the Objectives.

None of the outputs may be used for sales or marketing purposes by the Health-IQ customer.

Processing:

All data processing is done within the UK, and is carried out according to the following process:
1. Data is received from HSCIC (via HSCIC’s secure FTP link), by either the Head of Delivery or Senior Project Manager
2. Data is uploaded by either Head of Delivery or Lead Developer via an encrypted external drive onto a secure local server (server is security protected and locally based in the head office).
3. Data is deleted from encrypted external drive
4. Calculations are run against the HES data
5. Calculated HES Data uploaded into secure local data warehouse
6. Data undergoes testing process
7. A subset of the HES data is exported from the secure local server, and uploaded via an encrypted connection into the Vantage backend system on external UK data centre hosted by UK Fast, who only are only the 'bricks and mortar' location and do not process data.
8. Aggregate data is made available through the Vantage presentation layer to the live system users who access Vantage via a secure password login system.
9. Health iQ analysts will access record level data via the local data warehouse and secure connection only.
10. Backup of the Vantage system is held on a dedicated, secure, private encrypted backup drive

The Vantage system is held entirely on the secure server, and accessed only via secure web link (no record level data is held on any customer’s local machine at any time). The above processing means that the Vantage tool only presents aggregate data, and thus only aggregate data is available to customers of the tool.

The HES data protection policy has been enforced as follows:
1. The record level data (pseudonymised, non-identifiable) will only be stored in secured local data warehouse, hardware encrypted disk (for in house backup) or secure vantage hosting environment in UK Data centre
2. All Health iQ staff are instructed not to download any record level HES data to local PCs, laptops or any non-encrypted device.
3. Health iQ developer and analyst teams use PC/ laptops with encrypted drives
4. All data transmission must be encrypted to minimise the risk.

Pre-defined reports are exportable, in CSV and PDF formats. All reports are of aggregate data only. Users can create their own reports and export them.

All staff who have access to the raw record level data are Health iQ staff, and this function is never outsourced to anyone else.

Small numbers in the Vantage system and any other outputs are suppressed in line with the HES analysis guide, specifically :-

- For Vantage tool: rounding of all patient and admission counts to nearest multiple of 5. Eg. If at provider level patient count is 34. This provider has only two hospitals A and B, where A has 30 patients and B has 4 patients. The tool will show provider level patient count as 30 and hospital level counts as 30 and 5 respectively. A user will never get a number lower than 5. Furthermore, since all the patient and admission counts have been rounded to nearest multiple of 5, user will never know exact patient or admission counts.

- For other outputs: as per HES Analysis Guide

Health-IQ’s team includes consultants and data specialists the majority of whom are former NHS employees, who have worked at senior levels in Commissioning, Performance and Information management functions. Health iQ have utilised this insight into the needs of NHS commissioning and provider organisations to design the Vantage tool. All individuals with access to record-level data are employees of Health iQ.

Full data is required, as Health iQ's analysis is not limited to any particular age, region or any other sub-group.

The Vantage hosting infrastructure is regularly penetration tested by an external independent vendor. The latest penetration testing by an external vendor has been confirmed and is scheduled to take place in early 2017.

Treatment Pathway of HR+/HER2- Metastatic Breast Cancer in England ( ODR2021_059 ) — DARS-NIC-656880-K7V7P

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: Yes (Commercial)

Sensitive: Non-Sensitive

When:DSA runs 2023-04-13 — 2023-07-12 2023.04 — 2024.02. breached contract — audit report.

Access method: One-Off

Data-controller type: HEALTH IQ LTD, NOVARTIS PHARMACEUTICALS UK LIMITED

Sublicensing allowed: No

Datasets:

  1. NDRS Cancer Registrations
  2. NDRS Linked Cancer Waiting Times (Treatments only)
  3. NDRS Linked DIDs
  4. NDRS Linked HES AE
  5. NDRS Linked HES APC
  6. NDRS Linked HES Outpatient
  7. NDRS National Radiotherapy Dataset (RTDS)
  8. NDRS Systemic Anti-Cancer Therapy Dataset (SACT)

Objectives:

Novartis – are the funder for the project and act as Health IQ's client. Health IQ will implement the project on behalf of the client.  This contract was put in place by PHE and subsequently novated to NHS England. On return Health IQ must uplift the application to meet all DARS standards which will ratify the relationship between Health IQ and NOVARTIS.

The Data Recipient (Health IQ) will conduct an epidemiological research study with the following aims/objectives:

Research questions
What is the treatment pathway for patients diagnosed with hormone receptor-positive, human epidermal growth factor receptor 2 negative (HR+/HER2-) metastatic breast cancer (mBrCA) in England and how does access to treatment differ across England amongst this patient group?

Primary Objective
To describe the lines of therapy received by all HR+/HER2- mBrCA patients post-diagnosis along with systemic therapies received under each line of therapy.

Secondary Objectives
• To create a cohort of patients with HR+/HER2- mBrCA in England
• To describe this cohort of patients by demographic and pertinent clinical characteristics
• To determine differences in access to treatment across England by regions and provider trust.

Yielded Benefits:

Results generated are guiding a future research project looking at more specific epidemiological and treatment related questions and a new DARS submission to be completed in 2024.

Expected Benefits:

This project aims to describe the real-world demographic and clinical profile of women with HR+/HER- breast cancer in England, as well as the treatment provided to these patients and the clinical outcomes experienced by the patient group.
Referring back to the stated Outputs, the benefits derived from these outputs are listed below.
1. NICE submission: The inclusion of these data in a NICE submission aids informed policymaking decisions, with real-word data now seen as key for inclusion in health technology assessment decision-making. The inclusion of data in the NICE submission ensures that policy decisions are well evidenced, and in turn patients are provided with the best possible treatment options.
2. Manuscript: disseminating up-to-date real-world data results to a wide clinical and public health audience, allowing review and discussion of HR+/HER- breast cancer real-world treatment by such an audience aims to facilitate any necessary improvements in treatment and equity to treatment.

Outputs:

Most of Health iQ’s work is intended for publication, and as such we demand the highest quality work and academically vetted, robust methodology. Should the client decide to move forward with a publication, as likewise strongly encouraged by PHE for any project that is undertaken with their data, Health iQ is happy to author research for this project.

As part of Good Clinical Practice, Health iQ plans to register this study in preparation for future publication. Any such step will be taken only with the consent of the client.

Target conferences include: ISPOR, ISPOR Europe, ESMO, depending on date of completion of the study. Target journals include the BMJ, The Lancet Oncology, Value in Health and Health Economics

Request for ONS linked data for a cohort of patients diagnosed with Beta-thallasaemia and myelodysplasia syndrome between 01/01/2015 to 31/12/2019. — DARS-NIC-422044-Z5K5Q

Type of data: information not disclosed for TRE projects

Opt outs honoured: Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: Yes (Commercial)

Sensitive: Sensitive

When:DSA runs 2021-07-01 — 2022-06-30 2021.07 — 2021.07. breached contract — audit report.

Access method: One-Off

Data-controller type: HEALTH IQ LTD

Sublicensing allowed: No

Datasets:

  1. Civil Registration - Deaths
  2. Civil Registrations of Death

Objectives:

Health IQ Limited (Health IQ) is a research consultancy specialising in providing research and analytics expertise to healthcare and life sciences. Their consultants have experience in the application of data to solve specific problems within the industry. Their work spans primary, secondary, mental health, community and wider societal datasets. Health IQ Limited produce tools and reports used by health and social care to achieve the following broad aims:

1. Understand and quantify the burden of disease.
2. Support service improvement in terms of treatment and efficiency of service.
3. Add to the body of healthcare knowledge available through robust research”

For this particular project, Bristol-Myers Squibb (an American multinational biopharmaceutical company and a client of Health IQ) have funded Health IQ to undertake a one-time analysis and provide a report looking at the two conditions below:
Beta-thalassaemias are a group of hereditary blood disorders characterized by anomalies in the synthesis of part of red blood cells that carries oxygen throughout the body resulting in issues ranging from severe anaemia to other medical conditions while myelodysplastic syndromes (MDS) are an often unrecognized, under-diagnosed rare group of bone marrow failure disorders, where the body no longer makes enough healthy, normal blood cells in the bone marrow where a risk of progression to acute myeloid leukaemia (AML) exists.

Although, the prognosis of individuals with beta-thalassaemia has substantially improved in the last couple of decades as a result of advances in treatment methods, there is a gap in the knowledge of what a typical patient journey looks like in the actual hospital setting.

This study is therefore aimed at mapping out the patients journey of this cohort of patients from diagnosis including the treatments received, clinical outcomes e.g. death and the associated resource usage using secondary care data collected in England.

This is a retrospective observational study on an administrative healthcare data set in England between 01/01/2015 and 31/12/2019 with no link to other studies. The cohort was identified using ICD-10 codes from Hospital Episode Statistics (HES) data during the study period . The original HES data used to identify the cohort was obtained under agreement DARS-NIC-15293-R6V2H between Health IQ and NHS Digital. Under the original agreement Health IQ have access to HES Inpatient, Outpatient and Accident and Emergency (A&E) datasets which enabled them identify patients with the two conditions as those who had ever been coded within the preceding 5 years. The endpoints to be measured cover demographics and clinical patient profiles (including age, gender, comorbidities), treatment patterns (treatment specialities) and healthcare resource use (inpatient admissions, length of hospital stay, outpatient appointments, A&E attendances and costs). As an observational study, there will be limited utility establishing causality thus Health IQ will not be able to establish the statistical relationship between the conditions and selected endpoints, although this is not an objective of the study. The objectives are thus primarily descriptive as below.

Objective 1 - To describe the patients diagnosed with beta thalassaemia or MSD in terms of demographics and clinical characteristics.
Objective 2 - To describe the patient’s treatment pathway from diagnosis including procedures, transfusions and the specialities they have been treated in.
Objective 3 - To quantify the associated healthcare resource use and tariffs for this patient cohort including inpatient, outpatient, and A&E care.
Objective 4 - To quantify the clinical outcomes associated with patients with beta thalassaemia including adverse events resulting from blood transfusions, and death.
Objective 5 - To describe mortality outcomes such as cause of death and time to death (survival analysis).

For objective 5, although HES data has death records (mortality data), it is only recorded when a patient dies during a hospitalisation which is not sufficient for to achieve the study objectives. As mortality is one of the end points to be determined to achieve one of the objectives of this study, Health IQ therefore require Civil Registration mortality to ascertain when patients within the cohort die and what the recorded cause of death is outside of hospital. This information is only available in the Civil Registration (Deaths) data extract and hence why Health IQ require linkage.

Under the original agreement DARS-NIC-15293-R6V2H Health IQ's GDPR Legal Basis for processing the pseudonymised record-level data from NHS Digital was Articles 6(1)(f) Legitimate Interests and 9(2)(j). Health IQ wish to continue to process the data in order to conduct analysis that will support the optimal delivery of healthcare as a whole, and hence be a benefit to the individuals and all patients. Patient-level data is required in order to accurately conduct the above types of analysis, without this Health IQ could not conduct the level of research needed to provide new insights into diseases or treatment pathways, and the potential benefit to healthcare of this research would not be realised. Health IQ have carried out a Legitimate Impact Assessment using the Information Commissioner’s Office (ICO) template and has been reviewed by NHS Digital. NHS Digital continue to conclude that Health IQ can rely on legitimate interests for this processing.

However, this agreement requests only pseudonymised record-level data on Mortality. Date of death is being released under this agreement and NHS Digital have satisfied themselves that this will not render the dissemination identifiable, and that the dissemination remains pseudonymised and is not owed a duty of confidence.

Only aggregated data with small number suppression applied as per the HES analysis guide will be disseminated as part of a study report.

Health IQ will be the sole Data Controller and Funder for this request, who also processes the NHS Digital data. In this agreement Amazon Web Services (ASW) is, strictly, a Data Processor in the sense that NHS Digital data are hosted and manipulated on their infrastructure. By design, AWS themselves cannot access or read any of the NHS Digital data in Health IQ that are hosted on their infrastructure, nor can anyone else who is not specifically granted individual access to NHS Digital data (including Health IQ substantive employees).

Expected Benefits:

This study is aimed at generating knowledge to understand the treatment pathway, healthcare resource use and costs and clinical outcomes associated with the Beta thalassaemia and myelodysplastic syndromes. Health IQ would also want to look at whether there is a relationship between transfusions and survival and whether the degree or increase in transfusion over time change survival in these patients. Currently there is a lack of data on treatment pathways, healthcare burden and the impact of survival on UK patients with beta thalassaemia and MDS and how this compares to the general population. It is believed that these patients have a worse prognosis and therefore having greater understanding of this may help in shaping the treatment pathway in the future.

The knowledge generated once disseminated with the intended audiences through the suggested channels publication and presentation at conferences is hoped to go a long way within informing policy makers, clinicians and drug manufacturers of the real-world picture in relation to these two conditions. This, in turn, is hoped to inform budgeting, clinical management decisions and support evidence generation for Reblozyl[a] for the European Medicines Agency (EMA) review for the treatment of MDS and Beta thalassaemia patients with ring sideroblasts which would all lead to improved patient experiences and outcomes in the future once approved.

All output will be generated by Health IQ and the evidence will be shared with Bristol-Myers Squibb. The Main purpose of this analysis would be to generate evidence for Reblozyl for EMA review for the treatment of MDS and Beta thalassaemia patients with ring sideroblasts. As a result Bristol-Myers Squibb will use this data to inform their engagement with regulatory and licencing authorities. Bristol-Myers Squibb is the manufacturer of Reblozyl and as such would stand to gain by way of commercial profit if the drug is adopted for use in the UK and in other healthcare systems around the world.

[a] https://news.bms.com/news/corporate-financial/2020/European-Commission-Approves-Reblozyl-luspatercept-for-the-Treatment-of-Transfusion-Dependent-Anemia-in-Adult-Patients-with-Myelodysplastic-Syndromes-or-Beta-Thalassemia/default.aspx

Health IQ aim to have these findings published, targeting high impact journals (e.g. the BMJ, Lancet, NEJM, Value in Health). The resulting publication shall follow relevant guidelines for each journal, as well as the principles outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Understanding how these two conditions are managed for patients in the health system, the usage of resources and what happens to these patients post treatment including survival is hoped to lead to:
i. Improved treatment options and policy that is based on data.
ii. Data led resource allocation and treatment strategies for any patient diagnosed with these conditions.
iii. Data le assessment of unmet need to inform the need for an intervention of the most at risk patients.
iv. The above will all lead to better treatment outcomes hence reducing preventable morbidity and mortality due to these conditions amongst the population.

This is hoped to be of significant benefit to newly diagnosed and existing NHS patients with beta-thalassaemia and myelodysplasia syndrome.

Outputs:

The output from this data processing is expected to be an excel report and a peer reviewed article that will be submitted to a peer reviewed journal such as the British Medical Journal (BMJ) or Lancet. The reports are hoped to also be used to submit poster and oral presentations to relevant conferences e.g. International Conference on Immunological, Hematological and Rheumatological Sciences. It is expected that this will enable the results of this study to reach policy makers such as the NHS, commissioners, disease area experts, clinicians, other researchers, scientists, clinician groups and pharma. The study team hope to influence policy for care of patients with these conditions, inform budget allocations and foster engagement on issues affecting patient care within this disease area thus ensuring the knowledge generated is of public health benefit for the UK and the rest of the world.

Health IQ Limited aim to have the information generated to be communicated through the different channels between July and December 2021.

The reports will be aggregate data with small numbers suppressed based on HES analysis guidance to make sure deductive disclosure does not happen. No individual level data will be published or disseminated to the public.

NHS Digital will be recognised as a data provider in all reports or articles produced as part of this data processing.

Processing:

The cohort will be identified from the NHS Digital pseudonymised HES data by Health IQ based on ICD-10 codes using agreement DARS-NIC-15293-R6V2H. Each individual record is assigned a unique HES-ID.

The cohort of will be shared with NHS Digital to be linked to the Civil Registrations (ONS) data set using the HESID field to identify the required mortality data. Linkage will be based on unique HESIDs which will ensure no duplication can occur.

The extracted record-level pseudonymised data (containing only those records where a death is registered) will then be sent to Health IQ by NHS Digital through a secure file sharing mechanism called SEFT (Secure Electronic File Transfer).

Health IQ will then process the record level pseudonymised data to carry out survival analysis and determine cause of death for each individual record. The results will be aggregated with small number suppression applied for the whole cohort and presented in a study report.

Data will be stored in a secure cloud platform – Amazon Web Services and are only accessible through secure access 2-factor authentication mechanisms (i.e. via a Virtual Private Network (VPN)). Analysis will only be carried out by Health IQ analysts who are all substantive employees who have monitored access to the databases. Health IQ staff will carry out the analysis using remote devices that are secured through very strict access password-protected 2-factor authentication access system. All staff who will access the data have regular IT/ Information Governance/ Data Protection training. No data is permitted to be downloaded and stored on remote devices. All storage and processing will be conducted in the cloud server platform.

Amazon Web Services is, strictly, a data processor in the sense that NHS Digital data are hosted and manipulated on their infrastructure. By design, AWS themselves cannot access or read any of the NHS Digital data in Health IQ that are hosted on their infrastructure, nor can anyone else who is not specifically granted individual access to NHS Digital data (including Health IQ substantive employees). Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Amazon Web Services UK are compliant with standard security frameworks, including ISO 9001, 27001, 27017, 27018; the Cloud Security Alliance certification and UK Cyber Essentials Plus. Amazon Web Services will only be storing NHS Digital data on UK based servers.

Processing of the data is restricted to within England and Wales. No attempt to re-identify individuals will be undertaken by Health IQ Limited.

DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION
In order to protect patient confidentiality, when presenting results calculated from record level Mortality data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing Mortality data, you must make sure that:
· cell values from 1 to 7 are suppressed at a local level to prevent possible identification of individuals from small counts within the table.
· Zeros (0) do not need to be suppressed.
· All other counts will be rounded to the nearest 5.
Data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide.