MICA: A partnership to extend the research utility of a source of real-world health data, the UK National Neonatal Research Database
Lead Research Organisation:
Imperial College London
Department Name: School of Public Health
Abstract
Aim: Our aim is to improve the usefulness of an established UK resource, the National Neonatal Research Database (NNRD) for parents and for researchers so that they can view data and conduct studies to improve the care of preterm and sick newborn babies more quickly, efficiently and at lower cost than presently. About 1 in 7 (100,000 each year) newborn babies is admitted to a NHS neonatal unit. Neonatal problems and the care received, affect life-long health and well-being.
Background: We established the NNRD, a unique, award-winning resource, in collaboration with parents, doctors, nurses, other healthcare professionals, and researchers to improve care, treatments and outcomes for preterm and sick babies admitted to NHS neonatal units. The NNRD contains comprehensive data, updated quarterly, from the electronic medical notes of all babies admitted to NHS neonatal units in England, Scotland and Wales. Imperial College London hosts the NNRD securely on a computer server. No data that can identify any individual baby are included. The data include details of diseases, daily treatments and outcomes. To-date the NNRD has information on about one million babies; around 25,000 new babies are added each quarter.
Why this work is needed: We established the NNRD because a key challenge in newborn care is the need for up-to-date, timely and accurate data for research to improve, evaluate and develop new treatments. Data are required for all of the many types of studies needed, such as improving understanding of diseases, their causes and the care provided, and to develop new medicines. Different types of studies often need similar data (e.g. age, sex, weight, disease) but traditionally, researchers collect these again and again for each new purpose. This is expensive, wastes time and increases the risk of errors. Studies can fail because data availability or quality are poor. Data also need to be up-to-date otherwise information may be misleading. For example, information on health outcomes of very preterm babies that are widely used in the UK to counsel parents and guide clinical practice was derived from research conducted over 20 years ago and no longer reflects circumstances today. The NNRD provides a single source of up-to-date data for research and other purposes. This work is needed to improve the NNRD and make it more useful.
Our objectives, and what we will do: We will automate processes to check accuracy and add new data into the NNRD that we currently perform manually. At present anyone who wants to use the NNRD must request our assistance, which inevitably incurs a delay. We will identify common types of information that researchers, parents and clinicians would find useful to obtain from the NNRD. This might be to determine the number of patients with particular conditions that are admitted to neonatal units. We will also obtain views on the way in which they would like to see the results (e.g. tables or graphs). This will help us develop web-based tools to enable parents and researchers to answer common questions themselves. We will make these tools available on our website. We will also develop ways to process NNRD data so that we can apply new techniques that can help identify patterns such as where particular types of disease occur and provide clues to their causes. Additionally, we will train young scientists in handling complex health data.
Why this partnership is needed: We have formed a partnership because our objectives require skills across different organisations and disciplines. Our partnership brings clinical neonatologists, academic researchers and data scientists together with the national information technology lead for the health and care system in England (NHS Digital), expertise in data tools (Strategic Intelligence Alliance for Health; SIA), the national charity for preterm and sick newborn babies (Bliss) and the national institute for health data, Health Data Research (UK HDR-UK).
Background: We established the NNRD, a unique, award-winning resource, in collaboration with parents, doctors, nurses, other healthcare professionals, and researchers to improve care, treatments and outcomes for preterm and sick babies admitted to NHS neonatal units. The NNRD contains comprehensive data, updated quarterly, from the electronic medical notes of all babies admitted to NHS neonatal units in England, Scotland and Wales. Imperial College London hosts the NNRD securely on a computer server. No data that can identify any individual baby are included. The data include details of diseases, daily treatments and outcomes. To-date the NNRD has information on about one million babies; around 25,000 new babies are added each quarter.
Why this work is needed: We established the NNRD because a key challenge in newborn care is the need for up-to-date, timely and accurate data for research to improve, evaluate and develop new treatments. Data are required for all of the many types of studies needed, such as improving understanding of diseases, their causes and the care provided, and to develop new medicines. Different types of studies often need similar data (e.g. age, sex, weight, disease) but traditionally, researchers collect these again and again for each new purpose. This is expensive, wastes time and increases the risk of errors. Studies can fail because data availability or quality are poor. Data also need to be up-to-date otherwise information may be misleading. For example, information on health outcomes of very preterm babies that are widely used in the UK to counsel parents and guide clinical practice was derived from research conducted over 20 years ago and no longer reflects circumstances today. The NNRD provides a single source of up-to-date data for research and other purposes. This work is needed to improve the NNRD and make it more useful.
Our objectives, and what we will do: We will automate processes to check accuracy and add new data into the NNRD that we currently perform manually. At present anyone who wants to use the NNRD must request our assistance, which inevitably incurs a delay. We will identify common types of information that researchers, parents and clinicians would find useful to obtain from the NNRD. This might be to determine the number of patients with particular conditions that are admitted to neonatal units. We will also obtain views on the way in which they would like to see the results (e.g. tables or graphs). This will help us develop web-based tools to enable parents and researchers to answer common questions themselves. We will make these tools available on our website. We will also develop ways to process NNRD data so that we can apply new techniques that can help identify patterns such as where particular types of disease occur and provide clues to their causes. Additionally, we will train young scientists in handling complex health data.
Why this partnership is needed: We have formed a partnership because our objectives require skills across different organisations and disciplines. Our partnership brings clinical neonatologists, academic researchers and data scientists together with the national information technology lead for the health and care system in England (NHS Digital), expertise in data tools (Strategic Intelligence Alliance for Health; SIA), the national charity for preterm and sick newborn babies (Bliss) and the national institute for health data, Health Data Research (UK HDR-UK).
Technical Summary
The National Neonatal Research Database (NNRD) is a dynamic relational database of extracts from the electronic patient records (EPR) of NHS neonatal unit admissions. We receive quarterly extracts over secure NHS N3 environment as a password protected .bak file of multiple tables reflecting groups of EPR entry screens, and identifier codes reflecting each table and episode of care. Neonatal care is delivered in a network model hence babies usually have multiple episodes across different hospitals. We remove identifiers and assign pseudonymised codes. We identify duplicate, missing, internally inconsistent and out-of-range entries. We check episode temporal consistency and hospital, provider and network codes, notifying neonatal units of potentially erroneous or missing entries. As each extract contains data on babies born within the last 5 years, corrections are incorporated progressively into the NNRD. With NHS Digital, we will automate the majority of these processes and publish detailed technical specifications. Supported by Bliss, we will identify and prioritise areas that researchers from different backgrounds, and parents, might wish to interrogate the NNRD (e.g. event rates, patient numbers, outcomes). The NNRD is managed in a MS SQL Server environment, hence can be used for automated reporting directly from data subsets. With SIA we will develop on-line analytical processing tools to enable standard queries to be run rapidly by researchers and parents. We will use applications such as IBM Cognos, MicroStrategy and Board MIT, basing initial development upon simulated data. We will also develop approaches to curate NNRD for future application of data-driven techniques such as selection of normalisation and clustering techniques (e.g. K-means, Dirichlet Process Gaussian Mixture Modelling), development of "smart" queries based on commonly utilised derived measures (e.g. birth weight Z-scores) and modelling time-dependent concepts (e.g. feeding patterns).
Planned Impact
The work we propose will have wide, substantial and immediate impact on academic research groups and industry sponsors in the UK and around the world, patients and families, clinicians, research funders, policy-makers and the global standing and competitiveness of the UK in relation to use of real-world health data i.e. data derived from routine sources.
The partnership will transform and scale-up technical infrastructure and improve the capabilities of researchers to access and interrogate the NNRD. This will reduce burden of data collection and the costs of research and improve the speed and efficiency of studies. The evidence-base for much of present-day neonatal care is limited, and over 90% of neonatal medications remain off-label or off-license. There would be considerable positive impact on patient care and outcomes from ability to generate new evidence more rapidly.
There is considerable global interest in the use of real-world data, The NNRD is a source of real-world data and already supports many types of studies such as observational research to identify disease determinants, health services research to improve the organisation and delivery of care, pragmatic clinical trials and epidemiological research. The outcome of this partnership will strengthen the use of routine real-world health data to improve newborn care and advance the world-leading position of the UK in this field.
There will be further impact through added value to current parallel work by the applicants. We are part of a newly formed initiative, the ALPHA Collaboration, led by the University of Sydney Clinical Trials Unit to deliver large international randomised controlled trials in perinatal medicine using routine data. We are also collaborating with Shanghai Fudan University to develop a China Neonatal Research Database modelled on the NNRD. Modi is co-director of the eNewborn network of European neonatal units sharing electronic health data for bench-marking and research.
Industry is increasingly interested in utilising real-world data. The lead applicant, NM, is a member of the International Neonatal Consortium, a US Food and Drug Administration funded initiative to accelerate the pace of development of medicines for newborn babies that includes developing the potential of real-world data through creation of standards for data definitions, measurements and methods. NM is also a member of C4C (connect4children) expert groups. C4C is a newly formed European network with 33 academic and 10 industry partners to facilitate the development of medicines for infants and children. C4C aims to bring innovative approaches, including use of real-world data to deliver fast and efficient clinical trials. The NNRD is already being used for an industry sponsored study to determine the optimum dose of a neonatal medication. Hence, the UK is poised to achieve high impact through the NNRD.
The NNRD is already impacting UK health policy; e.g. as sole data source for the UK National Neonatal Audit Programme, through use in the Department of Health Maternal and Neonatal Health and Care Policy Research Unit in which Knight, Modi and Gale are Co-I, the National Maternity and Perinatal Audit, and Maternity Transformation Programme. The outcomes of this partnership will accelerate opportunities for wider policy impact through more rapid availability of quality assured, timely data, and new tools enabling direct interrogation by researchers.
Health informatics is a multi-disciplinary field that aims to improve the safety, delivery and effectiveness of healthcare through use of technology and analysis of health data. However, delivering insights is bottle-necked due to the shortage of relevant skills. This partnership will grow capacity in health informatics and data science. We will publish our approach in high-impact peer-reviewed journals which will facilitate adoption by other specialities in the UK, and research groups world-wide.
The partnership will transform and scale-up technical infrastructure and improve the capabilities of researchers to access and interrogate the NNRD. This will reduce burden of data collection and the costs of research and improve the speed and efficiency of studies. The evidence-base for much of present-day neonatal care is limited, and over 90% of neonatal medications remain off-label or off-license. There would be considerable positive impact on patient care and outcomes from ability to generate new evidence more rapidly.
There is considerable global interest in the use of real-world data, The NNRD is a source of real-world data and already supports many types of studies such as observational research to identify disease determinants, health services research to improve the organisation and delivery of care, pragmatic clinical trials and epidemiological research. The outcome of this partnership will strengthen the use of routine real-world health data to improve newborn care and advance the world-leading position of the UK in this field.
There will be further impact through added value to current parallel work by the applicants. We are part of a newly formed initiative, the ALPHA Collaboration, led by the University of Sydney Clinical Trials Unit to deliver large international randomised controlled trials in perinatal medicine using routine data. We are also collaborating with Shanghai Fudan University to develop a China Neonatal Research Database modelled on the NNRD. Modi is co-director of the eNewborn network of European neonatal units sharing electronic health data for bench-marking and research.
Industry is increasingly interested in utilising real-world data. The lead applicant, NM, is a member of the International Neonatal Consortium, a US Food and Drug Administration funded initiative to accelerate the pace of development of medicines for newborn babies that includes developing the potential of real-world data through creation of standards for data definitions, measurements and methods. NM is also a member of C4C (connect4children) expert groups. C4C is a newly formed European network with 33 academic and 10 industry partners to facilitate the development of medicines for infants and children. C4C aims to bring innovative approaches, including use of real-world data to deliver fast and efficient clinical trials. The NNRD is already being used for an industry sponsored study to determine the optimum dose of a neonatal medication. Hence, the UK is poised to achieve high impact through the NNRD.
The NNRD is already impacting UK health policy; e.g. as sole data source for the UK National Neonatal Audit Programme, through use in the Department of Health Maternal and Neonatal Health and Care Policy Research Unit in which Knight, Modi and Gale are Co-I, the National Maternity and Perinatal Audit, and Maternity Transformation Programme. The outcomes of this partnership will accelerate opportunities for wider policy impact through more rapid availability of quality assured, timely data, and new tools enabling direct interrogation by researchers.
Health informatics is a multi-disciplinary field that aims to improve the safety, delivery and effectiveness of healthcare through use of technology and analysis of health data. However, delivering insights is bottle-necked due to the shortage of relevant skills. This partnership will grow capacity in health informatics and data science. We will publish our approach in high-impact peer-reviewed journals which will facilitate adoption by other specialities in the UK, and research groups world-wide.
Organisations
- Imperial College London (Lead Research Organisation)
- Bliss (Collaboration, Project Partner)
- NHS DIGITAL (Collaboration)
- Strategic Intelligence Alliance Inc (Collaboration)
- UNIVERSITY OF OXFORD (Collaboration)
- HEALTH DATA RESEARCH UK (Collaboration)
- Critical Path Institute (Collaboration)
- Strategic Intelligence Alliance (Project Partner)
- NHS Digital (Project Partner)
- Health Data Research UK (Project Partner)
Publications
Lammons WB
(2023)
Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset.
in BMJ health & care informatics
Modi N
(2023)
Pilot feasibility study of a digital technology approach to the systematic electronic capture of parent-reported data on cognitive and language development in children aged 2 years.
in BMJ health & care informatics
Greenbury S
(2021)
Identification of variation in nutritional practice in neonatal units in England and association with clinical outcomes using agnostic machine learning
in Nature Scientific Reports
Modi N
(2020)
Improving the Efficiency and Impact of Clinical Research: A Game Changer for 21st Century Neonatology.
in Neonatology
Modi N
(2021)
Facilitating quality improvement through routinely recorded clinical information.
in Seminars in fetal & neonatal medicine
Greenbury S
(2021)
Birthweight and Patterns of Postnatal Weight Gain in Very and Extremely Preterm Babies: A 12 Year, Whole Population Study
in SSRN Electronic Journal
Greenbury SF
(2022)
Post-natal growth of very preterm neonates - Authors' reply.
in The Lancet. Child & adolescent health
Greenbury SF
(2021)
Birthweight and patterns of postnatal weight gain in very and extremely preterm babies in England and Wales, 2008-19: a cohort study.
in The Lancet. Child & adolescent health
Description | Department of Health initiative to reduce perinatal brain injury |
Geographic Reach | National |
Policy Influence Type | Contribution to new or improved professional practice |
URL | https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/6629... |
Description | Extending parental leave for famillies with babies in neonatal intensive care |
Geographic Reach | National |
Policy Influence Type | Citation in other policy documents |
Impact | Parents whose babies are in neonatal care for over a week will be entitled to statutory paid leave for every further week their baby is on the unit up to a maximum of 12 weeks. It will be available to parents of all babies in neonatal care, whether they were born premature or at term. The leave will be paid at a rate of around £160 per week. It will become available in 2023. |
URL | https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/8718... |
Description | Born in Scotland in the 2020s |
Amount | £870,247 (GBP) |
Organisation | University of Edinburgh |
Sector | Academic/University |
Country | United Kingdom |
Start | 05/2021 |
End | 11/2022 |
Description | Cervical Ripening at Home or In-Hospital - prospective cohort study and process evaluation (CHOICE Study) |
Amount | £782,967 (GBP) |
Funding ID | NIHR127569 |
Organisation | National Institute for Health Research |
Sector | Public |
Country | United Kingdom |
Start | 12/2019 |
End | 11/2022 |
Description | European Health Data Network (EHDEN) Data Partner Call 3 |
Amount | € 100,000 (EUR) |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 03/2021 |
End | 03/2022 |
Description | Infrastructure Services Development |
Amount | £50,000 (GBP) |
Organisation | Health Data Research UK |
Sector | Private |
Country | United Kingdom |
Start | 12/2021 |
End | 05/2022 |
Description | MICA: Meeting global need to improve newborn care through real-world-health-datafacilitated, digital-technology-supported randomised clinical trials |
Amount | £664,698 (GBP) |
Funding ID | MR/X009831/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 04/2023 |
End | 03/2025 |
Description | PROTECT PRegnancy Outcomes using continuous glucose monitoring TEChnology in pregnant women with Type 2 diabetes: A multicentre randomised controlled trial of the clinical and cost effectiveness of using continuous glucose monitoring in pregnant women wit |
Amount | £1,447,896 (GBP) |
Organisation | University of East Anglia |
Sector | Academic/University |
Country | United Kingdom |
Start | 05/2023 |
End | 04/2027 |
Description | Precision-medicine platform trials to improve the care of sick and preterm newborn babies |
Amount | £201,720 (GBP) |
Funding ID | NIHR153935 |
Organisation | National Institute for Health Research |
Sector | Public |
Country | United Kingdom |
Start | 09/2022 |
End | 08/2023 |
Description | Preterm birth as a determinant of neurodevelopment and cognition in children: mechanisms and causal evidence |
Amount | £2,050,400 (GBP) |
Organisation | University of Edinburgh |
Sector | Academic/University |
Country | United Kingdom |
Start | 11/2022 |
End | 10/2027 |
Title | NNRD interrogation tools |
Description | On-line tools for users to interrogate the NNRD, e.g. to obtain information on neonatal outcomes, demographics, and to assist in trial design |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | Tools available to the public, parents, researchers and NHS clinicians and managers |
URL | https://www.imperial.ac.uk/neonatal-data-analysis-unit/neonatal-data-analysis-unit/neonatal-data-vis... |
Title | National Neonatal Research Database - AI |
Description | National Neonatal Research Database curated for AI applications |
Type Of Material | Data analysis technique |
Year Produced | 2021 |
Provided To Others? | No |
Impact | This will be available to others by the end of 2021 |
Title | Neonatal Data Set |
Description | The Neonatal Data Set outlines the data items required for the secondary uses data set, the National Neonatal Research Database (NNRD). The NNRD collects data about the care of babies admitted to NHS neonatal units and is maintained by the Neonatal Data Analysis Unit (NDAU), based at the Chelsea and Westminster Hospital Campus of Imperial College London. The Neonatal Data Set is an NHS Information Standard. This information standard is published under section 250 of the Health and Social Care Act 2012. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | The Neonatal Data Set is an NHS Information Standard. |
URL | https://digital.nhs.uk/data-and-information/information-standards/information-standards-and-data-col... |
Description | Automating National Neonatal Research Database quality assurance processes |
Organisation | NHS Digital |
Country | United Kingdom |
Sector | Public |
PI Contribution | Revision of the Neonatal Data Set |
Collaborator Contribution | This work has been delayed by COVID-19 |
Impact | No outputs as yet |
Start Year | 2020 |
Description | Development of a real-world dataset to faciitate the development of neonatal medicines |
Organisation | Critical Path Institute |
Country | United States |
Sector | Charity/Non Profit |
PI Contribution | Data provision |
Collaborator Contribution | Assembling an international collaboration |
Impact | No outcomes yet |
Start Year | 2021 |
Description | Development of on-line National Neonatal Research Database interrogation tools |
Organisation | Strategic Intelligence Alliance Inc |
Country | Canada |
Sector | Private |
PI Contribution | Data contribution and domain specific expertise |
Collaborator Contribution | Collaboration to train new staff member |
Impact | On-line publicly available tools to interrogate the National Neonatal Research Database. Multidisciplinary development including parents, former patients, NHS clinicians, managers, social scientists, and researchers. |
Start Year | 2020 |
Description | Growing public trust in use of routine clinical data |
Organisation | Bliss |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Public-patient involvement and engagement activities; assistance with HDR-UK Gateway functionality development; membership of Alliance Board |
Collaborator Contribution | Support with discoverability of the National Neonatal Research Database; access processes |
Impact | Development of communication materials; dissemination of outputs |
Start Year | 2019 |
Description | Improving the discoverability of the National Neonatal Research Database |
Organisation | Health Data Research UK |
Country | United Kingdom |
Sector | Private |
PI Contribution | Access to the National Neonatal Research Database; membership of HDR-UK committees and working parties |
Collaborator Contribution | Assistance in navigating HDR-UK Gateway processes |
Impact | The National Neonatal Research Database is listed as a national data asset on the HDR-UK Alliance Gateway |
Start Year | 2020 |
Description | Maternal and Neonatal Health and Care Policy Research Unit |
Organisation | University of Oxford |
Department | National Perinatal Epidemiology Unit Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Data from the National Neonatal Research Database; neonatal expertise |
Collaborator Contribution | Lead of neonatal theme |
Impact | Multiple publications |
Start Year | 2019 |
Title | NNRD-AI |
Description | The NNRD-AI is a version of the NNRD curated for data science applications |
IP Reference | |
Protection | Trade Mark |
Year Protection Granted | 2022 |
Licensed | No |
Impact | Licensing is under consideration. The notable impact is facilitation in the use of real-world clinical data in research through curation that reduces the need for domain expertise and speeds applications. |
Description | Focus groups with European parents and preterm adults, in partnership with European Foundation for the care of Newborn Infants |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | Development of neonatal precision medicine platform RCT |
Year(s) Of Engagement Activity | 2022 |
Description | Focus groups with UK parents, preterm adults and clinicians |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | Development of a neonatal precision medicine platform RCT |
Year(s) Of Engagement Activity | 2023 |
Description | Parent and former patient advisory groups |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | Multiple focus groups and formation of i) parent advisory group; ii) former patient advisory group; ancillary advisory group |
Year(s) Of Engagement Activity | 2021,2022 |
Description | Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Presentation of the National Neonatal Research Database at a meeting orgainised by HDR-UK |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.hdruk.ac.uk/news/the-national-neonatal-research-database-an-exemplar-of-collaboration-to... |
Description | Understanding the National Neonatal Research Database |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Real-world data for real-world evidence and real patient benefit 1 November 2021 How the National Neonatal Research Database (NNRD) is working with Health Data Research UK (HDR UK). The National Neonatal Research Database (NNRD) is a longitudinal, whole-population registry, developed with extensive stakeholder and parent involvement, as a single source of high-quality, detailed clinical information to improve newborn care. It was developed and is maintained and managed at the Neonatal Data Analysis Unit at the Chelsea and Westminster NHS Foundation Trust campus of Imperial College London, led by Professor Neena Modi. The NNRD is formed from regular extractions from electronic patient records; and contains information on all admissions to NHS neonatal units in England, Wales, and Scotland from 2007, representing over one million patients' to-date. It is an immensely valuable asset, and its use has led to numerous improvements in neonatal clinical care, the organisation of health services for sick and preterm newborn babies, and national health policy. Recently the team at the Neonatal Data Analysis Unit has partnered with Health Data Research UK (HDR UK), the national institute for health data science, to work with other custodians of UK health data, and improve how the NNRD can be better accessed for research for patient benefit. At HDR UK's monthly "Open Door" session for the Head Data Research Innovation Gateway (the 'Gateway'), Professor Neena Modi talked about the NNRD to researchers in more detail; and how partnering with HDR UK is supporting their vital work. |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.hdruk.ac.uk/news/real-world-data-for-real-world-evidence-and-real-patient-benefit/ |