About

Assembling the Data Jigsaw is a research programme in Greater Manchester that will bring together existing and new health care data to answer questions about arthritis that are important to patients. It will solve problems of missing health information, data in formats that are difficult to analyse, or which are stored in isolation.

The problem

Arthritis and other musculoskeletal (MSK) conditions are a leading cause of disability and have a significant impact on the quality of people’s lives. Unfortunately, the amount and quality of information collected from patients living with musculoskeletal disease is limited. This makes it hard for doctors and researchers to make the same progress in understanding disease and selecting the best treatment for musculoskeletal conditions, compared to some other health conditions. This is sometimes because information is just never recorded within the NHS (such as people’s experiences of living with disease), or because information is not recorded in a way that be accessed or analysed by researchers.

How we are trying to address this problem

In Assembling the Data Jigsaw, we will join together different sources of patient data to answer important questions about musculoskeletal conditions, as well as collecting information in different ways or for the first time. We will develop a web-based questionnaire so that patients can share information about the impact of living with musculoskeletal conditions and any support received for day-to-day activities, as well as their use of opioids and other pain medications.

The project will be run in Salford, Greater Manchester where hospital and GP records are already joined up. We will extract information contained in letters sent to patients and their GPs (following visits to hospital clinics) using a technique called text-mining, allowing computers to analyse data rather than manually reading each letter. We will also find ways for healthcare staff to record information in a better way that can both improve care as well as be accessed for research. We will additionally link this information to social care datasets and look at ways of adding information given by patients themselves.

We will use the safest and most secure ways to assemble the data and provide access for researchers. We are committed to ensure all research activities follow, and indeed help establish, the highest standards in dealing with medical information and patient data.

How this will benefit patients

We will demonstrate the value of this new data by using it to answer important questions such as:

  • How common is it for people to be diagnosed with this particular type of arthritis?
  • Are there ways of speeding up the time it takes to be diagnosed with rheumatoid arthritis and ankylosing spondylitis?
  • What are the benefits and possible harms of certain painkillers?

Lastly, we will identify how our new ways of collecting and linking data can be reproduced in other parts of the country. We hope that, in the future, improving data quality and access across England will develop more accurate diagnosis and improve treatment of arthritis and other MSK conditions.

If collected in the right way and accessed safely, data will improve the management of health conditions for future generations.

Patient and public involvement and engagement (PPIE)

PPIE will take place throughout the programme by researchers in collaboration with and supported by a core group of experienced public contributors. The public contributors are undertaking engagement activities with diverse communities in Salford, where the research is taking place, to raise awareness of the research and involvement opportunities, and ensure a range of voices and lived-experience will be heard within the Jigsaw research.  

Download Patient and Public Involvement and Engagement strategy (PDF)

Jigsaw Advisory Group

The Jigsaw Advisory Group comprises expertise from the musculoskeletal health community, social care and patient data.  Their role is to bring advice and challenge to the research programme to help ensure it is:

  • Robust
  • Meets the needs of its stakeholders
  • Aware of existing and forthcoming relevant initiatives
  • Produces high quality outputs

Members of the Group will guide and support the successful dissemination of the research and other outputs from the programme.

See Terms of Reference for more information and a list of Group members.

Download Terms of Reference for the Jigsaw Advisory Group and (PDF)

Project workstreams and work packages

Workstream 1: Clinical Research Questions

Work package 1.1 Understanding the frequency and impact of rheumatic and musculoskeletal conditions in Salford

First, we will look at data from patients’ hospital records to identify patients with a musculoskeletal diagnosis. Because of the way musculoskeletal conditions are sometimes recorded, it is difficult to make reliable estimates of how common they are through just patients’ GP records alone. Comparing diagnoses in both hospital and GP records will help us provide more accurate estimates of both how many people have musculoskeletal conditions (the prevalence) and how many new cases occur each year (the annual incidence) of arthritis and musculoskeletal conditions. More accurate estimates can inform the design and planning of GP and rheumatology outpatient services and staffing levels.

We also aim to collect information directly from patients about how musculoskeletal conditions affect their lives to “fill the gaps” in the information that is currently collected, including any support they need for day-to-day activities. The information from patients will be linked to hospital, GP, and social care records to create a fuller picture of the impact of musculoskeletal conditions on patients’ lives. This can inform local planning and government policy for social care.

Work package 1.2 Develop an algorithm to identify patients diagnosed with axial Spondyloarthritis (axSpA)

Axial Spondyloarthritis (axSpA), is a form of inflammatory arthritis affecting the spine which occurs in around 1 in 200 of the UK adult population; the average age that symptoms start is 24. The UK has a long average delay of 8.5 years between first symptoms appearing and a diagnosis being given. AxSpa significantly impacts on quality of life and ability to function, and this delay in diagnoses and treatment can result in irreversible damage. Finding ways to diagnose axSpA earlier is therefore a high priority.

Using  data from patients’ GP records we will work with a company, IQVIA*, to develop an algorithm (a set of rules) that will predict if a patient will be diagnosed with axSpA at the hospital rheumatology clinic given their pattern of GP visits. We will do this by linking patients’ GP and hospital records to see if the predictions are true. If the algorithm is found to work effectively, we will look at how this could be used to identify patients with potentially undiagnosed axSpA in GP surgeries, who could then be referred earlier to the hospital clinic where a diagnosis of axSpA will be considered by a rheumatologist.

*IQVIA is a private company experienced in working with patient level healthcare data to diagnose patients earlier.

Work package 1.3 Safety and effectiveness of analgesics

We will look at the use of opioids in people with musculoskeletal and other conditions (except for cancer). We will compare the characteristics of hospital patients prescribed low, medium and high dose opioids, and estimate how likely it is for patients leaving hospital to return to the care of their GP with treatments having started, stopped, or the dose changed. We will evaluate how common high-risk opioid prescribing and potential association with hospital admission is in older patients.

We will also ask a sample of musculoskeletal patients from Salford Royal hospital about their ongoing use of over-the-counter medications such as CBD oil. This will help to understand the benefits and harms relating to the use of different medications, which could better inform shared decision-making for doctors and patients, national prescribing guidelines and GP prescribing practices, and provide information on the benefits and harms of opioids for patient organisations and musculoskeletal charities to share.

Workstream 2: Data Collection, Access and Processing

Work package 2.1 Generating structured data from outpatient clinic letters using text-mining

Arthritis and other musculoskeletal diagnoses in patients are not recorded on inpatient records in hospital outpatient clinics, yet they are a vital piece of the data ‘jigsaw’. Diagnoses are included in letters sent to patients following visits to the rheumatology clinic. To be able to use this information for research, it needs to be extracted from the letter. Rather than manually reading each letter, a computer can read and extract the data using a technique called text-mining. It can then be linked to other datasets, for example patients’ hospital and GP records, for use in health research.

Similarly, we will use text-mining to extract information about opioid use before being admitted to hospital from a separate document, called the Medicines Reconciliation document.

Data about diagnoses and opioid use will feed into research about how common arthritis and other musculoskeletal conditions are, and the use of opioid medication when moving from hospital to GP care.

Work package 2.2 Collecting structured Electronic Health Record information

We will look at how data is recorded in the Rheumatology clinic at Salford Royal. We will then propose some solutions for collecting data during patient consultations in a way that helps inform the planning and delivery of the clinic and doesn’t add extra work for the doctor. We will report on what gets in the way, and what helps, this way of collecting data.

Work package 2.3 Collecting Patient-Generated Health Data (PGHD) for musculoskeletal research

In discussion with Salford Royal musculoskeletal patients and healthcare practitioners, we will develop a web-based questionnaire so that patients can share their experience of:
1. Practical help and care provided by family, friends and neighbours.
2. Use of opioid and over-the-counter medication, including benefits and side effects.
This information from patients will be linked to GP, hospital, and social care datasets to carry out the research in work packages 1.1 and 1.3.

The questionnaire will be sent to 60 patients to be completed once every two weeks for six months, after which we will have discussions with the people who took part. As well as providing vital information in the data ‘jigsaw’, patients’ data and feedback will help us to understand people’s views of providing new data for research in this way, and how easy it is to do. This information is rarely collected in appointments, so collecting this directly from patients may help us to answer important questions about arthritis and musculoskeletal conditions, which may help to provide information important for their care, and for use in research.

Work package 2.4 Social care data pilot

We will look at what data is held locally about adult social care, how to access the data for research and link it to hospital or GP patient records, or the patient data collected in this project. If we are successful in this, we will use the information to help answer questions about the impact of musculoskeletal disease on people’s lives, and their use of care services.

Workstream 3: Maintaining Public Trust

Work package 3.1 Maintaining Public Trust

This work focuses on understanding and building public and patient trust in health data sharing for research which aims to improve diagnosis, treatment and services for people with musculoskeletal conditions.

It is important to us that we speak with, and listen to the views of, people whose health data is being used. Consequently, the people we talk to will live in Salford, or be treated at Salford Royal hospital’s Rheumatology clinic. 

We will seek people’s views on health data sharing, including how data is kept safe, and how we might communicate more widely with patients and the public about data sharing. Working with design agency, True North, we will develop and test ways of talking with the wider public in ways that will help build their trust in data sharing for musculoskeletal research.

Work package 3.2 Sustainability and scalability

We want to make sure that the learning from collecting information from patients and linking different datasets is shared and used by other healthcare providers, and adopted by policy-makers. We will identify and work with people who can help this happen. This includes working with patient organisations, such as Versus Arthritis, to make sure that our research addresses the most important gaps about musculoskeletal conditions, and therefore has the maximum impact on patients’ lives.

We will evaluate how successfully we have done this, and what difference our research has made.

Meet the team

Prof Will Dixon

Prof Will Dixon is the Principal Investigator for the Jigsaw programme with expertise in rheumatology (clinically active), epidemiology and digital health.

As Director of the Centre for Epidemiology Versus Arthritis he has experience of overseeing a wide range of parallel, complex projects and programmes.

Prof William Dixon | The University of Manchester

Louise Cook

Louise Cook is the Jigsaw Programme Manager. 

Louise manages and coordinates the overall delivery of the Jigsaw programme and has previous experience of working on digital health epidemiology projects.

Louise Cook I The University of Manchester

Prof John McBeth

Prof John McBeth leads workstream 1: Clinical Research Questions and oversees the activity within each associated work package. John is Deputy Director of the Centre for Epidemiology Versus Arthritis. Prof John Mcbeth | The University of Manchester

Dr Jenny Humphreys

Dr Jenny Humphreys leads work package 1.1: Understanding the frequency and impact of rheumatic and MSK conditions in Salford. Jenny is a practising rheumatologist at Manchester Royal Infirmary.

Dr Jennifer Humphreys MRCP, PhD | The University of Manchester

Dr Mark Lunt

Dr Mark Lunt contributes to the biostatistics element of work package 1.1: Understanding the frequency and impact of rheumatic and musculoskeletal conditions in Salford.

Dr Mark Lunt | The University of Manchester

Dr Benjamin Brown

Dr Benjamin Brown leads on the health informatics element of work package 1.2 Developing an algorithm to identify patients diagnosed with axial Spondyloarthritis (axSpA).

Dr Benjamin Brown MRCGP, MSc, MPH, PhD, FFCI | The University of Manchester

Dr Meghna Jani

Dr Meghna Jani leads work package 1.3, looking at the safety and effectiveness of analgesics.

Dr Meghna Jani MRCP MSc PhD | The University of Manchester

Dr Belay Birlie Yimer

Dr Belay Birlie Yimer

Research Associate (Epidemiology) for workstream 1: Clinical Research Questions.

Belay conducts analysis of health data in work packages 1.1 and 1.3 about the frequency and impact of musculoskeletal conditions and the effectiveness and safety of analgesics.

Dr Belay Birlie Yimer | The University of Manchester

Prof Niels Peek

Prof Niels Peek leads workstream 2: Data Collection, Access and Processing and oversees the activity within each associated work package.  Niels is also the Director of the Christabel Pankhurst Institute for Health Technology Research and Innovation.

Prof Niels Peek MSc, PhD | The University of Manchester

Prof Goran Nenadic

Prof Goran Nenadic leads work package 2.1: Generating structured data from outpatient clinic letters using text-mining.

Prof Goran Nenadic | The University of Manchester

Prof Dawn Dowding

Prof Dawn Dowding leads work package 2.2: Collecting structured Electronic Health Record information.

Prof Professor in Clinical Decision Making Dawn Dowding | The University of Manchester

Dr Sabine van der Veer

Dr Sabine van der Veer leads work package 2.3: Collecting Patient-Generated Health Data (PGHD) for musculoskeletal research.

Dr Sabine van der Veer | The University of Manchester

Dr Paul Clarkson

Dr Paul Clarkson leads work package 2.4: Social care data pilot.

Dr Paul Clarkson PhD, MSc, BA (Hons), CQSW | The University of Manchester

Dr Judith Jeyafreeda Andrew

Dr Judith Jeyafreeda Andrew

Research Associate in Healthcare and Text Analytics for work package 2.1: Generating structured data from outpatient clinic letters using text-mining.

Judith will support the development of text-mining methods to extract structured information from outpatient letters to help answer clinical questions.

Dr Judith Andrew | The University of Manchester

Warren Del-Pinto

Warren Del-Pinto

Research Associate supporting work package 2.1: Generating structured data from outpatient clinic letters using text-mining.

Mr Warren Del-Pinto | The University of Manchester

Prof Caroline Sanders

Prof Caroline Sanders leads workstream 3: Public Trust – understanding and building public and patient trust in health data sharing and oversees the activity within each associated work package.

Prof Caroline Sanders RGN/RSCN, BA hons, MSc, PhD | The University of Manchester

Prof Søren Holm

Prof Søren Holm leads on the law, ethics and governance element of work package 3.1: Public Trust.

Prof Søren Holm | The University of Manchester

Dr Charlotte Sharp

Dr Charlotte Sharp leads work package 3.2: Sustainability and scalability, which aims to help the whole JIGSAW programme ensure that the research questions and methodology are as relevant to its end users as possible, to try to scale up and sustain the outcomes, and to try to capture the impact of this work across the whole programme.

Dr Charlotte Sharp | The University of Manchester

Dr Susan Moschogianis

Susie is a qualitative researcher reviewing evidence on what makes Electronic Health Record systems easy or difficult to use (work package 2.2), and what helps or gets in the way of health professionals collecting high quality patient information (work package 2.3). 

 

Ramiro Bravo

Dr Ramiro Bravo is Digital Health Data Manager at The University of Manchester.

Lucy Njoki Njuki

Lucy Njoki Njuki research assistant in a data science capacity at The University of Manchester on data wrangling of primary and secondary health data for the study of health outcomes of patients with arthritis.

Dr Darryl Bourke

Dr Darryl Bourke is a research assistant in a data science capacity at The University of Manchester on data wrangling of primary and secondary health data for the study of health outcomes of patients with arthritis.

Dr Elaine Mackey

Dr Elaine Mackey

Research Information Governance Manager provides information governance support and advice across the Jigsaw programme and the Centre for Epidemiology. 

Dr Elaine Mackey | The University of Manchester

Rachel Heron

Rachel Heron  

Research Information Governance Officers provides information governance support and advice across the Jigsaw programme and the Centre for Epidemiology. 

Dr Zainab Yusuf

Dr Zainab Yusuf

Research Associate in Qualitative Research for the Public Trust workstream.

Zainab is a qualitative researcher working on developing and sustaining public trust in health data sharing for people with MSK.  Zainab also works with a number of patient and public involvement (PPI) groups to obtain input and feedback from diverse groups and communities throughout the research.

Dr Zainab Yusuf | The University of Manchester

Dr Stephanie Lyons

Dr Stephanie Lyons

Research Associate in Qualitative Research workstream 2: Data Collection, Access and Processing.

Stephanie is a qualitative researcher reviewing evidence on what makes Electronic Health Record systems easy or difficult to use (work package 2.2), and what helps or gets in the way of health professionals collecting high quality patient information (work package 2.3). 

Dr Stephanie Lyons | The University of Manchester

Ginny Mitchell

Ginny Mitchell

Research Project Administrator

Public contributors

Joyce Fox

Joyce Fox

Patient and Public Involvement and Engagement (PPIE) lead for Jigsaw and the Centre for Epidemiology Versus Arthritis with over 8 years of experience in PPIE roles. 

Jane Taylor

Public contributor working with the Patient-Generated Health Data (PGHD) work package in workstream 2.

Owen Power

Owen Power

Public contributor part of the Public Advisory Group in workstream 3

Jennifer-Anne Smith

Jennifer-Anne Smith

Public contributor part of the Public Advisory Group in workstream 3

Jennifer-Anne Smith has various conditions and disabilities, including early onset arthritis, M.E and Fibromyalgia.  She is CEO of a local charity in Salford and a regular volunteer for various organisations covering a range of local groups.

Russ Cowper

Russ Cowper

Public contributor part of the Public Advisory Group in workstream 3

Russ Cowper has Psoriatic Arthritis and does advocacy work with various organisations such as the Psoriasis Association, Britpact and Innovation Health Manchester.

Katarzyna (Katie) Przybylska

Katarzyna (Katie) Przybylska

Public contributor part of the Public Advisory Group in workstream 3

Jav Rehman

Jav Rehman

Public contributor part of the Public Advisory Group in workstream 3

Jav is extremely passionate about equality.  Using his lived experience he aims to amplify the voice of users across platforms including: the NHS, councils, charities, universities, professional associations and other public services to ensure equality is embedded across services.

Partners

Northern Care Alliance NHS Foundation Trust (NCAFT)

Northern Care Alliance NHS Foundation Trust (NCAFT) is one of the largest NHS organisations in the country and was established to provide safe, reliable and high quality care. We provide hospital, community and social care services to around 1 million people in Bury, Oldham, Rochdale and Salford, and for wider populations in Greater Manchester and beyond. We are supporting the Assembling the Data Jigsaw team by facilitating access to clinical datasets via our secure research data environment and supporting the recruitment of study participants.

Website: www.ncaresearch.org.uk/

Twitter: @NCAResearchNHS

Get in touch

If you would like to get involved in our research, or if you have any questions about the Assembling the Data Jigsaw project, contact us at jigsaw@manchester.ac.uk.

This project has been funded by:

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