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Wolfson Institute of Population Health

SPCR research

QMUL applicant Dr Ratna Sohanpal

Summary Chronic obstructive pulmonary disease (COPD) is a public health problem, associated with socio-economic deprivation with significant burden to health services and patients and high morbidity and mortality.  There is a move to embed remote technologies into all areas of medicine including, respiratory medicine. However, there is need to understand how to harness the opportunities available via technology, how to identify and address the challenges and how to recognise when remote delivery may be inadequate or inappropriate.

Aims

  • To explore among patients with COPD and their carers, their views and experiences of remote care to understand what worked well, what were the challenges for them and to ask how their experience of care could be improved.
  • To explore among health care professionals, their views and experiences of providing different types of care remotely  to understand what worked well, what were the challenges and how their experience of providing care could be improved.

Method Qualitative research comprising of in-depth interviews among patients with COPD, their carers and health care professionals. A topic guide informed by the literature sought to explore:

  • type of care offered/received via remote delivery and types of remote modalities available
  • experience of remote care and challenges encountered, and possible solutions
  • preferences for different types of remote care, suitability for which patients, in what circumstances and
  • identification of resources, training, and support needs for health care professionals

Targets for reducing health inequalities and improved mortality and morbidity 

  • The study is focusing on an underserved population, chronic obstructive pulmonary disease (COPD) that are relatively disadvantaged overall.
  • The study is using qualitative methodology to explore perspectives on the type of remote care that is offered/received, experience of remote care and challenges encountered and possible solutions, preferences for future care delivery and identification of resources, training and support among patients with COPD, their carers’ and health care professionals. The methodology will help us to identify what worked well, what did not work well and how health care delivery might be improved for people with COPD.
  • The study will enable us to better understand WHO remote care is appropriate for; WHEN is it appropriate to provide remote care; WHAT type of care can be given to patients remotely that is acceptable to patients and professionals; WHAT training and support might be given to deliver effective care and WHAT support can be given to patients to access care as per their need. 

QMUL Co-applicant Professor Steph Taylor Dr Liz Steed  Dr Nina Fudge

Lead institution Queen Mary University London

QMUL applicant Dr Grace Okoli 

Summary During the COVID-19 pandemic two-week wait referrals in England, UK, were reported to have decreased by up to 84%. This has been attributed to the reallocation of health resources to address prevention and treatment of those at risk or affected by COVID-19. There has also been public apprehension to present to their general practice with symptoms that can be associated with cancer during this time.

Aim The aim of this study is to understand how the incidence of TWW referrals were affected during the pandemic and isolate key, person- and practice- level, factors that could reinforce the resilience of this service.

Study design Retrospective cohort study using EMIS Web primary care data. The data will be comprised of records of approximately 60 million patients registered in approximately 2,000 general practices in the UK  and comparison will be made with an multi-ethnic community in the London Borough of  Lambeth.

Targets for reduced inequality and reduced mortality and morbidity

  • Health inequalities exist within communities in the UK. This study uses primary care data to assess factors that are associated with these inequalities, specifically as they relate to the early diagnosis of diseases such as cancer.  
  • Multimorbidity will be determined within these UK communities using the Charlson index, it performs well as a predictor of mortality in data coded in primary care (Read/SNOMED-CT) which will be the initial data source used for this study. Our study outcomes will highlight areas of improvement that are required in the health care delivered to these communities.

QMUL applicant Hajar Hajmohammadi 

Summary To investigate the association between short and long-term air pollution exposure and the risk of developing SARS-CoV-2 infection and COVID-19 disease in the UK. 

Aim to understand the relationship between air quality exposure and the risk of developing COVID-19 at the individual level in the UK. We will develop a multivariate logistic regression model to analyse the associations between long-term (10 years) and short-term (daily) exposure to two types of air pollution, Nitrogen dioxide (NO2) and PM2.5, and risk of SARS-CoV-2 seropositivity. 

Methods Two main datasets used for this study are: 1) Longitudinal population-based cohort study of coronavirus disease in the UK population (COVIDENCE UK) and 2) high resolution annual average NO2 and PM2.5 concentrations. COVIDENCE UK is a nationwide population-based cohort study of coronavirus disease (COVIDENCE UK), launched on 1st May 2020. Participants were invited via a national media campaign to complete an online baseline questionnaire to capture information on potential symptoms of COVID-19 experienced.

Targets for reduced inequality, morbidity and mortality 

  • Providing evidence of the harmful effects of both long and short-term air pollution exposure on raising the risk of respiratory disease   
  • Examining how people with respiratory conditions may be affected by the COVID-19 pandemic indirectly
  • Motivating municipal leaders and decision-makers to take air pollution more seriously

QMUL Co-applicant: Chris Griffiths

lead institution UCL

Summary The NHS Long-Term Plan is underpinned by expectations of collaborative and integrated working in primary care. The opportunities and challenges presented by this policy’s expectations for collaborative and integrated working in practice are relatively unexplored. This review focuses on the working relationship between Community Pharmacy (CP) and General Practice (GP). 

Aims To understand how, when and why working arrangements between Community Pharmacy and General Practice can provide the conditions necessary for optimal communication, decision-making, and collaborative and integrated working.

Method Over 15 months researchers will conduct a Realist Review which brings together evidence such as policy documents, NICE guidance, research documents, and debate articles to understand what helps and hinders collaborative and integrated work between Community Pharmacy and GPs. They will conducted a initial scoping review to identify a significant field of potentially relevant information focused mainly on the UK. Researchers will examine whether, why, how and to what extent CP-GP collaborative and integrated working practices support effective and equitable care delivery for patients. 

Targets for reducing inequalities mortality and morbidity 

  1. Unnecessary polypharmacy & overprescribing carry an associated morbidity (e.g. 10% hospitalisations of older adults are related to adverse drug reactions). Our study population comprises patients (>65y) who are prescribed at least 10 medications.
  2. DHSE report on overprescribing: polypharmacy increases with relative socioeconomic deprivation; thus is an issue relevant to health inequalities. Two of our three study sites were in urban areas with high levels of deprivation.
  3. Our work is investigating what is happening interactionally between clinicians and patients during medication reviews in primary care (for older adults >65y taking >10 medicines). By investigating what is happening in medication reviews, we explore what may be sustaining polypharmacy in primary care in older adults.

QMUL Collaborator Nina Fudge 

Lead institution Manchester University

Summary In recent years, the number of patients and their healthcare needs have grown faster than the number of General Practitioners (GPs). This has led to escalating workloads in general practice that have a negative impact on GP morale, well-being and recruitment and retention. Nationally reported data on appointments and other health outcomes convey only a partial account of GP work; many tasks cannot be captured in these datasets and the impact of responsibility for them  is poorly understood.

In this study, we propose to qualitatively explore the nature and impact of 'hidden' GP work - i.e. work that escapes capture in existing datasets and that may not be considered as a necessary part of GP workloads. We will to engage with GPs and practice staff to refine qualitative research methods suitable for investigating the hidden work of GPs, look at the nature, extent and impact of GPs’ hidden work, and develop conversations about positive change in working practices.

Aims 

1) to work with GPs and practice staff to identify which research methods are feasible, acceptable and productive in shedding light on hidden work,

2) to use these methods to discover the nature and impact of GPs’ hidden work, and

3) to invite GPs and practice staff to participate in a reflexive workshop for collective learning with potential for quality improvement. 

Methods  This qualitative study will include interviews with GPs, observations of the work GPs do which patients do not usually see, and other/innovative methods of gathering data. In each practice, we will arrange a reflexive workshop with GPs and staff members. Dates of study: 1 June 2022 -31 July  2023

Targets to reduce inequalities, mortality and morbidity 

  • The focus of this one-year project is GP workforce. The research thus addresses a serious problem in UK general practice, namely that those populations of patients who most need care are often served by understaffed practices.
  • Identifying the nature of behind-the-scenes work and exploring ways this work could be made more manageable can contribute to GP retention.
  • Retaining GPs is critical for both reducing health inequalities and improving morbidity and mortality.

Research team: Dr Sharon Spooner University of Manchester (CI), Prof Deborah Swinglehurst QMUL (PI/lead at QMUL), Prof John Campbell University of Exeter, Ms Emily Fletcher University of Exeter, Prof Kath Checkland University of Manchester

Lead institution Oxford University

Summary The shift to remote consulting in UK general practice, using phone and video to help with infection control during the COVID 19 pandemic will have lasting impact on how primary care services are provided to patients and the public. At the moment it is unclear how decisions are made about which sort of consulting to use, and how to best organise and deliver these different types of appointment in general practice.

Aims To understand how, when, by whom and why decisions are made to offer different types of appointment and to consider the implications for the future organisation and delivery of general practice and primary care.

Methods The team will work in three practices to collect detailed data about consulting: (i) shadowing  one GP and one receptionist/care navigator (one week) and then other members of the primary care team (second week) in each practice to gain first hand insights into the work they do and the decisions they make about consulting; (ii) talking with practice staff (e.g. receptionists, GPs, practice nurses) to understand their experience of remote consulting and their role in shaping decisions about the type of appointment offered; (iii) homing in on ten patients with complex needs and tracking their consulting activity over the previous 24 months. The team will work with three practices that are already part of the Remote by Default 2 study to collect data. Link to more information

Targets to reduce inequalities, mortality and morbidity 

  • There are concerns that the shift towards increasing use of remote consultations may widen inequities of access for patients in primary care
  • The study will use methods that enable us to see how decisions are made about who gets access and to what kind of consultation
  • One element of the study will focus on patients with complex needs and how they navigate and experience different modes of consultation as part of their care

Lead institutions:  University of Leeds with Queen Mary University, London 

Background Many intra-thoracic cancers remain diagnostic challenges, have similar presentations to other co-morbidities, are sometimes ‘easily missed’ in primary care and are often diagnosed at a late stage as result. However, we know that patients do experience symptoms and have detectable changes in blood and other biomarkers in the time prior to their diagnosis, creating a time window in which imaging or biomarker testing may facilitate earlier diagnosis.

Aims To publish the main findings of the two reviews in high-impact journals and publish a version of the findings for a lay audience. Findings will be disseminated at international conferences. 

Methods To undertake two systematic reviews about detecting intra-thoracic cancers. The first will look at the role of imaging and the second the role of biomarkers in the detection of these cancers in primary care. These reviews will be carried out in parallel, with the Exeter researcher leading on the imaging review and the QMUL researcher leading on the biomarker review. 

Targets to incorporate consideration of  reducing inequalities, mortality and morbidity within this study

  • Our study seeks to Identify novel biomarkers suitable for early detection of Intrathoracic cancers in primary care, thereby aiming to reduce health inequalities as there are currently large differences in stage at diagnosis by geography and other socio-economic factors.
  • As >80% people diagnosed with intrathoracic cancers first present with symptoms in primary care and are diagnosed with late stage disease where curative treatment is not possible, then the findings may contribute to diagnosing more people with lung and other intrathoracic cancers at an earlier stage of their disease where they can be treated with curative intent
  • This will result in improving morbidity and mortality from intrathoracic cancers.

Lead institution Queen Mary University of London

Summary Identification of people infected with blood borne viruses remains a challenge. Up to 1:20 people with HIV remain undiagnosed, and almost half of people with hepatitis B or hepatitis C are unaware of their infection. Health inequalities are widening across societal groups. New approaches are urgently needed to improve identification and specialist referral of people with blood-borne viruses.

Aim To improve identification and referral systems for people with blood-borne virus infections. 

Methods In the first developmental phase

  • Identify and summarise all the research publications describing existing computer risk tools for screening people with blood-borne virus infections
  • Build on the best models to develop a new, more accurate risk prediction tool that can identify those at risk and target an offer to test for multiple infections

In the second evaluative phase

  • Test the accuracy of the risk prediction tool in different populations in the UK; then test the screening model in three or four general practices to feasibility, effectiveness and value for money
  • Develop a peer supporter-led “Failsafe” pathway to help patient engage with secondary care and to receive the best possible treatment
  • Liaise with the government and NHS leaders to disseminate findings, prior to seeking funding for a large-scale national evaluation

Targets to reduce inequalities, morbidity and mortality 

  • Aims to identify people with blood-borne viruses early, as this has been shown to reduce morbidity and mortality.
  • Supports the most vulnerable groups in society - including migrants, people with substance misuse and men who have sex with men - who are most at risk of suffering from these infections.
  • Enables equitable case identification across a variety of societal and geographical regions, ranging from inner city migrant populations to more homogenous rural populations.

QMUL Co-applicants Chris Griffiths John Robson  Dominik Zenner

Lead institution Queen Mary University of London

Summary There is strong interest in the relationship between short-term and long-term air pollution exposure and human health. A variety of studies focus on mortality and hospital admission as a result of long or short-term air pollution exposure. However, less severe health effects such as respiratory conditions requiring primary care management are rarely considered in the literature, likely to be the result of limited access to primary care clinical and prescribing data, despite the major health and economic burden resulting.

Aim To learn more about the link between short-term and long-term air pollution exposure and asthma exacerbations treated in primary care. In addition to investigate how COVID-19 pandemic influenced this connection.

Methods Use data from the longitudinal population-based cohort study of coronavirus disease in the UK population (COVIDENCE UK (https://www.qmul.ac.uk/covidence/)), launched on 1st May 2020, and link those data to the high-resolution (25m x 25m) Nitrogen dioxide (NO2) and fine particle (PM2.5, particles with diameter less than 2.5 mm) outdoor concentrations from a land-use regression model. 

Researchers will estimate the risk of developing COVID-19 infection associated with poor air quality, as well as the extent to which changes in the concentration of NO2 and PM2.5 over the two major lockdown periods modified any adverse association.

Targets to reduce inequalities, morbidity and mortality

  • Providing evidence of the harmful effects of both long and short-term air pollution exposure on raising the risk of respiratory disease   
  • Examining how people with respiratory conditions may be affected by the COVID-19 pandemic indirectly
  • Motivating municipal leaders and decision-makers to take air pollution more seriously

QMUL Co-investigator Dr John Robson and Professor Christopher Griffiths

Lead institution Queen Mary's University of London

Summary Ovarian cancer is the 6th most common cause of death from cancer in UK women. Most ovarian cancers are not detected until the disease is advanced and harder to treat. Ovatools is new age- and CA125-based risk models which estimate the probability of ovarian cancer in primary care. Ovatools exhibited excellent diagnostic performance in internal validation and are validated using external datasets.

Methods

The team proposes to develop a decision analytic model of the ovarian cancer diagnosis and treatment pathway to assess the value of integrating Ovatools in primary care. This analytical framework will relax the homogeneous population assumption in previous health economic assessments of the ovarian cancer pathway used by NICE, and enable integration of patient age, CA125 level and estimated risk considerations informed by their previous work and the linked patient data (i.e. use of further diagnostic tests, stage at cancer diagnosis, subsequent cancer treatment modalities and survival).

Targets to reduce inequalities, morbidity and mortality 

  • Ovatools, developed by our co-PI Dr Garth Funston and co-applicant Prof Fiona Walter, are prediction models that have demonstrated excellent diagnostic performance and could help improve ovarian cancer detection in primary care, which is the key to ensure patients start appropriate treatment in a timely way and thus improve outcomes.
  • This project aims to gather health economic evidence to evaluate cost-effectiveness of using Ovatools in primary care, and therefore would facilitate the adoption of Ovatools and identify the most cost-effective diagnostic pathway in primary care in the UK.
  • Higher deprivation and ethnic minority backgrounds have been linked with later stage at ovarian cancer diagnosis. Through improving ovarian cancer diagnosis, the project would particularly benefit women from higher deprivation and ethnic minority backgrounds and reduce health inequalities in ovarian cancer treatment and mortality.

QMUL Co-investigators  Professor Fiona Walter, Professor Borislava Mihaylova

Lead Institution Queen Mary University of London

Summary Air pollution impairs children’s brain development, increasing risk of behavioural and mental health problems, and harming life chances. We urgently need to find out whether improving air quality can prevent harm to children’s developing brains. In this study the authors seek to exploiting these interventions to address whether reductions in traffic improve various indicators of how well children’s brains work: from response time, to problem solving and memory recall. In addition, the team will look at general mental wellbeing, such as feelings of isolation or anxiety to see how these are affected by poor air quality.

Methods The design is a prospective parallel cohort study, with repeated assessments of:

  1. Cognitive function (annually, at school visits)
  2. Revised Children’s Anxiety and Depression (RCADs) questionnaire annually, by child at cognitive assessment session (5)
  3. Strengths and Difficulties Questionnaire (SDQ), annually by teacher (6)
  4. Child Health Utility questionnaire (CHU9D) completed annually, by parent by post (7)
  5. Coded NHS health record data on mental health and behavioural outcomes

Data extracted from the children’s Early Years Foundation Stage Profile assessments carried out at the end of reception years 

Targets to reduce inequalities, mortality and morbidity

  • This study will investigate the impact of poor air quality on children’s cognitive development. Recent data has indicated that poorer individuals and families are more likely to experience poor air quality.
  • We will investigate whether improving air quality can reverse the adverse health effects of air pollution exposure on the brain.
  • The study will also investigate the impact of air pollution on children’s mental health, focusing on symptoms of anxiety and depression using data collected from parents, teachers, and the children themselves.

QMUL Co-investigator Professor Christopher Griffiths

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