Benjamin Brown

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The University of Manchester
Country flagUnited Kingdom

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Recent Grants

Grant: Close

Personalising renal function monitoring and interventions in people living with heart failure: RENAL-HF

Open Date: 2021-10-01

Close Date: 2026-09-30

Grant: Close

Cluster randomised trial to improve antibiotic prescribing in primary care: individualised knowledge support during consultation for general practitioners and patients

Open Date: 2020-12-01

Close Date: 2023-11-30

Grant: Close

The JPIAMR Primary Care Antibiotic Audit and Feedback Network (PAAN): An international collaboration on best practices for the delivery of antibiotic prescribing feedback to community clinicians using behavioural science

Open Date: 2020-11-01

Close Date: 2022-10-31

Grant: Close

Assembling the data jigsaw: powering robust population research in musculoskeletal disease

Open Date: 2020-09-01

Close Date: 2024-03-01

Grant: Close

Better Care North Partnership

Open Date: 2020-05-01

Close Date: 2023-11-01

Articles (10)

Year:

2025

Year:

2025

Year:

2025

Introduction Long-term conditions are a major burden on health systems. One way to facilitate more research and better clinical care among patients with long-term conditions is to collect accurate data on their daily symptoms (patient-generated health data) using wearable technologies. Whilst evidence is growing for the use of wearable technologies in single conditions, there is less evidence of the utility of frequent symptom tracking in those who have more than one condition. Aims To explore patient views of the acceptability of collecting daily patient-generated health data for three months using a smartwatch app. Methods Watch Your Steps was a longitudinal study which recruited 53 patients to track over 20 symptoms per day for a 90-day period using a study app on smartwatches. Semi-structured interviews were conducted with a sub-sample of 20 participants to explore their experience of engaging with the app. Results In a population of older people with multimorbidity, patients were willing and able to engage with a patient-generated health data app on a smartwatch. It was suggested that to maintain engagement over a longer period, more ‘real-time’ feedback from the app should be available. Participants did not seem to consider the management of more than one condition to be a factor in either engagement or use of the app, but the presence of severe or chronic pain was at times a barrier. Conclusion This study has provided preliminary evidence that multimorbidity was not a major barrier to engagement with patient-generated health data via a smartwatch symptom tracking app.

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2022

Background National clinical audit programmes aim to improve patient care by reviewing performance against explicit standards and directing action towards areas not meeting those standards. Their impact can be improved by (1) optimising feedback content and format, (2) strengthening audit cycles and (3) embedding randomised trials evaluating different ways of delivering feedback. Objectives The objectives were to (1) develop and evaluate the effects of modifications to feedback on recipient responses, (2) identify ways of strengthening feedback cycles for two national audits and (3) explore opportunities, costs and benefits of national audit participation in a programme of trials. Design An online fractional factorial screening experiment (objective 1) and qualitative interviews (objectives 2 and 3). Setting and participants Participants were clinicians and managers involved in five national clinical audits – the National Comparative Audit of Blood Transfusions, the Paediatric Intensive Care Audit Network, the Myocardial Ischaemia National Audit Project, the Trauma Audit & Research Network and the National Diabetes Audit – (objective 1); and clinicians, members of the public and researchers (objectives 2 and 3). Interventions We selected and developed six online feedback modifications through three rounds of user testing. We randomised participants to one of 32 combinations of the following recommended specific actions: comparators reinforcing desired behaviour change; multimodal feedback; minimised extraneous cognitive load for feedback recipients; short, actionable messages followed by optional detail; and incorporating ‘the patient voice’ (objective 1). Main outcome measures The outcomes were intended actions, including enactment of audit standards (primary outcome), comprehension, user experience and engagement (objective 1). Results For objective 1, the primary analysis included 638 randomised participants, of whom 566 completed the outcome questionnaire. No modification independently increased intended enactment of audit standards. Minimised cognitive load improved comprehension (+0.1; p = 0.014) and plans to bring audit findings to colleagues’ attention (+0.13, on a –3 to +3 scale; p = 0.016). We observed important cumulative synergistic and antagonistic interactions between modifications, participant role and national audit. The analysis in objective 2 included 19 interviews assessing the Trauma Audit Research Network and the National Diabetes Audit. The identified ways of strengthening audit cycles included making performance data easier to understand and guiding action planning. The analysis in objective 3 identified four conditions for effective collaboration from 31 interviews: compromise – recognising capacity and constraints; logistics – enabling data sharing, audit quality and funding; leadership – engaging local stakeholders; and relationships – agreeing shared priorities and needs. The perceived benefits of collaboration

Year:

2022

Year:

2022

Collaborators (14)

Robbie Foy

University of Leeds

UNITED KINGDOM
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Fiona Stevenson

University College London

UNITED KINGDOM
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John McBeth

The University of Manchester

UNITED KINGDOM
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Carl Wikberg

University of Gothenburg

SWEDEN
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Akke Vellinga

Professor Epidemiology

Dublin City University

IRELAND
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Sabine van der Veer

Senior Lecturer

The University of Manchester

UNITED KINGDOM
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Dawn Dowding

The University of Manchester

UNITED KINGDOM
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David Wong

The University of Manchester

UNITED KINGDOM
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Tom Blakeman

The University of Manchester

UNITED KINGDOM
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Jan Verbakel

University of Oxford

UNITED KINGDOM
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Christopher Armitage

The University of Manchester

UNITED KINGDOM
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Niels Peek

Professor of Data Science and Healthcare Improvement

University of Cambridge

UNITED KINGDOM
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Syed Mustafa Ali

The University of Manchester

UNITED KINGDOM
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Jung Yin Tsang

The University of Manchester

UNITED KINGDOM
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