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AnteayerBMJ Open

Using digital tools in clinical, health and social care research: a mixed-methods study of UK stakeholders

Por: Clohessy · S. · Arvanitis · T. N. · Rashid · U. · Craddock · C. · Evans · M. · Toro · C. T. · Elliott · M. T.
Objective

The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools.

Design

Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically.

Setting, participants

To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020–2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8).

Results

Six themes were identified in the qualitative interviews: ‘definition of a digital tool in clinical research’; ‘impact of the COVID-19 pandemic’; ‘perceived benefits/drawbacks of digital tools’; ‘selection of a digital tool’; ‘barriers and overcoming barriers’ and ‘future digital tool use’. The context of each theme is discussed, based on the interview results.

Conclusions

Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.

Development and application of simulation modelling for orthopaedic elective resource planning in England

Por: Harper · A. · Monks · T. · Wilson · R. · Redaniel · M. T. · Eyles · E. · Jones · T. · Penfold · C. · Elliott · A. · Keen · T. · Pitt · M. · Blom · A. · Whitehouse · M. R. · Judge · A.
Objectives

This study aimed to develop a simulation model to support orthopaedic elective capacity planning.

Methods

An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians.

Results

A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60%, allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 75% reduces bed utilisation to below 40%, even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app.

Conclusions

The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties.

A novel, multidomain, primary care nurse-led and mHealth-assisted intervention for dementia risk reduction in middle-aged adults (HAPPI MIND): study protocol for a cluster randomised controlled trial

Por: Cross · A. J. · Geethadevi · G. M. · Magin · P. · Baker · A. L. · Bonevski · B. · Godbee · K. · Ward · S. A. · Mahal · A. · Versace · V. · Bell · J. S. · Mc Namara · K. · O'Reilly · S. L. · Thomas · D. · Manias · E. · Anstey · K. J. · Varnfield · M. · Jayasena · R. · Elliott · R. A. · Lee
Introduction

Middle-aged multidomain risk reduction interventions targeting modifiable risk factors for dementia may delay or prevent a third of dementia cases in later life. We describe the protocol of a cluster randomised controlled trial (cRCT), HAPPI MIND (Holistic Approach in Primary care for PreventIng Memory Impairment aNd Dementia). HAPPI MIND will evaluate the efficacy of a multidomain, nurse-led, mHealth supported intervention for assessing dementia risk and reducing associated risk factors in middle-aged adults in the Australian primary care setting.

Methods and analysis

General practice clinics (n≥26) across Victoria and New South Wales, Australia, will be recruited and randomised. Practice nurses will be trained to implement the HAPPI MIND intervention or a brief intervention. Patients of participating practices aged 45–65 years with ≥2 potential dementia risk factors will be identified and recruited (approximately 15 patients/clinic). Brief intervention participants receive a personalised report outlining their risk factors for dementia based on Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI) scores, education booklet and referral to their general practitioner as appropriate. HAPPI MIND participants receive the brief intervention as well as six individualised dementia risk reduction sessions with a nurse trained in motivational interviewing and principles of behaviour change, a personalised risk reduction action plan and access to the purpose-built HAPPI MIND smartphone app for risk factor self-management. Follow-up data collection will occur at 12, 24 and 36 months. Primary outcome is ANU-ADRI score change at 12 months from baseline. Secondary outcomes include change in cognition, quality of life and individual risk factors of dementia.

Ethics and dissemination

Project approved by Monash University Human Research Ethics Committee (ID: 28273). Results will be disseminated in peer-reviewed journals and at healthcare conferences. If effective in reducing dementia risk, the HAPPI MIND intervention could be integrated into primary care, scaled up nationally and sustained over time.

Trial registration number

ACTRN12621001168842.

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