CONCOMITANT PRIMARY PREVENTION OF MULTIPLE CHRONIC DISEASES THROUGH DATA-DRIVEN APPROACHES MOBILISING POPULATION-WIDE LONGITUDINAL HEALTH RECORDS

RESEARCH QUESTION What is the potential for data-driven, health-record-based approaches to enhance the primary prevention of multiple chronic diseases?

BACKGROUND Population ageing, and its associated increase in chronic diseases, presents a major challenge for health and healthcare.

Primary prevention is key to improved health and NHS sustainability, but prevailing approaches typically consider only one-disease-at-a-time and fail to exploit the full potential of information in population-wide longitudinal e-health records for prevention.

My research will mobilise major recent advances in data science and e-health record access for ~56M people in England, with the aim of securing transformative improvements in the concomitant prediction and primary prevention of multiple major chronic diseases. This work will address inter-related unmet needs in relation to efficiency, equity and precision of prevention.

I will develop and evaluate pragmatic joined-up approaches involving digitalised, accessible and implementable tools for monitoring the inter-related risk profiles of multiple chronic diseases.

Combining risk profiles to formulate evidence-based primary prevention strategies for targeting the right interventions at the right time to the people who need them most, this work will optimise prevention in fresh ways, with direct implications for NHS Health-Check and other programmes.

AIMS AND OBJECTIVES Aim-A: To develop digitalised, accessible and implementable tools for monitoring risk of multiple chronic diseases over time Objective-A1: Adapt and apply analytical methods to develop and validate risk prediction tools for multiple chronic diseases, leveraging longitudinal e-health records Objective-A2: Create standardised and personalised risk profiles for multiple chronic diseases, incorporating estimated causal effects for recommended and emerging interventions Objective-A3: Through co-production with stakeholders, translate chronic disease risk profiles into digitalised, accessible and implementable tools for clinical practice Aim-B: To improve targeting of preventative interventions to simultaneously reduce risks of multiple chronic diseases and narrow health inequalities Objective-B1: Formulate evidence-based primary prevention strategies to identify the appropriate time point and type of preventative intervention Objective-B2: Evaluate the impact, efficiency, cost-effectiveness and equity gain of improved targeted primary prevention strategies Objective-B3: Design proof-of-concept randomised controlled trials in primary care to evaluate the impact of novel strategies on uptake of, and adherence to, preventive interventions and reduction in disease risks METHODS Public and patient involvement and engagement will be embedded in the whole research lifecycle.

Statistical modelling will account for the ways different people access healthcare, and incorporate causal effects of preventive interventions.

For translation, I will apply the MRC's 'Framework for the development and evaluation of complex interventions' and deploy user-centred design methods to optimise design and theory, ensure accessibility, operationalise commitments to diversity and inclusivity, and facilitate effective implementation for clinical practice.

ANTICIPATED IMPACT AND DISSEMINATION Outputs will inform policy-makers (e.g., public health agencies, Integrated Care Boards, NICE technology appraisal committees) on efficient and cost-effective strategies for monitoring, risk assessing and managing chronic diseases, and which support the reduction of health inequalities.

Ultimately, adopting optimal strategies will lead to fewer chronic diseases and healthier lives, aligning with the NHS ambition to 'help prevent over 150,000 heart attacks, strokes and dementia cases over the next 10-years'22.