Bringing NHS data analysis into the 21st century

Goldacre, Ben; Bardsley, Martin; Benson, Tim; Cheema, Kate; Chinn, R. H.; Coughlan, Ellen; Dougan, Sarah; Farr, Marc; Hawkins, Loraine; Jonas, Adrian; Kinnear, Andy; Mcinnes, Morag; Mohammed, Mohammed Amin; Morton, Caroline; Pasumarthy, Rahul; Pettinger, N; Rowland, Ben; Sebire, Neil J.; Stroner, Paul; Tennison, Jeni; Warnakula, Samantha; Watson, Oliver; Wright, E Hassel; Young, H.; Morley, Jessica

doi:10.1177/0141076820930666

Cited by 13 publications

(8 citation statements)

References 2 publications

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“…Taken literally, part of academia's primary purpose is to be an “academy” to train the future workforce to meet the needs of society. Training a data science literate workforce is urgently needed to meet the increasing move toward data‐driven translational precision medicine 86,87 . Academia also has the flexibility to take greater risks, due to having fewer constraints or less influence from external market forces.…”

Section: Key Recommendations In Using Data Science To Improve Medical...mentioning

confidence: 99%

Artificial intelligence for dementia drug discovery and trials optimization

Doherty,

Yao,

Khleifat

et al. 2023

Alzheimer's & Dementia

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Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi‐disciplinary approach can promote data‐driven decision‐making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation.

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Section: Key Recommendations In Using Data Science To Improve Medical...mentioning

confidence: 99%

Artificial intelligence for dementia drug discovery and trials optimization

Doherty,

Yao,

Khleifat

et al. 2023

Alzheimer's & Dementia

View full text Add to dashboard Cite

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“…In terms of the care of people with diabetes, the relevance of big data is in relation to research, routine clinical management and monitoring, image reporting and a move to more self‐management using connected technologies. To date there has been an emphasis on the research benefits but the concept of coalface analytics needs to rise up the agenda 7 . This comprises many aspects of care to improve its quality, safety and cost effectiveness.…”

Section: Research Tool or Enhanced Clinical Carementioning

confidence: 99%

“…To date there has been an emphasis on the research benefits but the concept of coalface analytics needs to rise up the agenda. 7 This comprises many aspects of care to improve its quality, safety and cost effectiveness. It will also ensure that set key performance indicators are met.…”

Section: Research Tool or Enhanced Clinical Carementioning

confidence: 99%

Diabetes care: is big data the future?

Begg

2022

Practical Diabetes

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“…We also have a National Health Service that has developed computerised medical records for use in general practices on a population of around 67 million people. 14 , 15 These electronic medical records provide longitudinal data on people’s health and medical experiences and can be used to monitor vaccine uptake by population group. Early results from UK studies show a lower uptake of COVID-19 vaccines among people from ethnic minority groups and people living in poorer parts of the UK.…”

Section: Addressing Evidence Gapsmentioning

confidence: 99%

Assessing the long-term safety and efficacy of COVID-19 vaccines

2021

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We have read and understood the JRSM policy on declaration of interests. MP is a former Senior Scientific Adviser of the European Medicines Agency. AM and MM declare that that they have no competing interests.Funding: This article is part of the COVID-19 work programme of the NIHR Applied Research Collaboration NW London. The views expressed in this article are those of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency, its Scientific Committees, other Regulatory Agencies, the NIHR or the Department of Health and Social Care.

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Bringing NHS data analysis into the 21st century

Cited by 13 publications

References 2 publications

Artificial intelligence for dementia drug discovery and trials optimization

Artificial intelligence for dementia drug discovery and trials optimization

Diabetes care: is big data the future?

Assessing the long-term safety and efficacy of COVID-19 vaccines

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