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Adam Steventon

Showing results (31-40 of 57) with videos related to

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BMJ (Clinical Research Ed.)|September 15, 2019
New AI laboratory for the NHSAdam Steventon, Sarah R Deeny, Josh Keith, et al.
BMJ (Clinical Research Ed.)|June 22, 2019
Evaluating the impact of healthcare interventions using routine dataGeraldine M Clarke, Stefano Conti, Arne T Wolters, et al.
BMJ Open|June 14, 2019
Effect of an integrated care pathway on use of primary and secondary healthcare by patients at high risk of emergency inpatient admission: a matched control cohort study in Tower HamletsWill Parry, Arne Timon Wolters, Richard James Brine, et al.
AI and Ethics|November 18, 2021
Ethical funding for trustworthy AI: proposals to address the responsibilities of funders to ensure that projects adhere to trustworthy AI practiceAllison Gardner, Adam Leon Smith, Adam Steventon, et al.
BMC Health Services Research|August 8, 2014
Effect of telehealth on glycaemic control: analysis of patients with type 2 diabetes in the Whole Systems Demonstrator cluster randomised trialAdam Steventon, Martin Bardsley, Helen Doll, et al.
Health Services Research|January 10, 2012
The role of matched controls in building an evidence base for hospital-avoidance schemes: a retrospective evaluationAdam Steventon, Martin Bardsley, John Billings, et al.
Journal of Health Services Research & Policy|February 25, 2012
Overlap of hospital use and social care in older people in EnglandMartin Bardsley, Theo Georghiou, Ludovic Chassin, et al.
BMJ Open|August 14, 2012
Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30)John Billings, Ian Blunt, Adam Steventon, et al.
Clinical Medicine (London, England)|April 9, 2019
Predictors of emergency department attendance following NHS 111 calls for children and young people: analysis of linked dataCicely Robinson, Arne Wolters, Adam Steventon, et al.
Age and Ageing|January 22, 2011
Predicting who will use intensive social care: case finding tools based on linked health and social care dataMartin Bardsley, John Billings, Jennifer Dixon, et al.
Pageof 6

Showing results (31-40 of 57) with videos related to

Sort By:
Pageof 6
BMJ (Clinical Research Ed.)|September 15, 2019
New AI laboratory for the NHSAdam Steventon, Sarah R Deeny, Josh Keith, et al.
BMJ (Clinical Research Ed.)|June 22, 2019
Evaluating the impact of healthcare interventions using routine dataGeraldine M Clarke, Stefano Conti, Arne T Wolters, et al.
BMJ Open|June 14, 2019
Effect of an integrated care pathway on use of primary and secondary healthcare by patients at high risk of emergency inpatient admission: a matched control cohort study in Tower HamletsWill Parry, Arne Timon Wolters, Richard James Brine, et al.
AI and Ethics|November 18, 2021
Ethical funding for trustworthy AI: proposals to address the responsibilities of funders to ensure that projects adhere to trustworthy AI practiceAllison Gardner, Adam Leon Smith, Adam Steventon, et al.
BMC Health Services Research|August 8, 2014
Effect of telehealth on glycaemic control: analysis of patients with type 2 diabetes in the Whole Systems Demonstrator cluster randomised trialAdam Steventon, Martin Bardsley, Helen Doll, et al.
Health Services Research|January 10, 2012
The role of matched controls in building an evidence base for hospital-avoidance schemes: a retrospective evaluationAdam Steventon, Martin Bardsley, John Billings, et al.
Journal of Health Services Research & Policy|February 25, 2012
Overlap of hospital use and social care in older people in EnglandMartin Bardsley, Theo Georghiou, Ludovic Chassin, et al.
BMJ Open|August 14, 2012
Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30)John Billings, Ian Blunt, Adam Steventon, et al.
Clinical Medicine (London, England)|April 9, 2019
Predictors of emergency department attendance following NHS 111 calls for children and young people: analysis of linked dataCicely Robinson, Arne Wolters, Adam Steventon, et al.
Age and Ageing|January 22, 2011
Predicting who will use intensive social care: case finding tools based on linked health and social care dataMartin Bardsley, John Billings, Jennifer Dixon, et al.
Pageof 6