How to build effective teams in General Practice

This guide draws on insights from research, policy analysis and leadership practice to outline ways in which practices can create and sustain effective teams, as they come together to form primary care networks | The Kings Fund

The need for collaboration and communication underpins much of the guide and links to further reading and case studies to support each section are provided. The guide looks at the following questions:

1. What are the fundamentals of effective teams?
2. Which roles should you recruit?
3. How can you make best use of new roles?
4. How can teams communicate effectively?
5. Do you need to re-design your physical space?
6. How can you ensure supportive management and accountability?
7. How can you work across organisations?
8. How should you engage with your patients?
9. ​How can you manage yourselves effectively?

Full document: How to build effective teams in general practice

Transforming health through innovation: Integrating the NHS and academia

Transforming health through innovation: Integrating the NHS and academia | Academy of Medical Sciences’ Council

This report finds that the UK’s world-leading biomedical and health research sector has contributed to major advances in patient care, as well as to the wealth of the nation. However, NHS staff increasingly lack the capacity to engage with research, and the number of clinical academics is declining.

This widening gap between the NHS and academia is preventing the research expertise and capability within the NHS from reaching its full potential. This report explores these issues further. It calls for the support of leaders across the biomedical research landscape to achieve six key outcomes that will be essential to enhance the interface between the NHS and the UK’s academic biomedical and health research sector.

Full report: Transforming health through innovation: Integrating the NHS and academia

Image source: https://acmedsci.ac.uk/

International evaluation of an AI system for breast cancer screening

McKinney, S. M., et al. |2020| International evaluation of an AI system for breast cancer screening| Nature| 577|(7788)| P. 89-94.

An international team of researchers including experts from Imperial College London trained and tested an artificial intelligence (AI) system screening using a simulation of the double-reading process that is used in the UK.  29000 mammography images were used to demonstrate that the AI system was able to correctly identify cancers from the images with a similar degree of accuracy to expert radiologists, and holds the potential to assist clinical staff in practice. 

The authors of the paper found that the computer algorithm (AI system) maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening (Source: Imperial College London). 

Full press release from Imperial College London Artificial intelligence could help to spot breast cancer

Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7%and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.

Paper: International evaluation of an AI system for breast cancer screening

 

NHS App Ambassadors boost app usage

NHS Digital | January 2020 | Number of NHS App users more than double in 3 months as ‘App Ambassadors’ set to work

Since the introduction of NHS App Ambassadors in Autumn 20199,  the number of NHS App registered users has more than doubled to 200,000, compared with 91,000 at the beginning of September. More people than ever before booked NHS appointments digitally choosing to use this route rather than calling their local surgery. In September there were 1.4million GP online service appointment transactions.

As part of the campaign the NHS has been undertaking a campaign focused on its own staff encouraging them to download the app themselves (Source: NHS Digital).

Image source: digital.nhs.uk

 

 

 

 

 

 

Number of NHS App users more than double in 3 months as ‘App Ambassadors’ set to work