Our work:
Novel methods to aid and evaluate implementation
Why this research:
The generation of high-quality evidence relies on obtaining the least biased information to answer clinical questions that affect patient care.
However, some of the least biased methods can be very complex, and tend to be the least likely to include vulnerable and disadvantaged patients (where evidence is most needed).
We are using Electronic Health Records to model and evaluate changes to the way healthcare is delivered. Use of such models could enable greater participation rates from diverse communities where health needs are greatest. However, most of these tools need to be developed or tailored to the current data available.
We will also provide all other themes in the Applied Research Collaboration with methodological, statistical and health economic support.
Theme Lead
Workstreams in this research area:
Create a framework for developing and evaluating early health economic models with a specific
focus on diagnostic tools
Diagnostic research to provide guidance on the evaluation of new prediction models based on “Big Data”
and artificial intelligence (AI)
Modeling changes to the health service and predicting potential impact.
New tools to explore impact of multimorbidity on workload in Primary Care and predicting requirements in service redesign.