Identifying the right patients for Structured Medicines Reviews
What is the challenge your project is going to address and how does it connect to the theme?
In England, SMRs are a requirement of the Primary Care Network contract for general practice. There are five patient cohorts (care homes, frailty, 10 or more medicines, on dependency forming medicines and medicines with potential to cause harm); within these groups there will be varying levels of need. This project aims to work with a number of partners across the system to develop a digital tool that will identify patients who urgently need a structured medication review and support primary care case loads for clinical pharmacists, general practitioners and others who undertake SMRs. The team will explore data sets in primary care and secondary care, as well as other sectors to understand medicines risk.
What does your project aim to achieve?
The aim of this project is to develop a solution for case-loading for Structured Medication Review appointments in primary care.
How will the project be delivered?
A cross system team of experts in medicines optimisation, digital systems, analytics and primary care will be established to run the project. Initially, a gap analysis will be undertaken to understand current methods of identifying people for SMR caseloads; both digital and manual processes will be considered. Using a panel of experts, an ideal digital solution will be designed. This will be iterated taking account of current availability of data and linking data possibilities. A digital solution to automate case-loading will be
How is your project going to share learning?
Identifying the key population groups remains a barrier to effective medication reviews. Furthermore, with limited capacity in primary care it is imperative that appointment slots are utilised well through effective caseloading. Learning from this work could be applied in other areas.
How you can contribute
- Current technology available for caseloading
- Data sources
- AI expertise to support effective caseloading