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Digital Learning, Disability and Autism Dynamic Support Register

The NHS has a crucial role in helping people with a learning disability, autism, or both, lead longer, happier, healthier lives. People with a learning disability and/or autism have poorer physical and mental health than the general population, with many of the conditions they die from being potentially avoidable.

The ‘Care (Education) and Treatment Review policy’ and ‘Building the Right Support’ highlight the importance of services knowing the people who are likely to need additional support, so that they don’t end up being admitted to mental health or learning disability hospitals unnecessarily.

The Learning, Disability and Autism Dynamic Support Register (LDA DSR) has three principle aims:

  1. to provide a single up-to-date record of these individuals
  2. to identify those adults and children most at risk of an admission or readmission, in order to provide timely care in the community
  3. to support reporting needs, to enable data-driven transformation, continuous improvement, and quality assurance

Currently, maintaining the LDA / DSR register often requires manual data collection, usually through Excel or Word documentation, which leads to access issues and reporting challenges across multidisciplinary multi-organisational teams. Graphnet has worked with ICS colleagues to develop a Learning Disability and Autism module within their CareCentric integrated care record. The module consists of 3 elements: 

  • A candidate list – based on QOF membership and SNOMED codes that identifies individuals who could benefit from a risk assessment
  • An LDA/DSR assessment form – that digitizes the traditional paper form and auto calculates the risk of admission or captures that they are currently an inpatient
  • A dynamic register – listing all the individuals assessed and their RAG status based on risk

Both the list and the register are enabled to allow a care professional to drill through to the individuals integrated care record, to support decision making. Centralising the storage of information and making the risk status clear, provides a powerful tool for professionals to manage shared caseloads, and make better informed and timely interventions that prevent unnecessary hospital admissions.

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