South West and Wessex
Session Chair: George Allen
4.00pm Tim McDonald, A newborn screening programme for neonatal diabetes
4.30pm Kat Mordue, Use of clinical decision support in patient test pathways
5.00pm Kristen Lilly, Demand management of ANA and specific IgEs
The majority of errors in laboratory medicine originate in the pre and post analytical phases of testing. Yet arguably these are the phases where the laboratory has the least influence or control. Join our session which will focus on innovations in the South West & Wessex to ensure that the right test is done at the right time, in the right location for the patient and that the right action is taken in response to the result.
A newborn screening programme for neonatal diabetes - Tim McDonald
Professor Tim McDonald will present his experience of introducing a Newborn Screening Program for Neonatal Diabetes in the UK. Tim will present his experience of the hurdles and challenges of generating the evidence required to satisfy the National Screening Committee that a test meets the standards to be considered for implementation into newborn screening in the UK.
Use of clinical decision support in patient test pathways - Kat Mordue
University Hospitals Plymouth has piloted the use of Clinical Decision Support (CDS) software (AlinIQ, Abbott) to interrogate patient cases against a rules-based algorithm, built using evidence-based clinically defined thresholds for determining the cause of anaemia. The pilot CDS project has focused on the diagnosis of anaemia due to iron deficiency, vitamin B12 and folate deficiency, and anaemia secondary to chronic kidney disease. This presentation will share our experience designing the CDS anaemia pathway and how the CDS software can support our primary care colleagues in requesting the right tests at the right time.
Demand management of ANA and specific IgEs - Kristen Lilly
Laboratory tests are essential to support diagnosis but can also be requested in the wrong clinical context which may prove difficult to interpret. We aim to present an algorithmic approach to demand management which provides additional clinical advice at the point of request (via order communication IT) to reduce inappropriate testing from primary care, provide clinical advice and prevent incidental findings.