Endocrine Abstracts

Background: The 2013 Scottish Diabetes Survey demonstrated that only 22% of individuals with type 1 diabetes have optimal glycaemic control, defined as a HbA1c <58 mmol/mol. The 2014 Diabetes Improvement Plan in Scotland prioritised, ‘improving the care and outcomes of all people living with type 1 diabetes’. Scotland’s Diabetes Education Advisory Group has now been established. Accordingly, the Fife Insulin and Food Education for Diabetes (FIFE Diabetes) structured education programme was developed.

Methods: Since 2013, patients with poor control were provided with an information leaflet in clinic and invited to register. FIFE Diabetes is an education course for adults with T1DM using multiple injection or basal bolus insulin regimes. Aims include learning interactively about carbohydrate counting and insulin dose adjustment, improving knowledge and encouraging self-management to improve control and reduce complications. Three courses annually are led by diabetes specialist nurses and dieticians over 4 consecutive weeks. Participants are required to attend all sessions, keep a diary, have serial HbA1c measurements and complete Problem Area In Diabetes (PAID) and Symptom Awareness of Hypoglycaemia questionnaires. The paired t-test, McNemar’s and Fisher’s exact tests were used.

Results: Forty-eight patients have participated to date, with median age 41 at enrolment, and mean baseline HbA1c 79 mmol/mol. Mean HbA1c at 12 months was 71.4 mmol/mol, a 9.62% reduction (two-tailed P value 0.0221). The number of participants reporting significant distress and emotional burnout on the PAID tool decreased, but this did not reach statistical significance. No significant difference in hypoglycemia symptom awareness was observed between baseline and 6 months.

Discussion: Our structured education programme demonstrated significant improvements in glycaemic control in this adult cohort with T1DM. A more sensitive tool for assessing hypoglycaemia symptom awareness will be trialled. Further analyses will enable us to better predict patients most likely to benefit, improving selection to the programme.