The use of National Diabetes Inpatient Audit data to tailor training needs across a district general hospital

Burnett, R.

The use of National Diabetes Inpatient Audit data to tailor training needs across a district general hospital - 2016

NMUH Staff Publications EMBASE 33

<span style="font-size: 10pt;"><span style="color: #4a4a4a; font-family: Lato, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; text-decoration-color: initial;">The National Diabetes Inpatient Audit collects diabetes care data across English and Welsh health trusts. Following the collection of data for 2015, we decided to look into it in more detail to help identify the wards and departments where quality of care could be improved and to develop a targeted training programme. Methods: The hospital wards were subdivided by specialty into six groups (A-F) and data for glycaemic control, hypoglycaemic episodes(hypos), prescription errors and specialist review were retrieved and compared. Results: We found significant differences in the quality of care across different specialty subgroups. Group A patients had no hypos for 31 patient days whereas group B had 43 hypos in 172 patient days (0.28 hypos/day). There was variation in hypo management according to trust guidelines with group B managing 85% of hypos according to guidelines whereas group D managed 40% appropriately. Groups A, B and F did not keep glycaemic control tight enough in cases where good control was desired (poor control in 8/27, 38/103 and 35/55 patient days respectively). Medication errors (prescription and titration) also varied, with patients in groups A and D having a likelihood of error in 38% and 30% of cases respectively. Specialist diabetes team review rates were similar across groups. Conclusions: This detailed analysis of data from the National Diabetes Inpatient Audit has given us insight into educational and training needs across different subspecialties. This will help us to develop strategy to improve quality of care across the trust.</span>&nbsp;(Conference abstract)</span>
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