Article Text

G34(P) Use of a handover database to identify cases and provide a morbidity governance system
  1. SP Williams
  1. Child Health Department, University Hospital North Midlands, Stoke on Trent, UK


Aim One important route to organisational learning is through individual reflection and group discussion of cases of morbidity. Our aim has been to use an existing, successful, networked, computer based clinical handover system as the base to identify, assess and learn from difficult clinical cases.

Methods Microsoft Access software was used to build a relational database linking inpatient data generated by the handover process with new data indicating the nature and pre-determined category of morbidity that occurred. Cases identified were assessed by trainee staff and their inputs discussed at 3 monthly Morbidity Meetings. These generated additional information including lessons learned, actions suggested and summative classification of acceptability. Where insufficient investigation had taken place to set a classification these were set as ‘undetermined’. Where the morbidity issue was due to care in another department these were set as ‘not applicable’. Departmental governance meetings provided ultimate closure.

Results Over a period of 3 years to end November 2016 a total of 155 cases of morbidity were identified and 153 were presented in 3 monthly Morbidity and Mortality meetings with 2 cases deferred. The median number of cases identified per month was 6 varying from 1 to 18. See table 1 for morbidity categories. From these cases 107 learning points were generated and 60 actions suggested of which 16 have yet to be completed. See table 2 for summative classifications.

Abstract G34(P) Table 1

Morbidity categories

Abstract G34(P) Table 2

Summarative classifications

Conclusion Inpatient morbidity cases can be identified, assessed and relevant departmental governance actions recorded using a handover based database. One challenge was maintaining interest in identifying patients as shown by a wide variation in the numbers of patients identified per month and the other challenge has been assiduous assessment of cases. This is now an embedded part of our organisational learning aimed at the highest possilble standards of care.

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