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Introduction: The incidence and prevalence of diabetes is increasing in pregnant women. Midwives manage a substantial proportion of care of these women. Currently it is notknown whether midwives have sufficient competence in managing these patients well. The Diabetes Care Trust commissioned a survey to assess the diabetes education and training needs of midwives who look after pregnant women with diabetes.Material and methods: A freedom of information request was made to all the NHS Trusts in the UK to gather relevant information about the roles and responsibilities of midwives in thematernity units in the UK. This was followed by a Survey Monkey questionnaire to midwives in the UK who are members of the Royal College of Midwives to assess their education and training level, needs, desires and views preceded by a test survey on nine midwives.Results: The survey revealed considerable variation in the roles and responsibilities, current levels of training and education needs of midwives. Over 85% of midwives expressed a desire to access additional education on diabetes management in different areas. Training in insulin initiation and titration, management during labour and ability to contribute to the antenatal clinic was desired by over 85% of midwives surveyed. Conclusions: There is an unmet need for structured education and training programmes for midwives in the management of diabetes in pregnancy. We recommend further work in producing tailored and accredited training programmes at different levels to suit the differing needs of midwives and diabetes specialist midwives in the UK.

The use of an expert system shell (EXPERTECH Xi Plus) in the construction of an expert system for the diagnosis of infertility has been evaluated. A module was devised for predicting ovulation from the medical history alone. Two versions of this system were constructed, one using the expert system shell, and the other using QuickBASIC. The two systems have been compared with respect to: (1) ease of construction; (2) ease of knowledge base update; (3) help and explanation facilities; (4) diagnostic accuracy; (5) acceptability to patients and clinicians; (6) user-friendliness and ease of use; (7) use of memory space; and (8) run time. The responses of patients and clinicians were evaluated by questionnaires. The predictions made by the computer systems were compared to the conclusions reached by clinicians and to the “gold standard” of day 21 progesterone.The conclusions of this pilot study are: (1) the construction of this expert system was NOT facilitated by the use of this expert system shell; (2) update of the knowledge base was not facilitated either; (3) the expert system shell offered built-in help and explanation facilities, but as the system increased in complexity these became less useful; (4) after initial adjustment of decision thresholds the diagnostic accuracy of the system equalled that of the clinician; (5) the patient response to computer history-taking was very favorable but much less favorable to computer diagnosis; (6) the clinicians took a positive attitude to computer diagnosis; (7) the systems were easy to use; (8) the expert systems shell required much more memory space and had a much slower response time than the system written in BASIC.

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