ABSTRACT
Objective To evaluate the demand for midwives in Yunnan province utilizing Birthrate Plus for planning and development of such workforce. Methods A convenient sample method was used to investigate 8435 maternal cases at 9 hospitals in Yunnan province in four months from 9 - 12 in 2017, and Birthrate Plus was used to calculate the demand for midwifery at each hospital. We also analyzed the two core elements of Birthrate Plus- maternal category allocation and midwife hours of each hospital. Results Maternal cases fall into five categories and maternal category allocation in hospitals is roughly the same;Maternal in higher category tended to need longer midwife hours; the average birthrate of 9 hospitals was (194. 22 ± 44. 84) case/ ( year·midwife). The number of midwives in two tertiary hospitals is obviously insufficient. Midwives at 7 secondary hospitals are more than predicted. Conclusions Midwives in Yunnan are generally faced with a large workload, especially at secondary hospitals, and midwives need to bear numerous non-midwifery workload beyond Birthrate Plus. Therefore, the Birthrate Plus can reflect the midwifery workload scientifically and reasonably in the current situation of midwifery work. But the predication for midwifery workforce requires a study of the ratio of midwifery work in the entire clinical work of the hospital.
ABSTRACT
The forecast of health human resources demand is the most important and one of the most complex aspects of health manpower planning projections. There are many methods in forecasting human resources demand,and each method has its own advantages and disadvantages. Five kinds of commonly used basic methods are comparatively analysised in this paper.
ABSTRACT
An initial forecast model of BP neural networks is established, and is trained using the history data of our hospital inventory. This model is applied to forecasting the demand of medical equipment in Daping Hospital. The result indicates that the inventory cost is reduced enormously. The model is useful in the purchase and inventory management of medical equipment.