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Related Experiment Videos

Towards rational midwifery service planning.

B Moores

    Journal of Advanced Nursing
    |May 1, 1980
    PubMed
    Summary

    This study examines midwife supply and demand, finding a potential oversupply of state-certified midwives nationally. Birth rate trends and seasonal effects were analyzed to estimate local needs and impact on maternity bed provision.

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    Area of Science:

    • Maternal Health Workforce Planning
    • Public Health Statistics Analysis
    • Healthcare Resource Management

    Background:

    • Analysis of health district data revealed a potential imbalance in the number of state-certified midwives trained versus those actively employed.
    • Published statistics suggest a concerning discrepancy from a healthcare manpower planning perspective.

    Purpose of the Study:

    • To investigate national birth rate trends and identify seasonal variations impacting midwife demand.
    • To estimate the future demand for midwives at local levels, considering varying maternity bed provisions.
    • To assess the workload implications for maternity units.

    Main Methods:

    • Examination of national birth rate statistics to identify trends and seasonal effects.
    • Development of models to estimate midwife demand at local levels based on birth projections and bed provision.
    • Attempted regression analysis using data from 417 maternity units was unsuccessful due to high variable correlation; estimates were derived from existing literature.

    Main Results:

    • A surprising seasonal effect was identified in national birth rate trends.
    • Initial attempts at regression analysis to link maternity unit inputs and outputs were inconclusive due to strong variable correlations.
    • Estimates of midwife workload and demand were derived from secondary sources.

    Conclusions:

    • The current training output of state-certified midwives may exceed the number gainfully employed, indicating a potential oversupply.
    • Accurate workload and demand forecasting for maternity services requires robust data and analytical methods, potentially necessitating alternative approaches when direct analysis is unfeasible.

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