A model for the distribution of daily number of births in obstetric clinics based on a descriptive retrospective study

OBJECTIVE: To test whether the relatively unpredictable nature of labour onset can be described by the Poisson distribution. DESIGN: A descriptive retrospective study. SETTING: From the Danish Birth Registry, we identified births from all seven obstetric clinics in the capital region of Denmark (n=211 290) between 2000 and the end of 2009. On each date, the number of births at each department was registered. Births are categorised based on whether an elective caesarean section or induction of labour has been performed, and among the remaining ‘non-elective births’, acute caesareans were registered. METHODS: After the exclusion of elective caesarean sections and births after induction of labour, only ‘non-elective’ births (n=171 009) were included for the main statistical analysis. Simple descriptive plots and one-way analysis of variance were used to analyse the distribution of ‘non-elective’ births for each day of the week. MAIN OUTCOME MEASURES: The daily number of ‘non-elective’ births. RESULTS: The number of ‘non-elective’ births varies considerably over the days of the week and over the year for each obstetric clinic regardless of clinic size. However, for each fixed day of the week, the variation over the year is well described by a Poisson distribution, allowing simple prediction of the variability. For births at each fixed day of the week, the Poisson distribution is indistinguishable from a normal distribution. CONCLUSIONS: The number of ‘non-elective’ births for each day of the week is well described by a Poisson distribution. Consequently, the Poisson model is suitable for estimating the variation in the daily number of ‘non-elective’ births and could be used for planning of staffing in obstetric clinics. The model can be used in smaller as well as larger clinics.