Forecasting of Caesarean Births in the University of Cape Coast Hospital, Ghana

Authors

  • McAdams Abu Bakr
  • Esther Rhoda Ababio
  •  Richard Pinkrah
  • James Kojo Prah

DOI:

https://doi.org/10.47672/ajsas.944

Keywords:

Caesarean section, Time series modelling, Stationarity, Box-Jenkins Methods, Unit root testing, Forecasting.

Abstract

Background: The increasing phenomenon in caesarean sections at the global as well as the national level is a public health concern. Periodic variations in Caesarean Sections incidences at the University of Cape Coast Hospital is currently unclear and the model that can best represent its movement is unknown. This study sought to model and predict the monthly incidence of Caesarean Sections at the hospital.

Methods: The study employed a monthly periodicity of 115 time-series data sourced from District Health Information Management Systems Two on Caesarean Section births at the University of Cape Coast Hospital over a 9-year period. The autoregressive integrated moving average models of the classical Box-Jenkins methods of Time Series Analysis were used to analyse the data. Analysis was performed in EViews 12 and R (version 4.0.4)

Results: There were six non-seasonal tentative candidate models for the hospital. The model autoregressive integrated moving average (1, 1, 2) with a first-order autoregressive and second-order moving average with one order of nonseasonal differencing emerged as the best fit model. The findings revealed an overall rising trend in the incidence of Caesarean section rates in the hospital over the study period with an average of 30.54% per month. This is expected to increase to over 40% per month over the next five-year period of August 2021 to July 2026 according to projections.

Conclusion: Non-Seasonal autoregressive integrated moving average (1,1,2) was identified as the best model that describes monthly expected Caesarean Sections births at the University of Cape Coast Hospital. Using this model to forecast the expected number of Caesarean Section births will facilitate health policy formulations and allow for the prudent use of available obstetric services.

Recommendations: Clinicians should be trained to improve their skills in the use of instruments in deliveries as well as in the safe conduct of vaginal breech deliveries.

Author Biographies

McAdams Abu Bakr

Department of Public Health, University of Cape Coast Hospital, University of Cape Coast, Cape Coast, Ghana

Esther Rhoda Ababio

Department of Public Health, University of Cape Coast Hospital, University of Cape Coast, Cape Coast, Ghana

 Richard Pinkrah

Department of Public Health, University of Cape Coast Hospital, University of Cape Coast, Cape Coast, Ghana

James Kojo Prah

Department of Public Health, University of Cape Coast Hospital, University of Cape Coast, Cape Coast, Ghana

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Published

2022-02-26

How to Cite

Bakr, M. A. ., Ababio, E. R. ., Pinkrah, Richard., & Prah, J. K. . (2022). Forecasting of Caesarean Births in the University of Cape Coast Hospital, Ghana. American Journal of Statistics and Actuarial Sciences, 4(1), 1 - 17. https://doi.org/10.47672/ajsas.944

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