Forecasting cesarean deliveries with robust time series models in a tertiary care hospital

Abstract

Introduction: Caesarian section rate was 47% at Patan Hospital in 2014 despite the recommendation of keeping it below 15%. This has become a public health problem and it is debated as human right violation of childbearing women. This study aims use robust time series model to forecast caesarian deliveries to keep track of it at the hospital.
 Method: Univariate time series models were used to forecast 3-year caesarean deliveries at Patan Hospital using 60-month (2010-2014) data. A robust time series model with low mean average percentage error from validation period and without autocorrelation problem was selected and used to forecast caesarean deliveries for 2015-2017 period. 
 Result: Winter’s additive model had lowest validation forecasting error and showed decreasing trend of caesarian deliveries but it showed autocorrelation. Quadratic regression gave similar result but is also autocorrelation problem. Artificial Neural Network – Multilayer Perceptron model gave close forecasts but autocorrelation was not assessed. Best Autoregressive Integrated Moving Average (ARIMA) model gave valid forecasts without autocorrelation problem.
 Conclusion: ARIMA (0,1,1),(0,0,0) model with one difference and one level of moving error correction gave valid forecasts for Patan Hospital. Advanced univariate and multivariate time series models with large samples can be used to get precise forecasts of caesarean deliveries in Nepal.

Application of Time Series Analysis in Modelling an Integrated Moving Average for Predicting Caesarean Sections Births

“…The increasing or upward trend in CS cases revealed in this study also concurs with the findings of other researchers [6,8,9,17]. Bosson-Amedenu et al [6] study exhibited an increasing or upward trend for CS incidence rate (both within the study period and the forecast period) for all the then ten (10) regions of Ghana, however, that study showed seasonal pattern in CS incidence rate for Eastern, Greater Accra and Ashanti regions respectively.…”

“…The seasonal pattern for Eastern region peaked in January; Greater Accra peaked in May whereas Ashanti region peaked in both May and October. Pradhan, and Bhandary [8] in their study rather had a decreasing CS rate in their forecast though the study period exhibited increasing CS rate. The forecast of Caesarean section incidences in UCC hospital for the period of August 2021 to July 2026 indicates an increasing trend or an upward movement for the CS mode of childbirth with an expected rate of over 40%.…”

“…Pradhan and Bhandary [8] applied univariate time series analysis to model and forecast caesarean section deliveries in a tertiary health care hospital in India. Monthly data were taking from Patan Hospital in India from 2010 to 2014 and the best SARIMA model (0,1,1) (0,0,0)12 without autocorrelation was formulated to forecast caesarean section incidences in the hospital for the period of 2015-2017.…”