Forecasting Frequency of Delivery using Poisson Hidden Markov Models
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background And Objectives
Delivery is one of the most important services in the health systems, and increasing its effectiveness and efficiency are a health priorities. The aim of this study was to forecast the number of deliveries in order to design plans for using all facilities to provide patients with better services.Methods
The data used in this study were the number of deliveries per month in Hakim Jorjani Hospital, Gorgan, Iran during the years 2010 to 2016. Due to the over-dispersion of the data and non-compliance with a Poisson distribution, the Poisson hidden Markov model was applied to predict the frequency of monthly deliveries. The model parameters were estimated using the maximum likelihood method and expectation maximization algorithm.Results
The use of the Akaike criteria revealed the frequency of delivery in different months in the hospital followed a Poisson hidden Markov models with three hidden states, and the mean Poisson distribution in each component was 193.74, 236.05, and 272.61 labors, respectively.Conclusion
The results of this study showed that governments encouraging policies have had short-term, limited effects on increasing fertility with minimal effects on the results of the two-year forecast. Keywords:
Language:
Persian
Published:
Iranian Journal of Epidemiology, Volume:14 Issue: 1, 2018
Pages:
74 to 82
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