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Healthcare Expenditure Prediction in Turkey by Using Genetic Algorithm Based Grey Forecasting Models

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Operations Research Applications in Health Care Management

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 262))

Abstract

This chapter aims to predict the health care expenditure (HCE) per capita which is an important indicator of a country’s health status and economic growth. Accurate estimation of HCE can guide efficient health care policy making and resource allocation. Grey forecasting models are applied for predicting the HCE per capita of Turkey. Three different strategies are proposed which are rolling mechanism, training data size optimization and parameter optimization to improve the forecasting accuracy of these models. Genetic algorithm (GA) which is one of the most widely used meta-heuristic optimization techniques is applied for training data size and parameter optimization of the grey forecasting models. The application results indicate that the optimization of parameters and training data size together with rolling mechanism highly improve the forecasting performance of the grey models.

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Authors and Affiliations

  1. Department of Industrial Engineering, İstanbul University, 34320, İstanbul, Turkey

    Tuncay Özcan & Fatih Tüysüz

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  1. Tuncay Özcan
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  2. Fatih Tüysüz
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Correspondence to Fatih Tüysüz .

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Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Macka, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University, Macka, Istanbul, Turkey

    Y. Ilker Topcu

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Özcan, T., Tüysüz, F. (2018). Healthcare Expenditure Prediction in Turkey by Using Genetic Algorithm Based Grey Forecasting Models. In: Kahraman, C., Topcu, Y. (eds) Operations Research Applications in Health Care Management. International Series in Operations Research & Management Science, vol 262. Springer, Cham. https://doi.org/10.1007/978-3-319-65455-3_7

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