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Forecasts of Performance Indicators in the Health System Using the Arima Method

Author

Listed:
  • Mirescu Lucian

    (University of Craiova, Doctoral School of Economic Sciences, Romania)

  • Popescu Liviu

    (University of Craiova, Faculty of Economics and Business Administration, Romania)

Abstract

This paper presents quarterly forecasts on several performance indicators from the Romanian health system, from a county emergency hospital. Using data from the period 2010-2022, forecasts are made for the period 2023-2025 of the average duration of hospitalization, the rate of bed utilization, the index of complexity of cases, the number of cases and the average cost of hospitalization. The method used is that of the auto-regressive integrated moving average (ARIMA) applied to time series. The Dickey-Fuller test is used to check the stationarity of the time series, as well as other tests for the validation of prediction models.

Suggested Citation

  • Mirescu Lucian & Popescu Liviu, 2024. "Forecasts of Performance Indicators in the Health System Using the Arima Method," Journal of Social and Economic Statistics, Sciendo, vol. 13(1), pages 1-22.
    • Handle: RePEc:vrs:jsesro:v:13:y:2024:i:1:p:22:n:1001
    DOI: 10.2478/jses-2024-0005
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    References listed on IDEAS

    as
    1. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
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    More about this item

    Keywords

    health system; forecast; ARIMA method;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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