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Grey systems in the management of demand for palliative care services in Poland

Author

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  • Sylwia Nieszporska

    (Chair of Statistics and Econometrics)

Abstract

Background The concept of care for people in a critical or even terminal health condition, who are in the last stage of their life, has become the mission of palliative care facilities. Therefore, the life of a sick patient poses a number of challenges for health care services to make sure that medical services are tailored to the trajectory of the disease, as well as the various needs, preferences and resources of patients and their families. Methods Health systems financed from public funds need to adopt new methods of management to meet the high and arising demand for a long-term care. There are several ways of assessing the demand for long-term care services. The method recommended by the author and presented in more detail in this paper is the one relying on grey systems, which enables the estimation of forecasting models and, finally, actual forecasts of the number of potential future patients. Results GST can be used to make predictions about the future behaviour of the system, which is why this article aims to present the possibility of using the first-order grey model GM (1,1) in predicting the number of patients of palliative care facilities in Poland. The analysis covers the data from 2014 to 2019, whereas the prediction of the number of patients has been additionally formulated for 2020. Conclusions Health systems, particularly publicly funded ones, are characterised by a certain kind of incompleteness and uncertainty of data on the structure and behaviour of its individual components (e.g. potential patients or payers). The present study aims to prove how simple and effective grey systems models are in the decision-making process.

Suggested Citation

  • Sylwia Nieszporska, 2022. "Grey systems in the management of demand for palliative care services in Poland," Health Economics Review, Springer, vol. 12(1), pages 1-13, December.
  • Handle: RePEc:spr:hecrev:v:12:y:2022:i:1:d:10.1186_s13561-021-00349-5
    DOI: 10.1186/s13561-021-00349-5
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