doi: 10.17706/ijapm.2019.9.2.101-110
Lognormal Distribution in Health Insurance: Interval Estimation Methods for the Average Cost and Correction of Truncated Values
Marli Amorim
1
,
,
- 1 Multicare - Health Insurer, Portugal, Lisbon
- 2 Faculty of Sciences at the University of Lisbon, Portugal, Lisbon.
Abstract
Among the diseases with high treatment costs, oncologic and cardiovascular diseases are nowadays the main causes of death in Portugal as in many other high income per capita countries. This situation is a challenge for health insurance companies and financial institutions. Although there is currently some affordable health insurance in case of severe diseases, such as cardiovascular disorders or cancer, the available capital is easily depleted. The study of costs associated with many serious diseases shows that very often lognormal distribution fits well to the costs distribution. Therefore, a simulation study was made to compare different interval estimation methods of the average cost of a lognormal distribution. This work compares bootstrap parametric and non-parametric methodologies with Cox and large sample normal based methods and the results were applied to a breast cancer Portuguese dataset. Furthermore, for the lognormal distribution, a correction to the truncated values of costs following capital depletion is proposed, and the impact of this correction illustrated via its application to a heart failure dataset.
Keywords
- Bootstrap
- confidence interval
- costs distribution
- heart and cancer diseases
- lognormal distribution
How to Cite
Marli Amorim, Joana Fernandes, and Teresa Alpuim, "Lognormal Distribution in Health Insurance: Interval Estimation Methods for the Average Cost and Correction of Truncated Values," International Journal of Applied Physics and Mathematics, vol. 9, no. 2, pp. 101-110, 2019. https://doi.org/ 10.17706/ijapm.2019.9.2.101-110
Copyright & License
Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).