Research code: منتج از رساله دکتری
Ethics code: منتج از رساله دکتری
Clinical trials code: منتج از رساله دکتری
1- Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran , mojtabaabed1988@gmail.com
2- Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
Abstract: (501 Views)
Introduction: One of the most important pillars of improving healthcare services is the state of supplementary medical insurances, which increase people's access to healthcare. The accurate and scientific assessment of the risks of issuing a medical insurance policy is one of the most sensitive and important stages of risk assessment, and performing it leads to the identification of high-risk customers and the determination of the health insurance policy rate, in accordance with the customers' risk. Therefore, the present study aimed to classify and rate health insurance beneficiaries using a risk matrix approach.
Methods: In order to assess the risk of insured persons, a two-step model has been presented along with the risk assessment matrix approach, which can be used to classify the insureds into different risk classes. For this purpose, in the first step, the probability of claiming damages using logistic regression based on age, gender and geographical location risk factors are predicted and in the next step the severity of the damage is predicted using quantile regression.
Results: Finally a risk assessment model is presented with a risk matrix approach, which presents three risk class; critical (R_1), moderate (R_2) and acceptable (R_3) risk class.
Conclusion: Using the results of the risk matrix approach, insurance premiums have been determined for the insurance policies according to their risk class. This can help increase people's satisfaction, move towards justice, achieve fair insurance premiums, expand the security environment, and take a scientific look at the country's insurance industry.
Type of Study:
Research |
Subject:
Special Received: 2024/09/3 | Revised: 2025/01/7 | Accepted: 2024/11/19 | ePublished: 2024/12/23