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The COVID-19 pandemic that has hit the world has brought a positive trend to the pet industry in Indonesia. However, this increase in the number of pet owners is not accompanied by a strong commitment. As a result, not a few pets are abandoned because the owner is not able to cope with the soaring spike in health costs. In America, this phenomenon has been proven to be successfully prevented by the existence of animal health insurance, which gives pet owners a feeling of security if something bad threatens the health of their pets. However, pet health insurance in Indonesia is still relatively new even though Indonesia also has a large market share, which is around 70% of the Indonesian population. Therefore, this study will use multiple linear regression and utilize the bootstrapping technique to build a model of pet health costs that is used to determine premiums for pet health insurance. The results showed that the variables of the pet's age, the condition of the pet having been sterilized, routine control by the vet, and the level of activity of the animal had a significant effect on the model. Based on the model that has been successfully formed, the average frequency of visits to the veterinarian and the average amount of expenses incurred in a year are obtained, so that the prediction of the premium amount is IDR 1,003,794 annually. [ABSTRACT FROM AUTHOR]

This work will give a novel approach in predicting premium of Indonesian's health insurance for the next 30 years using application of dynamical systems. First, we fit Indonesian population dataset from 1960–2018 and the number of policy holders to estimate the coefficients of our dynamical systems using Markov Chain Monte Carlo Process. We used models fit to predict the number of participant for the next 30 years. We then implemented the frequency-severity model to evaluate the premium of each segment in the insurance policy. The projected premium for the next 30 years will be calculated using the same frequency-severity model but with new parameters obtained from the numerical solution of the dynamical system. We assumed a constant proportion between population data to the number of participant in the sample data and a gradually decreasing proportion between the number of zero claim and the number of sample data. Premium in all segments overestimated costs regulated by the government with one exception in one segment. [ABSTRACT FROM AUTHOR]

The increasing cost of treatment in hospitals has made many people worry about the financial risks they face. One way to reduce this risk is through a health insurance program. Each customer must bind himself to an insurance company as a risk guarantor by paying money, which is called a premium. The amount of premium must be calculated correctly, so that it does not harm the customer or the insurance company. Therefore, there are several factors that need to be considered in determining the premium, such as age, occupation, medical history, lifestyle, and other factors determined by the company. These factors are called underwriting factors. In this study, Generalized Linear Models were used to determine the claims and the number of claims. Variables that significantly influence of claims are having a history of allergies, having a history of hereditary diseases, class of health facilities, and length of stay. While the variables that have a significant effect on many claims are occupation, smoking, having a history of allergies, and consuming alcohol. These two models are used to calculate the premium price from a customer using the compound model principle. [ABSTRACT FROM AUTHOR]

The increase of Dengue Homorrhagic Fever (DHF) casualties in Indonesia can become a burden to the nation, especially for the mandatory health insurance which provided by BPJS (Badan Penyelenggara Jaminan Sosial) or Indonesia Social Security Administrator. In this research, a model of premium estimation of health insurance is developed for handling the DHF casualties, based on BPJS Data sample in four cities; Semarang, Malang, Bandung and DKI Jakarta. The model is based on monthly payments of premium and benefit. We use a classification of participants' ages and a fractional probability to survive. The result concludes that the largest premium for the highest number of participation and the largest amount of severity. Based on some assumption, the reserved fund to pay the total DHF claims by BPJS in 2016 was only about 1% of the real calculated expenses of a study, so the accessibility to this health insurance should be increased in the future. [ABSTRACT FROM AUTHOR]

Many American cities are facing budget shortfalls in 2010. The mayor and city council in Omaha, Nebraska addressed the shortfall by unilaterally requiring retirees to pay a portion of their health insurance premiums, despite labor contracts requiring the city to pay the entire premium. The contract clause in the United States Constitution prohibits states (and cities) from interfering with the obligation of contract; however, this prohibition is not absolute. This paper examines whether or not Omaha can legally require retirees to pay a portion of the premium. [ABSTRACT FROM AUTHOR]