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Using Mau Technique for Choosing an Insurance Package

Treatment delivery is a multifactorial process, as it includes monitoring, evaluation, intervention, and prevention over the long term. An insurance plan’s choice combines financial and non-material parts, as the optimal package must correspond to the economic and medical benefits. Four coverage plans were analyzed, taking into account performance reports, which show the core segments’ quality of services. The most suitable choice is the Empire Family Health Plan, as it is the most affordable and highly rated in terms of price and quality.

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Choosing an insurance plan involves examining offers based on price, quality, and diversity criteria. The four providers vary in price, but it does not predict the quality of their services. An online investigation made it possible to analyze each of the parts of their packages both on an individual and in a family plan. The study included a comparison of scores for both one employee and their relatives in terms of the offer’s diversity and the price. Hence, adult, behavioral, and child and adolescent health are the main criteria for studying packages. Empire Family Health Plan was selected as the most satisfactory in terms of value for money. It scored an average of 70, 46, and 66 points, respectively, which is 3-20 points higher than similar ratings from competitors (New York State Department of Health, 2019). Another determinant of equal weight was the price factor, which is also essential for working people. Empire offers the most affordable individual package and a beneficial family package covering women’s, psychological, and children’s health. Therefore, this package should be chosen due to the combination of high ratings and attractive prices.

Initial assessment of plans based on points provides reliable conclusions, but they are inferior because of the package’s variety of services. In other words, the Empire’s satisfactory rating is compiled as an average score, although some indicators are lower than those of the competitors. For example, Aetna Health was rated as a more trustworthy provider in terms of satisfaction with care. MetroPlus and Oxford also have higher scores in their core areas, but the overall count is still lower than the Empire’s. Thus, confidence in choosing the right insurance plan can be calculated at 8/10 due to each family’s unique preferences and needs.

Statistical analysis of insurance plans includes the same criteria as for subjective reviews. Individual and family prices, scores on the four primary measures, and the comparison of the national average parameters were used. The multi-attribute utility (MAU) technique has been employed as a way to validate the original hypothesis numerically. Adult and child health was chosen as the main criteria, as they partially characterize the quality of the individual and family plans. The advantage of MAU is objectivity, in which each parameter is given a particular priority (Hahn et al., 2012). Hence, the attributes can be optimized and ranked in importance for decision-making. This approach allows one to consider the price and quality characteristics, which significantly increases the rationality of further choice. On the other hand, MAU is a more laborious and time-consuming process as it takes efforts to enter parameters, priorities, and attribute values. Consequently, the level of confidence in decision-making increased when using the statistical model.

Choosing one of the care plans has become much more comfortable as the responsibility has been transferred to the computational process. Using subjective judgment and making a decision based on an online analysis and pricing table is a satisfactory choice, although it is stressful for the researcher. On the other hand, the use of MAU is more arduous, but it is a semi-autonomous system and only requires the input of primary information (El Sawalhi & El Agha, 2017). Besides, the model is essential for justifying the decision, since grouped research results and statistically correct calculations are evidence-based practice for choosing between the four attributes. Insurance plans are examined based on two formal variables, namely, quality and price. Each of them can be divided into several sections, in which a particular point or price tag is an attribute. An independent conclusion without statistical techniques is irrational, although it can be based on quantitative data. MAU will allow each parameter to be taken into account and prioritized based on the objectives of the analysis. Thus, the use of the model gives 10/10 points of confidence and comfort of choice.

An insurance plan combines financial and medical benefits for an individual. Empire Family Health Plan was selected as the optimal package based on subjective perception and performance report analysis. First of all, it has high marks in adult, behavioral, and child and adolescent health. The individual package price is lower than the competitors’, and the family plan is more affordable than most alternatives. The MAU technique was applied to a similar study using statistical methods. This model analyzes variables, attributes, and their priorities concerning the appropriateness of one of them. Using this strategy is more time consuming but accurate due to the calculation of the exact numbers. Thus, the MAU is a comfortable and reliable way to compare insurance plans and provides more analytical results.


El Sawalhi, N., & El Agha, O. (2017). Multi-attribute utility theory for selecting an appropriate procurement method in the construction projects. Journal of Construction in Developing Countries, 22(1), 75-96. Web.

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Hahn, W., Seaman, S., & Bikel, R. (2012). Making decisions with multiple attributes: A case in sustainability planning. Graziado Business Review, 15(2).

New York State Department of Health. (2019). An online report on quality performance results for health plans in New York state. New York City. Web.

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