• The Journal of the Korean life insurance medical association
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• v.28 no.1_2
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• pp.31-35
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• 2009

Background : Many of internists have been working for insurance industry. Insurance medicine is use of medical knowledge for insurance industry. There is social role of insurance medicine in terms of soundness of insurance administration. Recently social role of internists also have been being watched. Although theme of insurance medicine is medical risk selection, insurance claims administration also needs medical experts'opinion. There are not any corroborative study of medical consulting for insurance claims. Among insurance industry, someone called this medical review of insurance claims as 'medical claims review'. Aim : To investigate usefulness of medical review of insurance claims. Design : Questionnaire survey with claim staffs in one of insurance claim adjustment company in Korea. Methods : 265 claim staffs were divided into 4 groups and conducted survey using a questionnaire of 20 questions. Utility score, job satisfaction score, and difficult factors of claims administration were measured. Results : Utility score and job satisfaction score are highest in medical claims review group. The most difficult in claim administration to claim staffs was demonstrated to medical knowledge. Conclusion : Medical review of insurance claims is proved to be worthy. Document-based consulting method, namely medical claims review, is more useful than telephone-based simple query among claim staffs...Subjects of the medical claims review are medical record and it's principle is independent medical examination with evidence-based approach, it also has role of protecting fraud of insurance claims. Two main question types of medical claims review are verification and advice.

• The Journal of the Korean life insurance medical association
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• v.30 no.2
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• pp.8-11
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• 2011

Insurance medicine has been known to medical risk selection. The role of insurance medicine is sound maintenance of insurance system. So it's function is medical underwriting of life risks. However, emerging market has insufficient medical epidemiological research that is necessary for estimation of extra-risk and such market is usually lack of full understanding of life insurance among insurance customers. This problem makes difficult of performing the medical underwriting, as an original insurance medicine. Medical contributions at the stage of claims adjudication comparing the coverage provided in the product, with the information provided in the claims, based on medical records and the agreement between them. This is called medical verification. The insurance doctors can also use their medical knowledge to help the claims staff with informing claimants about the medical basis of claims decisions.

• The Journal of the Korean life insurance medical association
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• v.32 no.1
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• pp.21-27
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• 2013

In case of neoplasm claims, it is important to make a decision of differentiating malignant and benign. In Korean insurance market, there are many insurance products that cover cancer. In the insurance claims adjustment, differentiation between malignant and benign is according to histologic findings. However there are many neoplasms of bad clinical course in spite of benign histopathologic classification. In this article; astrocytoma, thymoma, gastrointestinal stromal tumor, colonic intramucosal carcinoma, gastric high grade adenoma/dysplasia, carcinoid tumor, MALT lymphoma, revision of Korean Classification of Disease-6th edition, and bladder tumors are reviewed in terms of differentiation between malignant and benign in the insurance claims. It may be helpful for claims staff to review important neoplasms in terms of differentiation between malignant and benign.

• The Journal of the Korean life insurance medical association
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• v.26
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• pp.31-39
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• 2007

Background and main issue: In the Korean insurance market, an outstanding issue is the decrease of margin of risk ratio. This affects the solvency and profitability of insurance companies. Insurance medicine, which has been developed in Western countries, is so-called medical risk selection or medical underwriting. Medical risk selection is based on clinical follow-up study and mortality analysis methodology. Unfortunately, there have been few clinical follow-up studies, and no intercompany disease analysis system is available in the Korean insurance market. In practice, we use underwriting guidelines, which were developed by some global reinsurance companies. However, these guidelines were developed under clinical follow-up studies performed abroad. So, we cannot rule out underestimation of excess mortality factors such as mortality ratio, excess death rate, and life expectancy. It is necessary to perform medical assessment in claims administration. Comparing the insured's statement by medical records with products' benefit according to this procedure, we can make sound claim decisions and participate in the role of sound underwriting. We can call this scientific procedure as the verification of medical claims review. Another area of medical claims review is medical counsel for claims staff. Result: There is another insurance medicine in addition to medical risk selection. Independent medical assessment by medical records of insured is medical claims review. Medical claims review is composed of verification and counsel.

• The Journal of the Korean life insurance medical association
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• v.29 no.2
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• pp.33-35
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• 2010

Multiple myeloma is characterized by the neoplastic proliferation of a single clone of plasma cells producing a monoclonal immunoglobulin and it is frequently associated with primary amyloidosis. I experienced a medical claims review case of plasma cell dyscrasia with primary amyloidosis. This medical consulting work to insurance claims will be helpful for another similar claims administration.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.323-336
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• 2024

The accurate forecasting of insurance claims is a critical component for insurers' risk management decisions. Hierarchical Bayesian parametric (BP) models can be used for health insurance claims forecasting, but they are unsatisfactory to describe the claims distribution. Therefore, Bayesian nonparametric (BNP) models can be a more suitable alternative to deal with the complex characteristics of the health insurance claims distribution, including heavy tails, skewness, and multimodality. In this study, we apply both a BP model and a BNP model to predict group health claims using simulated and real-world data for a private life insurer in Indonesia. The findings show that the BNP model outperforms the BP model in terms of claims prediction accuracy. Furthermore, our analysis highlights the flexibility and robustness of BNP models in handling diverse data structures in health insurance claims.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.125-131
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• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.565-584
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• 2024

More than 1 million automobile insurance repairs occur per year globally, and the related repair costs add up to astronomical amounts. Insurance companies and repair shops are spending a great deal of money on manpower every year to claim reasonable insurance repair costs. For this reason, promptly predicting insurance claims for vehicles in accidents can help reduce social costs related to auto insurance. Several recent studies have been conducted in auto insurance repair prediction using variables such as photos of vehicle damage. We propose a new model that reflects auto insurance repair characteristics to predict auto insurance repair claims through an association rule method that combines gradient descent and location information. This method searches for the appropriate number of rules by applying the gradient descent method to results generated by association rules and eventually extracting main rules with a distance filter that reflects automobile part location information to find items suitable for insurance repair claims. According to our results, predictive performance could be improved by applying the rule set extracted by the proposed method. Therefore, a model combining the gradient descent method and a location-based association rule method is suitable for predicting auto insurance repair claims.

• The Korean Journal of Health Service Management
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• v.11 no.1
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• pp.27-42
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• 2017

Objectives : This study analyzes the characteristics of hospital organization structures, insurance claims reviews and assessment tasks and their effects on hospitals in Pusan. Methods : The data for this study were collected through interview and self-administered surveys in 109 hospitals. The study included only - hospitals with a minimum of 50beds and excluded those providing only dental, psychiatric, or long-term care. Results : The findings of this study state that the number of beds has an influence on the organizitional structure. Conclusions : Hospital managements should seek human resources management(the insurance claims reviewer and evaluator) schemes that take into account the characteristics of the medical institution. In addition, insurance claims review and assessment tasks in hospitals require considerable knowledge and experience, and hospitals should be equipped with staff that have the relevant expertise. Therefore, to further deepen knowledge, comprehensive training should be continuously carried out in order to produce specialists in claims review and assessment.

• The Journal of the Korean life insurance medical association
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• v.32 no.2
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• pp.33-38
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• 2013

Coronary artery diseases are very important agenda in the insurance medicine. Insurance medicine is defined as using medical knowledge for insurance administration such as underwriting, claims, and customer satisfaction. This review article contains review of coronary artery disease in terms of insurance medicine. Estimation of extra-risks for acute myocardial infarction are MR of 349% and EDR of 41‰. In medical underwriting, individual life applicants can be assessed by Framingham's CHD risk assessment model. In claims, medical claims review is a useful method of consulting for claims staffs. Several diagnostic criteria of acute myocardial infarction are introduced in time. The universal definition of myocardial infarction by ESC/ACCF/WHF was demonstrated the most valuable predictor of 10-year mortality. Contents for State-Of-The-Art of the coronary artery disease are current antithrombotics. There are many novel anti-thrombotic agents such as ticagrelol, dabigatran, rivaroxaban, and pegnivacogin.