• Journal of Information Processing Systems
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• v.4 no.3
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• pp.113-120
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• 2008

Most enterprises have controlled claim data related to marketing, production, trade and delivery. They can extract the engineering information needed to the reliability of unit from the claim data, and also detect critical and latent reliability problems. Existing method which could detect abnormal quality unit lists in early stage from claim database has three problems: the exclusion of fallacy probability in claim, the false occurrence of claim fallacy alarm caused by not reflecting inventory information and too many excessive considerations of claim change factors. In this paper, we propose a process and methods extracting abnormal quality unit lists to solve three problems of existing method. Proposed one includes data extraction process for reliability measurement, the calculation method of claim fallacy alarm probability, the method for reflecting inventory time in calculating claim reliability and the method for identification of abnormal quality unit lists. This paper also shows that proposed mechanism could be effectively used after analyzing improved effects taken from automotive company's claim data adaptation for two years.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.343-357
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• 2014

In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.207-215
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• 2020

The purpose of this study is to investigate the current status of claim management process of general contractors in South Korea. As the claim management becomes more important nowadays, maintaining the process for claim management systematically and consistently becomes more important as well. To improve the claim management process, it is necessary to diagnose the current status of claim management process so companies establish their targets for improvement. This study develops a survey to identify the current status of claim management process that major general contractors in South Korea have. Questions in the survey are classified into four categories including entitlement check, potential claim event check, time bar check, and tasks for substantiation. By conducting a series of statistical analyses with 94 survey data collected from employees working in the general contractor companies in South Korea, this study examines and analyzes their claim management process in terms of the several categories. It is expected that the results contribute to diagnosing how practitioners maintain their claim management, which will help them establish the direction of management enhancement.

• Journal of Information Management
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• v.31 no.2
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• pp.47-65
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• 2000

KINITI implemented a claim system with EDI. This paper presents the way in which electronic data interchange(EDI) can be used to assist in the management of claim information and describes the definition, structures, benefits, problems of EDI and future enhancement.

• Health Policy and Management
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• v.21 no.1
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• pp.77-92
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• 2011

Objectives : This study examined the health policy researchers' needs and their accessibility towards health insurance claim datasets according to their academic capacity. Methods : An online questionnaire to capture relevant proxy variables for academic needs, accessibility, and research capacity was constructed based on previous studies. The survey was delivered to active health policy researchers through three major scholarly associations in South Korea. Seven-hundred and one scholars responded while the survey as open for 12 days (starting on December 20th, 2010). Descriptive statistics and logistic regression analysis were carried out. Results : Regardless of the definition for operational needs, the prevalent needs of survey respondents were not met with the current provision of claim data. Greater research capacity was shown to be correlated with increased demand for claim data along with a positive correlation between attempts to obtain claim datasets and research capacity. A greater research capacity, however, was not necessarily correlated with better accessibility to the claim data. Conclusions : The substantial unmet need for claim data among the healthcare policy research community calls for establishing proactive institutions which could systematically prepare and make available public datasets and provide call-in services to facilitate proper handling of data.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.199-208
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• 2015

An enhanced understanding of the nature of scientific knowledge-what counts as a scientific argument and how scientists justify their claims with evidence-has been central in Korean science instruction. However, despite its importance, scholars are generally concerned about the difficulty of both addressing and improving students' epistemic understanding, especially for students of a young age. This study investigated Korean middle school students' epistemic ideas about claim, data, evidence, and argument when they engage in reading both text-based and data-inscription arguments. Compared to previous studies, Korean middle school students show a sophisticated understanding of the role of claim and evidence. Yet, these students think that there is only a single way of interpreting data. When comparing students' ideas from text-based and data-inscription arguments, the majority of Korean students barely perceive text description as evidence and recognize only measured data as evidence.

• IE interfaces
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• v.23 no.2
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• pp.176-181
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• 2010

Warranty claim data analysis is a useful tool for the manufacturer because it contains many useful informations regarding reliability of the product in the real-world environments. Because of the nature of uncertainty and the incompleteness of data, some bias patterns are observed on warranty claim rate known as 'spikes'. Two types of spikes are considered. One is due to manufacturing-related failures. The other is caused by customer's behavior. This paper proposes a model by considering two types of spikes. Warranty claim data is analyzed with the proposed model. To represent spikes observed on the early warranty period, we classify failures into manufacturing-related failures and usage-related failures. Uniform distribution is assumed for the time delayed to diagnose and report by customers. By reducing maximum value of the delayed time by customers, the proposed model characterizes customer's rush in the vicinity of the warranty expiration limit. Experimental results by using the real warranty claim data show that the proposed model is better than the existing one in respect to MSE(Mean Squared Error). Moreover it is expected to estimate the failure rate more realistically with proposed model because it considers the delayed time to diagnose and report by customers.

• Journal of Preventive Medicine and Public Health
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• v.33 no.4
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• pp.393-401
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• 2000

Objectives : To evaluate the impacts of the DRG payment system on the behavior of medical insurance claimants. Specifically, we evaluated the case-mix index, the numbers of diagnosis and procedure codes utilized, and the corresponding rate of diagnosis codes before, during and after implementation of the DRG payment system. Methods : In order to evaluate the case-mix index, the number of diagnosis and procedure codes utilized, we used medical insurance claim data from all medical facilities that participated in the DRG-based Prospective Payment Demonstration Program. This medical insurance claim data consisted of both pre-demonstration program data (fee-for-service, from November, 1998 to January, 1999) and post-demonstration program data (DRG-based Prospective Payment, from February, 1999 to April, 1999). And in order to evaluate the corresponding rate of diagnosis codes utilized, we reviewed 820 medical records from 20 medical institutes that were selected by random sampling methods. Results : The case-mix index rate decreased after the DRG-based Prospective Payment Demonstration Program was introduced. The average numbers of different claim diagnosis codes used decreased (new DRGs from 2.22 to 1.24, and previous DRGs from 1.69 to 1.21), as did the average number of claim procedure codes used (new DRGs from 3.02 to 2.16, and previous DRGs from 2.97 to 2.43). With respect to the time of participation in the program, the change in number of claim procedure codes was significant, but the change in number of claim diagnosis codes was not. The corresponding rate of claim diagnosis codes increased (from 57.5% to 82.6%), as did the exclusion rate of claim diagnosis codes (from 16.5% to 25.1%). Conclusions : After the implementation of the DRG payment system, the corresponding rate of insurance claim codes and the corresponding exclusion rate of claim diagnosis codes both increased, because the inducement system for entering the codes for claim review was changed.

• Journal of Preventive Medicine and Public Health
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• v.39 no.5
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1147-1157
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• 2005

Bonus-Malus system is generally constructed based on claim frequency and Bayesian credibility model is used to represent claim frequency distribution. However, there is a problem with traditionally used credibility model for the purpose of constructing bonus-malus system. In traditional Bonus-Malus system adopted credibility model, individual estimates of premium rates for insureds are determined based solely on the total number of claim frequency without considering when those claims occurred. In this paper, a new model which is a modification of structural time series model applicable to counting time series data are suggested. Based on the suggested model relatively higher premium rates are charged to insured with more claim records.