• 대한예방한의학회지
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• 제23권3호
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• pp.1-12
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• 2019

Objectives : Korean national health insurance data is a useful real-world data representing whole medical bills submitted to Health Insurance Review Agency. This study aims to understand recent benefit trend of insurance herbal preparations for treating bronchiectasis(disease code J47) utilizing insurance data. Methods : We reviewed national health insurance claims data from 2013 to 2017 which have main diagnosis or sub diagnosis code of J47 and with the record of prescribing insurance herbal medication. Frequency analysis was performed to analyze the most frequently prescribed prescription. Results & Conclusions : Both the number of claims statement(770 to 1,746cases) and patients(266 to 484) of insurance herbal preparations increased considerably from 2013 to 2017. Top 10 preparations based on the number of claims statement were 'Samso-eum', 'Yeonkyopaedok-san', 'Socheongryong-tang', 'Bojungikgi-tang', 'Hyangsapyungwi-san', 'Yijin-tang', 'Saengmaek-san', 'Jaeumganghwa-tang', 'Ojeok-san' and 'Gungha-tang'. Top 10 preparations based on the number of patients were 'Samso-eum', 'Socheongryong-Tang', 'Saengmaek-san', 'Yeonkyopaedok-san', 'Haengso-tang', 'Hyangsapyungwi-san', Yijin-tang', 'Jaeumganghwa-tang', 'Bojungikgi-tang' and 'Hyeonggaeyeongyo-tang' in respectiv order. Claims of top 10 frequent preparations occupied more than 60% of total claims. We hope this finding to be utilized as basic data for future research of evidence-based bronchiectasis treatment utilizing Korean traditional medicine.

• International Journal of Computer Science & Network Security
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• 제21권9호
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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.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.665-675
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• 2020

The aim of this article is to investigate the relationship between insurance and economic growth at aggregate and disaggregate level for the period 1982-2018. Very few studies have been carried out in this field, with contradictory results and using an aggregate data while, according to different authors, an aggregate data might provide spurious results. The author used Ordinary Least Squares Regressions (OLS) and Granger Causality tests to explore the strength and direction of the relationship between insurance and economic growth at an aggregate level. To check the relationship at disaggregate level life insurance, marine insurance, and property insurance are regressed on trade openness and investment, respectively. Non-life insurance at an aggregate level plays a positive and significant role in promoting economic growth, but life insurance has an insignificant impact on the Pakistan economy. On the other hand, non-life insurances at a disaggregated level such as marine insurance negatively affect a vital part of economic growth, i.e., trade. At the same time, property insurance has a significant and positive role in boosting investment. Life, marine, and property insurance Granger cause economic growth, trade, and investment in a single direction. Nevertheless, is a bi-directional relationship between economic growth and non-life insurance.

• 한국인공지능학회지
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• 제9권1호
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• pp.9-14
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• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• 응용통계연구
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• 제31권6호
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• pp.693-706
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• 2018

노인의 신체기능에 부합하는 복지용구를 제공하는 것은 노인이 가능한 한 오랫동안 자신의 집과 지역사회에서 자립하여 생활할 수 있도록 돕기 위해 매우 중요하다. 본 연구는 수급자의 신체 및 인지 기능 상태를 고려하여 개개인에게 적합한 복지용구 품목을 권고할 수 있는 과학적인 복지용구 표준급여모형 알고리즘을 개발하고자 수행되었다. 모형개발에는 데이터마이닝기법인 의사결정나무를 활용하였다. 수급자 8,084명의 장기요양인정조사자료와 파워어세서가 작성한 표준급여계획, 수급자 특성 자료를 이용하여 데이터를 구축하였고, 15개 복지용구 품목별로 표준급여모형을 개발하였다. 본 연구는 노인장기요양보험의 복지용구 급여계획의 객관성 및 과학성을 확보하고 수급자의 자립생활과 안전을 향상시키는 데에 기여할 것으로 기대된다.

• 한국병원경영학회지
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• 제28권2호
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• pp.9-20
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• 2023

Purpose: This study classified the actual functions of geriatric hospitals and examined the differences in their characteristics, in order to provide a basis for discussions on defining the functions of geriatric hospitals and how to pay for care. Methodology: This study used various administrative data such as health insurance data and long-term care insurance data. Cluster analysis was used to categorize geriatric hospitals. To examine the validity of the cluster analysis results, we conducted a discriminant analysis to calculate the accuracy of the classification. To examine cluster characteristics, we examined structure, process, and outcome indicators for each cluster. Findings: The cluster analysis identified five clusters. They were geriatric hospitals with relatively short stays for cancer patients(cluster 1; cancer patient-centered), geriatric hospitals with relatively large numbers of patients using rehabilitation services(cluster 2; rehabilitation patient-centered), geriatric hospitals with a high proportion of relatively severe elderly patients(cluster 3; severe elderly patient-centered), geriatric hospitals with a high proportion of mildly ill elderly patients with various conditions(cluster 4; mildly ill elderly patient-centered), and geriatric hospitals with a significantly higher proportion of dementia patients(cluster 5; dementia patient-centered). The largest number of geriatric hospitals were categorized in clusters 4 and 5, and the structure and process indicators for these clusters were generally lower than for the other clusters. Practical Implications: We have confirmed the existence of geriatric hospitals where the medical function, which is the original purpose of a geriatric hospital, has been weakened. It has been observed that the quality level of these geriatric hospitals is likely to be lower compared to hospitals that prioritize enhanced medical functions. Therefore, it is suggested to consider the conversion of these geriatric hospitals into long-term care facilities, and careful consideration should be given to the review of care-giver payment coverage.

• 응용통계연구
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• 제22권1호
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• pp.163-170
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• 2009

본 연구는 미래 보험소비자라 할 수 있는 대학생들을 대상으로 보험에 대한 사회적 인식수준을 진단하고 이를 토대로 신뢰받는 보험 산업으로 거듭나기 위한 방안을 제시하는데 그 목적이 있다. 본 연구를 위하여 대학생들을 보험 전공 학생과 비전공 학생으로 크게 구별하여 설문조사를 실시하였고 분석방법은 부분 순위자료(partially ranked data)의 수량화방법을 사용하였다. 대학생 대상 설문분석 결과 보험에 대한 신뢰도 수준은 설문대상 모든 집단이 보험에 대한 신뢰도가 다른 금융권(은행 및 증권)보다 비교적 낮은 것으로 나타났다. 특히 모든 집단이 신뢰도를 저하시키는 가장 큰 요인으로 보험 모집조직의 전문성 부족과 보험금 관련 분쟁 등을 지적하였고, 전공 학생은 부정적 언론 보도를 비전공 학생들은 보험상품 약관의 복잡성 등을 주요 원인으로 나타났다. 보험산업 신뢰도를 제고하기 위해서는 보험상품 및 약관개선을 공통적으로 지적하였으며 보험전공 학생들은 학교보험교육의 강화와 보험의 언론홍보를 통한 보험의 미래 보험상 정립이 가장 중요하다고 지적하였다. 한편 보험 비전공 학생들은 민원발생시 신속한 보상처리 및 보험회사의 윤리경영 및 건전경영을 위한 보험회사의 자체노력이 보험산업의 이미지 제고 방안으로 제시하고 있다.

• 기본간호학회지
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• 제10권3호
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• pp.300-306
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• 2003

Purpose: This study was done to help provide patients with information on medical insurance cost through medical insurance education for nurses, to increase effective management, check on omissions in treatment and appropriateness and accuracy of fees, and to contribute to the economic growth of hospital by providing nurses with necessary knowledge about medical insurance cost. Method: The participants in this study were clinical nurses in general hospitals. The study instrument was a questionnaire developed by the researcher through reference to data for medical insurance education. The data were analyzed with percentages, means, ANOVA, and Duncan method using SPSS PC+10. Result: The results on knowledge of medical insurance according to general characteristics of the nurses showed that there were significant differences according to age: (p=.0036) highest level of education (p=.0007), position (p=.0010) and place where education on medical insurance was received (p=.0093). Conclusion: Continuous in-service education for clinical nurses is reflected in increased knowledge about medical insurance costs but special attention needs to be given to younger nurses and nurses with less education, as well as staff nurses, and those nurses who only received education on medical insurance during their schooling. Accordingly, in-service education is necessary for nurses at the time of orientation so that they have knowledge on standards for recuperation allowance, guidelines to calculate material costs, and guidelines to calculate drug rates. In addition, as medical insurance cost frequently change, all nurses need continuous in-service education.

• Journal of Preventive Medicine and Public Health
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• 제54권1호
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• pp.8-16
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• 2021

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world's first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea's universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA's in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제16권2호
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• pp.137-149
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• 2012

We propose an efficient method to measure the insurance risk of causality insurance companies by using the CreditRisk+ methodology. This method is superior to previous methods in several aspects. Its computation speed is very fast and the input data form is simple. It is able to aggregate both credit risk and insurance risk, so the insurance company can manage the risk in combined manner. In this paper, we propose a mathematical method to obtain the aggregate loss distribution of portfolios having correlation among products or business lines as a general case, and then suggest its implementation algorithm. Finally we apply this method to the real data from Korea Insurance Development Institute (KIDI) and discuss its availability to real applications.