• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.1-12
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• 2021

The purpose of this study is to analyze the medical ecosystem in the post-corona era. In addition, this study introduces a new medical CRM model that allows primary-level hospitals to overcome the economic difficulties and to occupy a competitive advantage in the post-corona era. The medical environment in the post-corona era is expected to be changed by non-face-to-face treatment, reinforcement of public medical care, the transformation of a medical system centered on the primary-level hospitals, and the use of AI and big data technologies. The medical CRM model presented in this study emphasizes the establishment of mutual customer relationships through close information exchange between patients, primary-level hospital, and the government. In the post-corona era, primary-level hospitals should not simply be approached as private hospital pursuing profitability. These should be reestablished as the hospitals that can provide public health care services while ensuring stable profitability.

• Knowledge Management Research
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• v.12 no.3
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• pp.39-58
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• 2011

As the information from today's knowledge-based society alters the awareness of patients and provides a wider selection of medical institutions, the reality of medical institution management is struggling compared to the past. CRM was introduced to domestic hospitals as marketing strategy to dominate the competition under varying medical environment. Thus, this research invests on CRM activity types used in hospitals and the effects of CRM activities toward loyalty and switching intention. Futhermore, we investigate the mediating role of customer relationship commitment and termination in CRM activities. The subjects in this study included three hundred customers who are using hospital settings or who had experience with using the hospital settings. The researcher collected 262 survey questionnaires from May 23th, 2011 to June first. In order to evaluate the hypothesis in this study, structural equation model was analyzed by using AMOS 18.0.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.77-87
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• 2023

Objectives: It is critical to assess community readiness (CR) when implementing childhood obesity prevention programs to ensure their eventual success and sustainability. Multiple tools have been developed based on various conceptions of readiness. One of the most widely used and flexible tools is based on the community readiness model (CRM). This study aimed to adapt the CRM and assess the validity of a community readiness tool (CRT) for childhood obesity prevention programs in Iran. Methods: A Delphi study that included 26 individuals with expertise in 8 different subject areas was conducted to adapt the CRM into a theoretical framework for developing a CRT. After linguistic validation was conducted for a 35-question CR interview guide, the modified interview guide was evaluated for its content and face validity. The quantitative and qualitative analyses were performed using Stata version 13 and MAXQDA 2010, respectively. Results: The Delphi panelists confirmed the necessity/appropriateness and adequacy of all 6 CRM dimensions. The Persian version of the interview guide was then modified based on the qualitative results of the Delphi study, and 2 more questions were added to the community climate dimension of the original CRT. All questions in the modified version had acceptable content and face validity. The final CR interview guide included 37 questions across 6 CRM dimensions. Conclusions: By adapting the CRM and confirming linguistic, content, and face validity, the present study devised a CRT for childhood obesity prevention programs that can be used in relevant studies in Iran.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.101-108
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• 2023

Decision Support Systems (DSS) is an Information Systems (IS) application that aids in decision-making processes for many business concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model and for the purpose of the study we have compared the CRM between patients and hospital management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.915-923
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• 2007

Recently we can see many cases that the CRM Systems are implemented and operated in Hospitals. The reason for such situation is the management environments in medical service market is changing rapidly one hand, and on the other hand the competitions among the Hospitals became more severe. In this paper we try to present the factors and weights as index for the measurement of Hospital CRM's System Performance. To achieve this goal, we derived the primary factors for the success of the CRM Systems based on the precedent researches, and futhermore carry out the verification of the rightness of those factors. For the verification of the rightness of the factors, we employ the Structured-Model-Analysis Method of AMOS. This enhance the meaning of the analysis result of the factors. And we use the AHP method to compare the importance grade of each success factors, because the comparison of importance level of each success factor is very crucial for the measurement of the Hospital CRM's system performance. As a result, we derived the primary factors and analyzed the weights in this paper, which might be used as the guiding Index for the measurement of the Hospital CRM' System Performance.

• Korea Journal of Hospital Management
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• v.10 no.1
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• pp.93-114
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• 2005

The prenatal care is the preventive medical service to help the pregnant mother deliver the healthy baby. It's regular examines give some chances to check-up the healthy conditions. This thesis concentrates on the CRM system to support an effective prenatal care system and prove the effectiveness of it. As CRM is the adapted management related to the customer's own information, it is important to develop the CRM model classified by the patients characteristics. A general hospital in Busan operated the CRM system to carry out the effective prenatal care and there is an analysis to ensure the effectiveness of CRM system for the pregnant women in our maternity ward. The results can be summarized as follows: 1) According to the comparisons with the CRM system, we can conclude the system is desirable. (1) Maternal Age : In the age distribution, the prenatal visit frequency, triple marker freqency, oral GTT and targeted ultrasonography in the experimental group in 30 to 34 years old is higher on the whole. For over 35 years old group, the higher frequency comes out in the oral GTT and targeted ultrasonography and for 25 to 29 years old group the different figure shows just in the targeted ultrasonography. (2) Area of residence: There is a clear difference in all the items in Busan and near area but no sign of difference in prenatal visits and oral GTT in other residencial area. Especially in the targeted ultrasonography the higher figure shows in the experimental group located in the both areas. The targeted ultrasonography is known as the specific examination which should be examined by the specialists, on the contrary the other examinations can be operated in the small clinic. So the public information and seminars related with ultrasonography increases the check-up frequency. The clinic requests some ultrasonographical examinations to the specialists in general hospital. (3) Parity: The clear difference shows that the CRM system causes the prenatal visit frequency to become higher in experimental group. The figure is 9.7 times and 8.6 times each. This is opposite that the past study said multiparity reduced the average prenatal visits. But the result of CRM is considered as the method to help the multiparity understand the importance of the prenatal care. (4) Obstetrical history: In the experimental group of the spontaneous delivery group, the figure is higher in the prenatal visit frequency, triple marker, oral GTT and targeted ultrasonography but the Caesarean section delivery group has higher figure in targeted ultrasonography. (5) In the first check-up, the rate of targeted ultrasonography in under 16 week pregnancy, in the 16 week pregnancy to 32 week pregnancy and the over 32 week pregnancy in the experimental group is upper than the compared one. For the oral GTT, there is a difference in under 16 week pregnancy but no difference in prenatal visits and triple marker. 2) The analysis of characteristics of prenatal care through the decision tree resulted in the fact that the most important variable is the residential area. After the delivery frequency is following, the obstetrical history and maternal age are in order. It is the same result in the triple marker and oral GTT. Consequently it is the same order of important variables in CRM system. The effectiveness of CRM system is proved in this study. The CRM system is a marketing method to control and lead the customers through the segmentation of customer data. It increases the new customer aquisition, maintenance of loyal customers, augmentation of customers value, activation of potential customers and creation of life time customers. So eventually it can enlarge the customers value. The medical institution should make efforts to establish the data base enforced by the customer's information on the underlying ordinary data system to carry out the CRM system effectively. In addition, it should develop the a variety of marketing strategy in order to set up one to one marketing satisfying the needs of individual patients.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.79-87
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• 2010

This paper is proposed that implemental model of customer relationship management system for oriental hospital is designed by customer segmentation using personal information and medical record of outpatients in existing integrated medical information system database. Proposed model can be practical model at once, because it can construct by partial modification of existing medical information system without additional information technology and infrastructure. And, if we use the proper variable and method of customer segmentation according to marketing strategy, it can be flexible customer relationship management system not only improvement of customer satisfaction but also various marketing supports.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.581-594
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• 2011

The traditional method of 3+3 standard design and model-based Bayesian continual reassessment method (CRM) are commonly used in Phase I clinical trials to identify the maximal tolerated dose(MTD) of a new drug. In this paper we review clinical examples of Phase I trials that were carried out in patients with refractory or relapsed leukemia and myelodysplastic syndrome. The recently proposed 3+1+1 design and rolling-6 design can shorten the trial duration, when a very slow accrual of patients with a simple 3+3 standard design may result in the untimely termination of trials. Too conservative approaches in determining the dose levels in Phase I clinical trials can leave clinical investigators unable to accurately determine the MTD. When determining future patient doses, the designs that use a time-to-event CRM can cooperate late toxicities by accounting for the proportion of the observation period of each enrolled patient. With the CRM design, simulations under different scenarios during the trial are important in detecting the under- or over-estimation of the initial estimate of the dose-limiting toxicity rate for each dose level. We present the advantages and drawbacks of the designs used in Phase I clinical trials for leukemia patients.

• Health Policy and Management
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• v.12 no.2
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• pp.1-22
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• 2002

Since the early 1980s scholars have applied latent structure and other type of finite mixture models from various academic fields. Although the merits of finite mixture model are well documented, the attempt to apply the mixture model to medical service has been relatively rare. The researchers aim to try to fill this gap by introducing finite mixture model and segmenting inpatients DB from one general hospital. In section 2 finite mixture models are compared with clustering, chi-square analysis, and discriminant analysis based on Wedel and Kamakura(2000)'s segmentation methodology schemata. The mixture model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture model is to unfix the sample, to Identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. In section 3 and 4 we illustrate results of segmenting 4510 patients data including menial and ratio scales. And then, we show AHP can be identify the attractiveness of each segment, in which the decision maker can select the best target segment.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.10-17
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• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.