• Title/Summary/Keyword: Medical Data

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A Study on the Trend of Childhood Common Cold Treatment Using Health Big Data (보건의료 빅데이터를 활용한 소아 감기 치료의 동향 조사)

  • Kim, Tae Jeong;Sung, Hyun Kyung;Min, Sang Yeon
    • The Journal of Pediatrics of Korean Medicine
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    • v.36 no.2
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    • pp.1-12
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    • 2022
  • Objectives We analyzed visiting patterns to medical institutions and cost per visit according to the common cold patients aged 0-19 years. We analyzed Korean medical treatment for common cold. Methods Using the Pediatric Patient Sample data of the Health Insurance Review and Assessment Service (HIRA-PPS), we analyzed the data on health insurance claims of approximately 1 million people from 2017 to 2019. The data included the number of patients who visited the hospital due to common cold for the first and second time, the ratio of second visits by type of medical institution, and the status of prescriptions in Korean medical institutions. Results The number of patients visiting healthcare providers for common cold was higher in Western medical institutions than in Korean medical institutions. However, the number of second visits was higher in Korean medical institutions. Acupuncture is the most commonly used medical treatment in Korean medical institutions for common cold. Herbal medicine for common cold was usually prescribed for 2-3 days for children and adolescents. Conclusions Although the average medical cost of Korean medical institutions was higher than that of Western medical institutions, the rate of second visits to Korean medical institutions was higher because of the demand for Korean medical treatment

A Study of the virtue terms in herbal medicine (본초 효능 용어에 관한 연구)

  • Oh, Yong-Taek;Lee, Byung-Wook;Kim, Eun-Ha
    • Journal of Korean Medical classics
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    • v.23 no.5
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    • pp.35-50
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    • 2010
  • By grouping freshly the virtue terms used in herbal medicine, we are apt to establish the position coordinates of concepts and raise the level of the herbal virtue research in future. As the terms related to the herbal virtue used in herbal medicine are used with the virtue terms mingled with the chief treatable disease terms, it's hard to use the herbal virtue data only. And though the virtues terms imply many data like medical act data or medical operation data, we can't use them fully. We sort the terms related to the herbal virtue into the virtue terms and the chief treatable disease terms and acquire many data like medical act data or medical operation data and group the data by same attribute. At this time in the process of classification we establish sort standards inductively, put relations between the attributes in order, out of this result we grasp the actual conditions of the virtue terms used now, and show useful data for herbal virtue research in future. We got the chief treatable disease terms from the ones related to the herbal virtue, acquired a lot of data from the virtue terms and grouped the data by the same attribute. We established a proper standard inductively in the process of classification, put the relations between the attributes in order, grasped the actual conditions of the virtue terms in use at the moment out of the result of the classification and presented the applicable data for the herbal virtue research in future.

A Secure Medical Information Management System for Wireless Body Area Networks

  • Liu, Xiyao;Zhu, Yuesheng;Ge, Yu;Wu, Dajun;Zou, Beiji
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.1
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    • pp.221-237
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    • 2016
  • The wireless body area networks (WBANs) consist of wearable computing devices and can support various healthcare-related applications. There exist two crucial issues when WBANs are utilized for healthcare applications. One is the protection of the sensitive biometric data transmitted over the insecure wireless channels. The other is the design of effective medical management mechanisms. In this paper, a secure medical information management system is proposed and implemented on a TinyOS-based WBAN test bed to simultaneously address these two issues. In this system, the electronic medical record (EMR) is bound to the biometric data with a novel fragile zero-watermarking scheme based on the modified visual secret sharing (MVSS). In this manner, the EMR can be utilized not only for medical management but also for data integrity checking. Additionally, both the biometric data and the EMR are encrypted, and the EMR is further protected by the MVSS. Our analysis and experimental results demonstrate that the proposed system not only protects the confidentialities of both the biometric data and the EMR but also offers reliable patient information authentication, explicit healthcare operation verification and undeniable doctor liability identification for WBANs.

An Analysis of Emergency Care Based on Prehospital Care Reports (일부 구급대의 응급처치활동 분석 - 구급활동일지를 중심으로 -)

  • Uhm, Tai-Hwan
    • The Korean Journal of Emergency Medical Services
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    • v.9 no.1
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    • pp.101-109
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    • 2005
  • The purpose of this study which was done by 250 Prehospital Care Reports(PCRs) survey of some squads in Seoul Metropolitan Fire & Disaster Management Department was to improve prehospital emergency care by means of quality management. The data were collected in 3 squads from Jun. 21 to Jul. 18, 2004 and analyzed by using SPSS Win 12.0 Version. The conclusions from this study were summarized as follows. The mean time of Event to treatment interval was $4.6{\pm}4.3$ minutes and 49.2% arrived at patient within 4 minutes. Platinum minute was observed 61.1% of verbal response, 73.3% of painful response, 77.8% of unresponsive. The great majority of patients couldn't receive advanced life support on account of limited scope of practice and strict direct medical control in the Emergency Medical Services Act. Data from quality improvement activity will be useful to expand indirect medical control which is able to activate prehospital care. To utilize PCR for quality improvement. It has to have data elements, run data, patient data, check boxes, narrative including US DOT's minimum data set.

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Coverage, Density and Completeness of Sources used in Tehran Metropolitan Area Cancer Registry: According to the Data of Esophageal Cancer, 2003-2007

  • Aghaei, Abbas;Najafi, Farid;Mosavi-Jarrahi, Alireza;Ahmadi-Jouibari, Toraj
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.8
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    • pp.3617-3619
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    • 2012
  • Background: The completeness of cancer registration is a major validity index of any reported cancer incidence. The present study aimed to evaluate the esophageal cancer incidence registered in the Tehran Metropolitan Area Cancer Registry. Materials and methods: The data on esophageal cancer abstracted from three sources of 1) pathology departments, 2) medical records, and 3) death certificates during 2003 till 2007 were utilized. The completeness of the data sources were evaluated using coverage (defined as the proportion of a community population with esophageal cancer identified by the source) and density (defined as the proportion of non-empty fields of the data by source). Results: A total 1,404 cases of esophageal cancer were reported for the duration of the study. Pathology provided 771, medical records 432, and death certificates 609. The coverage was 0.55 for pathology, 0.31 for medical records, and 0.43 for death certificates. The respective density values were 0.82, 0.96 and 0.98, respectively. Pathology (0.45) was the most complete source followed by medical records (0.42), and death certificates (0.29). Discussion: A low degree of completeness dictates putting more effort into case finding plus abstracting data more thoroughly.

Applications and Issues of Medical Big Data (의료 빅데이터의 활용과 해결과제)

  • Woo, SungHee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.545-548
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    • 2016
  • Big data is all data generated in the digital environment which has a variety of large and a short life cycle. The amount and type of data are becoming more and more produced on a larger scale, as a smart phone and the internet are popular, and consequently it has been converted into time for users to take advantage and extract only the valuable and useful data from the generated big data. Big data can also be applied to the medical industry and health sectors. It has created the synergy to be fused with ICT such as IoT, smart healthcare, and so on. However, there will be challenges like data security in order securely to use a meaningful and useful vast amounts of data. In this study, we analyze the future prospects of the healthcare, applications and issues of medical big data, and the expected challenges.

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The Design of Integrated system for the cloud-based medical Information sharing

  • Lee, Kwang-Cheol;Hwang, Chigon;Lee, Seong Ro;Lee, Jong-Yong;Jung, Kye-Dong
    • International journal of advanced smart convergence
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    • v.4 no.2
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    • pp.145-153
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    • 2015
  • Development of IT technology, in combination with the medical area, a number of developments have been made of the digital advanced medical devices, also increased interest in health, sharing of medical information has become increasingly necessary. Standardization for medical information sharing to satisfy these requirements have been studied. However, the medical information system is to build a system independent hospital itself, is difficult to share and exchange medical data with other medical institutions. In this paper, we provide a medical cloud system that can share medical information. Use DBaaS of cloud services. And is an international standard to have a HL7 share information by forming a meta-schema, each of the data transfer, the format of the document oriented data solves the heterogeneity between hospitals. Extracts the required field name of examination information, to exchange information with each of the local information and mapping. Health diagnostic information in the present study and diagnosis through accurate information sharing and exchange is possible ongoing management.

Big data Analysis using Python in Agriculture Forestry and Fisheries

  • Kim, So hee;Kang, Min Soo;Jung, Yong Gyu
    • International journal of advanced smart convergence
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    • v.5 no.1
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    • pp.47-50
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    • 2016
  • Big Data is coming rapidly in recent times and keep the vast amount of data was utilized them. These data are utilized in many fields in particular, based on the patient data in the medical field to increase the therapeutic effect, as well as re-incidence to better treatment, lowering the readmission rates increased the quality of life. In this paper it is practiced to report basis of the analysis and verification of data using python. And it can be analyzed the data through a simple formula, from Select reason of Python to how it used; by Press analysis of Agriculture, Forestry and Fisheries research. In this process, a simple formula can be used that expression for analyzing the actual data so it taking advantage of the use of functions in real life.

A study on the policy of de-identifying unstructured data for the medical data industry (의료 데이터 산업을 위한 비정형 데이터 비식별화 정책에 관한 연구)

  • Sun-Jin Lee;Tae-Rim Park;So-Hui Kim;Young-Eun Oh;Il-Gu Lee
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.85-97
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    • 2022
  • With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

Estimation of Disease Code Accuracy of National Medical Insurance Data and the Related Factors (의료보험자료 상병기호의 정확도 추정 및 관련 특성 분석 -법정전염병을 중심으로-)

  • Shin, Eui-Chul;Park, Yong-Mun;Park, Yong-Gyu;Kim, Byung-Sung;Park, Ki-Dong;Meng, Kwang-Ho
    • Journal of Preventive Medicine and Public Health
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    • v.31 no.3 s.62
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    • pp.471-480
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    • 1998
  • This study was undertaken in order to estimate the accuracy of disease code of the Korean National Medical Insurance Data and disease the characteristics related to the accuracy. To accomplish these objectives, 2,431 cases coded as notifiable acute communicable diseases (NACD) were randomly selected from 1994 National Medical Insurance data file and family medicine specialists reviewed the medical records to confirm the diagnostic accuracy and investigate the related factors. Major findings obtained from this study are as follows : 1. The accuracy rate of disease code of NACD in National Medical Insurance data was very low, 10.1% (95% C.I. : 8.8-11.4). 2. The reasons of inaccuracy in disease code were 1) claiming process related administrative error by physician and non-physician personnel in medical institutions (41.0%), 2) input error of claims data by key punchers of National Medical Insurer (31.3%) and 3) diagnostic error by physicians (21.7%). 3. Characteristics significantly related with lowering the accuracy of disease code were location and level of the medical institutions in multiple logistic regression analysis. Medical institutions in Seoul showed lower accuracy than those in Kyonngi, and so did general hospitals, hospitals and clinics than tertiary hospitals. Physician related characteristics significantly lowering disease code accuracy of insurance data were sex, age group and specialty. Male physicians showed significantly lower accuracy than female physicians; thirties and fortieg age group also showed significantly lower accuracy than twenties, and so did general physicians and other specialists than internal medicine/pediatric specialists. This study strongly suggests that a series of policies like 1) establishment of peer review organization of National Medical Insurance data, 2) prompt nation-wide expansion of computerized claiming network of National Medical Insurance and 3) establishment and distribution of objective diagnostic criteria to physicians are necessary to set up a national disease surveillance system utilizing National Medical Insurance claims data.

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