Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record

碩士 === 國立高雄應用科技大學 === 資訊工程系 === 106 === Many medical businesses start with "finding the right patients from medical records". How to efficiently and quickly find patients meeting certain criteria from a large number of medical records is a frequently encountered problem by medical personne...

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Main Authors: WENG, KUO-HSUN, 翁國勛
Other Authors: LUO, MON-YEN
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/62m4j8
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spelling ndltd-TW-106KUAS03920032019-05-16T00:52:39Z http://ndltd.ncl.edu.tw/handle/62m4j8 Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record 運用巨量資料技術於電子病歷系統之分散式病例檢索應用研究 WENG, KUO-HSUN 翁國勛 碩士 國立高雄應用科技大學 資訊工程系 106 Many medical businesses start with "finding the right patients from medical records". How to efficiently and quickly find patients meeting certain criteria from a large number of medical records is a frequently encountered problem by medical personnel. Electronic medical records (EHR) are an important source of data for medical big data. EHR have sufficient integrity and representativeness for the record of patients' medical history. However, the use of EHR by medical institutions is often limited to the most original purpose of medical services and fee declarations. It may not be possible to use EHR for secondary use in an efficient manner because of the lack of introduction of relevant information technology, and the value of medical big data cannot be realized. There are restrictions on the methods available to existing medical institutions to "find the right patients from medical records.” Searching for patients based on a single type of information (such as only based on administrative data, only based on radiology reports) may not accurately identify patients who meet the conditions. The performance and scalability of multi-condition query, which queries multiple type of medical record at the same time, is a challenge in the context of medical big data Big-data technology, which has received rapid attention in recent years, is being gradually adopted in the medical and biomedical fields and has achieved certain results, due to characteristics such as easier horizontal expansion which is suitable for processing medical big data. This study proposes two different versions of system to solve the problem of multi-condition query: one system applies big-data technology such as NoSQL and Apache Spark, and another one applies traditional relational database management system. The study then compare the performance between the two to determine whether big-data technology is more suitable for processing multi-condition queries and explore its future feasibility in other medical businesses. LUO, MON-YEN 羅孟彥 2018 學位論文 ; thesis 48 zh-TW
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description 碩士 === 國立高雄應用科技大學 === 資訊工程系 === 106 === Many medical businesses start with "finding the right patients from medical records". How to efficiently and quickly find patients meeting certain criteria from a large number of medical records is a frequently encountered problem by medical personnel. Electronic medical records (EHR) are an important source of data for medical big data. EHR have sufficient integrity and representativeness for the record of patients' medical history. However, the use of EHR by medical institutions is often limited to the most original purpose of medical services and fee declarations. It may not be possible to use EHR for secondary use in an efficient manner because of the lack of introduction of relevant information technology, and the value of medical big data cannot be realized. There are restrictions on the methods available to existing medical institutions to "find the right patients from medical records.” Searching for patients based on a single type of information (such as only based on administrative data, only based on radiology reports) may not accurately identify patients who meet the conditions. The performance and scalability of multi-condition query, which queries multiple type of medical record at the same time, is a challenge in the context of medical big data Big-data technology, which has received rapid attention in recent years, is being gradually adopted in the medical and biomedical fields and has achieved certain results, due to characteristics such as easier horizontal expansion which is suitable for processing medical big data. This study proposes two different versions of system to solve the problem of multi-condition query: one system applies big-data technology such as NoSQL and Apache Spark, and another one applies traditional relational database management system. The study then compare the performance between the two to determine whether big-data technology is more suitable for processing multi-condition queries and explore its future feasibility in other medical businesses.
author2 LUO, MON-YEN
author_facet LUO, MON-YEN
WENG, KUO-HSUN
翁國勛
author WENG, KUO-HSUN
翁國勛
spellingShingle WENG, KUO-HSUN
翁國勛
Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
author_sort WENG, KUO-HSUN
title Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
title_short Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
title_full Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
title_fullStr Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
title_full_unstemmed Study of Applying Big data Technologies to Case-Finding on Distributed electronic health record
title_sort study of applying big data technologies to case-finding on distributed electronic health record
publishDate 2018
url http://ndltd.ncl.edu.tw/handle/62m4j8
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