图书情报工作

图书情报工作 >

2023 , Vol. 67 >Issue 15: 35 - 43

DOI: https://doi.org/10.13266/j.issn.0252-3116.2023.15.004

专题：数据价值与数据创新研究

健康医疗大数据价值挖掘分析框架构建

  • 张卫东 ,
  • 陈希鹏 ,
  • 杨斯涵
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  • 吉林大学商学与管理学院 长春 130012
张卫东,教授,博士生导师,E-mail:wdzhang@jlu.edu.cn;陈希鹏,博士研究生;杨斯涵,硕士研究生。

收稿日期: 2023-01-03

  修回日期: 2023-04-28

  网络出版日期: 2023-08-03

基金资助

本文系吉林大学“中国式现代化道路”与“人类文明新形态”哲学社会科学研究创新团队项目“推进人类数字生态文明：数字化转型视域下的数据价值与数据创新”（项目编号：2022CXTD20）研究成果之一。

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Construction of Value Mining Analytical Framework for Big Data in Healthcare

  • Zhang Weidong ,
  • Chen Xipeng ,
  • Yang Sihan
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  • School of Business and Management, Jilin University, Changchun 130012

Received date: 2023-01-03

  Revised date: 2023-04-28

  Online published: 2023-08-03

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摘要

[目的/意义] 为顺应健康信息学领域相关研究从剖面化向体系化转型的趋势，以整合海量多源异构健康医疗大数据、充分挖掘其核心价值为目标，构建一个集成多种工具、方法和管理应用的综合健康医疗大数据价值挖掘分析框架。[方法/过程] 在系统梳理国内外研究和实践的基础上，提出综合健康医疗大数据价值挖掘分析框架，以数据生命周期理论为基本逻辑，在不同结构层级中嵌入相应的目标价值、工具方法和管理应用，重点突破健康医疗大数据分析应用中的瓶颈，实现健康医疗大数据的价值创新。[结果/结论] 综合健康医疗大数据价值挖掘分析框架包含数据采集、数据整合、价值挖掘、数据可视化、数据管理5个层次，每个层次的价值目标和工具方法集合能够满足当前研究和实践的一般需求，在公共医疗卫生和个人健康等领域具有较大的应用空间。

关键词： 健康医疗大数据; 健康信息学; 价值挖掘; 大数据分析; 云计算

本文引用格式

张卫东 , 陈希鹏 , 杨斯涵 . 健康医疗大数据价值挖掘分析框架构建[J]. 图书情报工作, 2023 , 67(15) : 35 -43 . DOI: 10.13266/j.issn.0252-3116.2023.15.004

Abstract

[Purpose/Significance] To comply with the trend of healthcare informatics research shifting from sectional to systematic, this paper suggests providing a comprehensive healthcare big data value mining framework that contains multiple tools, methods, and management applications, aiming at integrating massive multisource heterogeneous data in healthcare and deeply mining hidden core values.[Method/Process] Based on the systematical combination of relevant research and practice at home and abroad, this study built a comprehensive healthcare big data value mining framework by taking the data life cycle theory as the basic logic and embedding corresponding target values, methods, and management in each progress. The framework's purpose was to break through the bottleneck in the implementation of big data analytics in healthcare and to realize the value innovation of big data in healthcare.[Result/Conclusion] The comprehensive healthcare big data value mining framework contains five phases:data collection, data integration, value mining, data visualization, and data management. The value objectives and the set of mechanisms at each progress can meet the general needs of current research and practice and have contributed to the improvement of applications in areas including public healthcare and personal healthcare.

Key words： big data in healthcare; health informatics; value mining; big data analytics; cloud computing

参考文献

[1] 中华人民共和国中央人民政府.中共中央国务院印发《"健康中国2030"规划纲要》[EB/OL].[2023-05-20].http://www.gov.cn/zhengce/2016-10/25/content_5124174.htm.
[2] 周晓英, 裴俊良.健康信息学的学科范畴与中国健康信息学的发展——兼述健康信息学学科建设与发展学术研讨会[J].中国图书馆学报, 2022, 48(2):76-93.
[3] SHILO S, ROSSMAN H, SEGAL E.Axes of a revolution:challenges and promises of big data in healthcare[J].Nature medicine, 2020, 26(1):29-38.
[4] 朱庆华, 杨梦晴, 赵宇翔, 等.健康信息行为研究:溯源、范畴与展望[J].中国图书馆学报, 2022, 48(2):94-107.
[5] 柴国荣, 汪佳颖."健康中国"战略下医疗健康大数据的价值挖掘与实现[J].电子政务, 2022(6):99-110.
[6] HTET H, KHAING S S, MYINT Y Y.Tweets sentiment analysis for healthcare on big data processing and IoT architecture using maximum entropy classifier[C]//Proceedings of the first international conference on big data analysis and deep learning.Singapore:Springer, 2019:28-38.
[7] KER J, WANG L, RAO J, et al.Deep learning applications in medical image analysis[J].Ieee access, 2017, 6:9375-9389.
[8] MIOTTO R, LI L, KIDD B A, et al.Deep patient:an unsupervised representation to predict the future of patients from the electronic health records[J].Scientific reports, 2016, 6(1):1-10.
[9] ALI F, EL-SAPPAGH S, ISLAM S M R, et al.An intelligent healthcare monitoring framework using wearable sensors and social networking data[J].Future generation computer systems, 2021, 114:23-43.
[10] 顾天阳, 赵旺, 曹林.跨组织医疗健康大数据聚合与案例知识推理方法研究[J].情报科学, 2022, 40(3):40-44.
[11] 杨善林, 丁帅, 顾东晓, 等.医疗健康大数据驱动的知识发现与知识服务方法[J].管理世界, 2022, 38(1):219-229.
[12] ZHANG Y, QIU M, TSAI C W, et al.Health-CPS:healthcare cyber-physical system assisted by cloud and big data[J].IEEE systems journal, 2015, 11(1):88-95.
[13] PASHAZADEH A, NAVIMIPOUR N J.Big data handling mechanisms in the healthcare applications:a comprehensive and systematic literature review[J].Journal of biomedical informatics, 2018, 82:47-62.
[14] RAJABION L, SHALTOOKI A A, TAGHIKHAH M, et al.Healthcare big data processing mechanisms:the role of cloud computing[J].International journal of information management, 2019, 49:271-289.
[15] HASHEM I A T, YAQOOB I, ANUAR N B, et al.The rise of "big data" on cloud computing:review and open research issues[J].Information systems, 2015, 47:98-115.
[16] eScholarship.Primer on data management:what you always wanted to know[EB/OL].[2023-06-03].https://escholarship.org/uc/item/7tf5q7n3.
[17] WANG Y, KUNG L A, BYRD T A.Big data analytics:understanding its capabilities and potential benefits for healthcare organizations[J].Technological forecasting and social change, 2018, 126:3-13.
[18] TA V D, LIU C M, NKABINDE G W.Big data stream computing in healthcare real-time analytics[C]//2016 IEEE international conference on cloud computing and big data analysis.Piscataway:IEEE, 2016:37-42.
[19] WU P Y, CHENG C W, KADDI C D, et al.Omic and electronic health record big data analytics for precision medicine[J].IEEE transactions on biomedical engineering, 2016, 64(2):263-273.
[20] HEMINGWAY H, ASSELBERGS F W, Danesh J, et al.Big data from electronic health records for early and late translational cardiovascular research:challenges and potential[J].European heart journal, 2018, 39(16):1481-1495.
[21] DASH S, SHAKYAWAR S K, SHARMA M, et al.Big data in healthcare:management, analysis and future prospects[J].Journal of big data, 2019, 6(1):1-25.
[22] RAMESH T, SANTHI V.Exploring big data analytics in health care[J].International journal of intelligent networks, 2020, 1:135-140.
[23] COZZOLI N, SALVATORE F P, FACCILONGO N, et al.How can big data analytics be used for healthcare organization management? literary framework and future research from a systematic review[J].BMC health services research, 2022, 22(1):1-14.
[24] WANG Y, HAJLI N.Exploring the path to big data analytics success in healthcare[J].Journal of business research, 2017, 70:287-299.
[25] MIOTTO R, WANG F, WANG S, et al.Deep learning for healthcare:review, opportunities and challenges[J].Briefings in bioinformatics, 2018, 19(6):1236-1246.
[26] ELSEBAKHI E, LEE F, SCHENDEL E, et al.Large-scale machine learning based on functional networks for biomedical big data with high performance computing platforms[J].Journal of computational science, 2015, 11:69-81.
[27] CAMACHO D M, COLLINS K M, POWERS R K, et al.Nextgeneration machine learning for biological networks[J].Cell, 2018, 173(7):1581-1592.
[28] GRAHAM S, DEPP C, LEE E E, et al.Artificial intelligence for mental health and mental illnesses:an overview[J].Current psychiatry reports, 2019, 21(11):1-18.
[29] FIROUZI F, RAHMANI A M, MANKODIYA K, et al.Internetof-Things and big data for smarter healthcare:from device to architecture, applications and analytics[J].Future generation computer systems, 2018, 78:583-586.
[30] GAJRA A, ZETTLER M E, MILLER K A, et al.Augmented intelligence to predict 30-day mortality in patients with cancer[J].Future oncology, 2021, 17(29):3797-3807.
[31] FENG W, LI G, ZHAO H.Research on visualization and application of medical big data[C]//2018 international conference on robots & intelligent system.Piscataway:IEEE, 2018:383-386.
[32] KAMBLE S S, GUNASEKARAN A, GOSWAMI M, et al.A systematic perspective on the applications of big data analytics in healthcare management[J].International journal of healthcare management, 2019, 12(3):226-240.
[33] 齐云飞, 李齐栋, 赵宇翔, 等.突发公共卫生事件中风险意识对公众健康保护意愿的影响研究[J].图书情报工作, 2020, 64(15):165-176.
[34] MANOGARAN G, VARATHARAJAN R, LOPEZ D, et al.A new architecture of Internet of things and big data ecosystem for secured smart healthcare monitoring and alerting system[J].Future generation computer systems, 2018, 82:375-387.
[35] 李彩宁, 毕新华, 王雅薇.个人健康信息管理技术促进用户健康行为的心理机制:基于智能可穿戴健康产品的实证研究[J].图书情报工作, 2021, 65(19):72-83.
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