Integrated Care and Connected Health Approaches Leveraging Personalised Health through Big Data Analytics

被引:7
|
作者
Maglaveras, Nicos [1 ,2 ]
Kilintzis, Vassilis [1 ,2 ]
Koutkias, Vassilis [2 ]
Chouvarda, Ioanna [1 ,2 ]
机构
[1] Aristotle Univ Thessaloniki, Sch Med, Lab Comp & Med Informat, Dept Med, Thessaloniki, Greece
[2] Ctr Res & Technol Hellas, Inst Appl Biosci, Thessaloniki, Greece
来源
PHEALTH 2016 | 2016年 / 224卷
关键词
Telemonitoring; eHealth; integrated care; connected health; chronic care; disease management; patient empowerment; biosensors; clinical decision support; Big Bio-data management and analytics;
D O I
10.3233/978-1-61499-653-8-117
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Integrated care and connected health are two fast evolving concepts that have the potential to leverage personalised health. From the one side, the restructuring of care models and implementation of new systems and integrated care programs providing coaching and advanced intervention possibilities, enable medical decision support and personalized healthcare services. From the other side, the connected health ecosystem builds the means to follow and support citizens via personal health systems in their everyday activities and, thus, give rise to an unprecedented wealth of data. These approaches are leading to the deluge of complex data, as well as in new types of interactions with and among users of the healthcare ecosystem. The main challenges refer to the data layer, the information layer, and the output of information processing and analytics. In all the above mentioned layers, the primary concern is the quality both in data and information, thus, increasing the need for filtering mechanisms. Especially in the data layer, the big biodata management and analytics ecosystem is evolving, telemonitoring is a step forward for data quality leverage, with numerous challenges still left to address, partly due to the large number of micro-nano sensors and technologies available today, as well as the heterogeneity in the users' background and data sources. This leads to new R&D pathways as it concerns biomedical information processing and management, as well as to the design of new intelligent decision support systems (DSS) and interventions for patients. In this paper, we illustrate these issues through exemplar research targeting chronic patients, illustrating the current status and trends in PHS within the integrated care and connected care world.
引用
收藏
页码:117 / 122
页数:6
相关论文
共 50 条
  • [31] Review of Data Extraction, Segregation & Privacy with Big Data Analytics in the Online Health Care Systems
    Purandhar, N.
    Kumar, N. M. Saravana
    [J]. PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT SUSTAINABLE SYSTEMS (ICISS 2019), 2019, : 193 - 197
  • [32] Big Data Analytics Framework for System Health Monitoring
    Xu, Brian
    Kumar, Sathish Alampalayam
    [J]. 2015 IEEE INTERNATIONAL CONGRESS ON BIG DATA - BIGDATA CONGRESS 2015, 2015, : 401 - 408
  • [33] Big Data Analytics in Biomedicine and Health: Trends and Challenges
    Peek, Niels
    Holmes, John H.
    Martin-Sanchez, Fernando
    Sun, Jimeng
    [J]. MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 : 1237 - 1237
  • [34] IMPLICATIONS OF BIG DATA ANALYTICS ON POPULATION HEALTH MANAGEMENT
    Bradley, Paul S.
    [J]. BIG DATA, 2013, 1 (03) : 152 - 159
  • [35] Editorial: Big Data Analytics for Precision Health and Prevention
    Capobianco, Enrico
    Deng, Jun
    [J]. FRONTIERS IN BIG DATA, 2022, 4
  • [36] Enhancing Digital Health Services with Big Data Analytics
    Berros, Nisrine
    El Mendili, Fatna
    Filaly, Youness
    El Idrissi, Younes El Bouzekri
    [J]. BIG DATA AND COGNITIVE COMPUTING, 2023, 7 (02)
  • [37] CrowdHEALTH: Big Data Analytics and Holistic Health Records
    Gallos, Parisis
    Aso, Santiago
    Autexier, Serge
    Brotons, Arturo
    De Nigro, Antonio
    Jurak, Gregor
    Kiourtis, Athanasios
    Kranas, Pavlos
    Kyriazis, Dimosthenis
    Lustrek, Mitja
    Magdalinou, Andrianna
    Maglogiannis, Ilias
    Mantas, John
    Martinez, Antonio
    Menychtas, Andreas
    Montandon, Lydia
    Picioroaga, Florin
    Perez, Manuel
    Stanimirovic, Dalibor
    Starc, Gregor
    Tomson, Tanja
    Vilar-Mateo, Ruth
    Vizitiu, Ana-Maria
    [J]. ICT FOR HEALTH SCIENCE RESEARCH, 2019, 258 : 255 - 256
  • [38] Transformation of the Doctor–Patient Relationship: Big Data, Accountable Care, and Predictive Health Analytics
    Seuli Bose Brill
    Karen O. Moss
    Laura Prater
    [J]. HEC Forum, 2019, 31 : 261 - 282
  • [39] Leveraging "big data" to enhance the effectiveness of "one health" in an era of health informatics
    Asokan G.V.
    Asokan V.
    [J]. Journal of Epidemiology and Global Health, 2015, 5 (4) : 311 - 314
  • [40] National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors
    Schatz, Bruce R.
    [J]. BIG DATA, 2015, 3 (04) : 219 - 229