Current applications of big data in obstetric anesthesiology

被引:4
|
作者
Klumpner, Thomas T. [1 ]
Bauer, Melissa E. [1 ]
Kheterpal, Sachin [1 ]
机构
[1] Univ Michigan, Dept Anesthesiol, Ann Arbor, MI 48109 USA
关键词
clinical decision support systems; obstetrical anesthesia; review; trends; NEW-YORK-STATE; WARNING SYSTEM MEOWS; ADVERSE EVENTS; SERIOUS COMPLICATIONS; NEURAXIAL ANESTHESIA; CESAREAN DELIVERIES; EPIDURAL ANALGESIA; ETHNIC DISPARITIES; PLATELET COUNTS; TEMPORAL-TRENDS;
D O I
10.1097/ACO.0000000000000452
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Purpose of review The narrative review aims to highlight several recently published 'big data' studies pertinent to the field of obstetric anesthesiology. Recent findings Big data has been used to study rare outcomes, to identify trends within the healthcare system, to identify variations in practice patterns, and to highlight potential inequalities in obstetric anesthesia care. Big data studies have helped define the risk of rare complications of obstetric anesthesia, such as the risk of neuraxial hematoma in thrombocytopenic parturients. Also, large national databases have been used to better understand trends in anesthesia-related adverse events during cesarean delivery as well as outline potential racial/ethnic disparities in obstetric anesthesia care. Finally, real-time analysis of patient data across a number of disparate health information systems through the use of sophisticated clinical decision support and surveillance systems is one promising application of big data technology on the labor and delivery unit. Summary 'Big data' research has important implications for obstetric anesthesia care and warrants continued study. Real-time electronic surveillance is a potentially useful application of big data technology on the labor and delivery unit.
引用
下载
收藏
页码:300 / 305
页数:6
相关论文
共 50 条
  • [41] Big Data and diabetes: the applications of Big Data for diabetes care now and in the future
    Rumbold, J. M. M.
    O'Kane, M.
    Philip, N.
    Pierscionek, B. K.
    DIABETIC MEDICINE, 2020, 37 (02) : 187 - 193
  • [42] Big Data Meet Green Challenges: Big Data Toward Green Applications
    Wu, Jinsong
    Guo, Song
    Li, Jie
    Zeng, Deze
    IEEE SYSTEMS JOURNAL, 2016, 10 (03): : 888 - 900
  • [43] What's new in obstetric anesthesiology? SOAP 1996
    Birnbach, DJ
    INTERNATIONAL JOURNAL OF OBSTETRIC ANESTHESIA, 1997, 6 (01) : 32 - 38
  • [44] Introducing focused reviews in obstetric anesthesiology: A new series
    Wong, Cynthia A.
    ANESTHESIA AND ANALGESIA, 2008, 107 (03): : 746 - 747
  • [45] Applications of Big Data in Tourism: A Survey
    Becha, Malika
    Riabi, Oumayma
    Benmessaoud, Yasmine
    Masri, Hela
    ADVANCED DATA MINING AND APPLICATIONS, 2020, 12447 : 533 - 546
  • [46] A Survey of Tools and Applications in Big Data
    Menon, Sindhu P.
    Hegde, Nagaratna P.
    PROCEEDINGS OF 2015 IEEE 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO), 2015,
  • [47] Applications of Big Data in Media Organizations
    Veglis, Andreas
    Saridou, Theodora
    Panagiotidis, Kosmas
    Karypidou, Christina
    Kotenidis, Efthimis
    SOCIAL SCIENCES-BASEL, 2022, 11 (09):
  • [48] Big Data Applications Performance Assurance
    Zibitsker, Boris
    ICPE'16 COMPANION: PROCEEDINGS OF THE 2016 COMPANION PUBLICATION FOR THE ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING, 2016, : 31 - 31
  • [49] BIG DATA AND ITS APPLICATIONS: A REVIEW
    Rout, Trilochan
    Senapati, Manas Ranjan
    Garanayak, Mamata
    Kamilla, Sushanta Kumar
    2015 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, SIGNALS, COMMUNICATION AND OPTIMIZATION (EESCO), 2015,
  • [50] Big Data: Concepts, Challenges and Applications
    Chebbi, Imen
    Boulila, Wadii
    Farah, Imed Riadh
    COMPUTATIONAL COLLECTIVE INTELLIGENCE (ICCCI 2015), PT II, 2015, 9330 : 638 - 647