Literature DB >> 27520614

Big Data in Health: a Literature Review from the Year 2005.

Isabel de la Torre Díez1, Héctor Merino Cosgaya2, Begoña Garcia-Zapirain3, Miguel López-Coronado2.   

Abstract

The information stored in healthcare systems has increased over the last ten years, leading it to be considered Big Data. There is a wealth of health information ready to be analysed. However, the sheer volume raises a challenge for traditional methods. The aim of this article is to conduct a cutting-edge study on Big Data in healthcare from 2005 to the present. This literature review will help researchers to know how Big Data has developed in the health industry and open up new avenues for research. Information searches have been made on various scientific databases such as Pubmed, Science Direct, Scopus and Web of Science for Big Data in healthcare. The search criteria were "Big Data" and "health" with a date range from 2005 to the present. A total of 9724 articles were found on the databases. 9515 articles were discarded as duplicates or for not having a title of interest to the study. 209 articles were read, with the resulting decision that 46 were useful for this study. 52.6 % of the articles used were found in Science Direct, 23.7 % in Pubmed, 22.1 % through Scopus and the remaining 2.6 % through the Web of Science. Big Data has undergone extremely high growth since 2011 and its use is becoming compulsory in developed nations and in an increasing number of developing nations. Big Data is a step forward and a cost reducer for public and private healthcare.

Keywords:  Big data; Databases; Health; Review

Mesh:

Year:  2016        PMID: 27520614     DOI: 10.1007/s10916-016-0565-7

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  24 in total

1.  [Big data in health in Spain: now is the time for a national strategy].

Authors:  Carlos Luis Parra Calderón
Journal:  Gac Sanit       Date:  2015-11-21       Impact factor: 2.139

2.  The role of cost in telemedicine evaluation.

Authors:  Fuhmei Wang
Journal:  Telemed J E Health       Date:  2009-12       Impact factor: 3.536

3.  ["Big data"; application and use for the health system].

Authors:  José Manuel Martínez Sesmero
Journal:  Farm Hosp       Date:  2015-03-01

4.  Design and development of a medical big data processing system based on Hadoop.

Authors:  Qin Yao; Yu Tian; Peng-Fei Li; Li-Li Tian; Yang-Ming Qian; Jing-Song Li
Journal:  J Med Syst       Date:  2015-02-10       Impact factor: 4.460

Review 5.  Big data for health.

Authors:  Javier Andreu-Perez; Carmen C Y Poon; Robert D Merrifield; Stephen T C Wong; Guang-Zhong Yang
Journal:  IEEE J Biomed Health Inform       Date:  2015-07-10       Impact factor: 5.772

6.  Accessibility and vulnerabilty: ensuring security of data in telemedicine.

Authors:  Charles R Doarn; Ronald C Merrell
Journal:  Telemed J E Health       Date:  2015-03       Impact factor: 3.536

7.  Large-scale electrophysiology: acquisition, compression, encryption, and storage of big data.

Authors:  Benjamin H Brinkmann; Mark R Bower; Keith A Stengel; Gregory A Worrell; Matt Stead
Journal:  J Neurosci Methods       Date:  2009-04-01       Impact factor: 2.390

Review 8.  Managing, analysing, and integrating big data in medical bioinformatics: open problems and future perspectives.

Authors:  Ivan Merelli; Horacio Pérez-Sánchez; Sandra Gesing; Daniele D'Agostino
Journal:  Biomed Res Int       Date:  2014-09-01       Impact factor: 3.411

9.  The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

Authors:  Ronald Margolis; Leslie Derr; Michelle Dunn; Michael Huerta; Jennie Larkin; Jerry Sheehan; Mark Guyer; Eric D Green
Journal:  J Am Med Inform Assoc       Date:  2014-07-09       Impact factor: 4.497

Review 10.  Big data in global health: improving health in low- and middle-income countries.

Authors:  Rosemary Wyber; Samuel Vaillancourt; William Perry; Priya Mannava; Temitope Folaranmi; Leo Anthony Celi
Journal:  Bull World Health Organ       Date:  2015-01-30       Impact factor: 9.408

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  9 in total

1.  Big data and pain.

Authors:  Jeong Gill Leem
Journal:  Korean J Pain       Date:  2016-09-29

2.  Opportunities of mHealth in Preconception Care: Preferences and Experiences of Patients and Health Care Providers and Other Involved Professionals.

Authors:  Ageeth N Rosman; Regine Pm Steegers-Theunissen; Matthijs R Van Dijk; Maria Ph Koster
Journal:  JMIR Mhealth Uhealth       Date:  2017-08-17       Impact factor: 4.773

3.  Clinical epidemiology in the era of big data: new opportunities, familiar challenges.

Authors:  Vera Ehrenstein; Henrik Nielsen; Alma B Pedersen; Søren P Johnsen; Lars Pedersen
Journal:  Clin Epidemiol       Date:  2017-04-27       Impact factor: 4.790

4.  Analysis of an Internet Community about Pneumothorax and the Importance of Accurate Information about the Disease.

Authors:  Bong Jun Kim; Sungsoo Lee
Journal:  Korean J Thorac Cardiovasc Surg       Date:  2018-04-05

5.  The identification of cases of major hemorrhage during hospitalization in patients with acute leukemia using routinely recorded healthcare data.

Authors:  Aukje L Kreuger; Rutger A Middelburg; Erik A M Beckers; Karen M K de Vooght; Jaap Jan Zwaginga; Jean-Louis H Kerkhoffs; Johanna G van der Bom
Journal:  PLoS One       Date:  2018-08-15       Impact factor: 3.240

6.  Automatic Classification of Sarcopenia Level in Older Adults: A Case Study at Tijuana General Hospital.

Authors:  Cristián Castillo-Olea; Begonya García-Zapirain Soto; Christian Carballo Lozano; Clemente Zuñiga
Journal:  Int J Environ Res Public Health       Date:  2019-09-06       Impact factor: 3.390

7.  Lyme disease: the promise of Big Data, companion diagnostics and precision medicine.

Authors:  Raphael B Stricker; Lorraine Johnson
Journal:  Infect Drug Resist       Date:  2016-09-13       Impact factor: 4.003

8.  How Big Data, Comparative Effectiveness Research, and Rapid-Learning Health-Care Systems Can Transform Patient Care in Radiation Oncology.

Authors:  Jason C Sanders; Timothy N Showalter
Journal:  Front Oncol       Date:  2018-05-09       Impact factor: 6.244

9.  Evaluation of Prevalence of the Sarcopenia Level Using Machine Learning Techniques: Case Study in Tijuana Baja California, Mexico.

Authors:  Cristián Castillo-Olea; Begonya Garcia-Zapirain Soto; Clemente Zuñiga
Journal:  Int J Environ Res Public Health       Date:  2020-03-15       Impact factor: 3.390

  9 in total

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