Literature DB >> 25123740

Big Data: Are Biomedical and Health Informatics Training Programs Ready? Contribution of the IMIA Working Group for Health and Medical Informatics Education.

P Otero1, W Hersh, A U Jai Ganesh.   

Abstract

OBJECTIVE: The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know?
METHODS: We hypothesize a set of skills that we hope will be discussed among academic and other informaticians.
RESULTS: The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one's area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them.
CONCLUSION: Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in "deep analytical talent" as well as those who need knowledge to support such individuals.

Entities:  

Keywords:  Data interpretation; databases as topic; education; individualized medicine; medical informatics; patient participation; statistical

Mesh:

Year:  2014        PMID: 25123740      PMCID: PMC4287071          DOI: 10.15265/IY-2014-0007

Source DB:  PubMed          Journal:  Yearb Med Inform        ISSN: 0943-4747


  16 in total

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Authors:  Christine K Cassel; James A Guest
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4.  Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics. First Revision.

Authors:  John Mantas; Elske Ammenwerth; George Demiris; Arie Hasman; Reinhold Haux; William Hersh; Evelyn Hovenga; K C Lun; Heimar Marin; Fernando Martin-Sanchez; Graham Wright
Journal:  Methods Inf Med       Date:  2010-01-07       Impact factor: 2.176

5.  Data scientist: the sexiest job of the 21st century.

Authors:  Thomas H Davenport; D J Patil
Journal:  Harv Bus Rev       Date:  2012-10

6.  Implementing the learning health system: from concept to action.

Authors:  Sarah M Greene; Robert J Reid; Eric B Larson
Journal:  Ann Intern Med       Date:  2012-08-07       Impact factor: 25.391

7.  The inevitable application of big data to health care.

Authors:  Travis B Murdoch; Allan S Detsky
Journal:  JAMA       Date:  2013-04-03       Impact factor: 56.272

8.  Caveats for the use of operational electronic health record data in comparative effectiveness research.

Authors:  William R Hersh; Mark G Weiner; Peter J Embi; Judith R Logan; Philip R O Payne; Elmer V Bernstam; Harold P Lehmann; George Hripcsak; Timothy H Hartzog; James J Cimino; Joel H Saltz
Journal:  Med Care       Date:  2013-08       Impact factor: 2.983

9.  Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial.

Authors:  Jacques E Rossouw; Garnet L Anderson; Ross L Prentice; Andrea Z LaCroix; Charles Kooperberg; Marcia L Stefanick; Rebecca D Jackson; Shirley A A Beresford; Barbara V Howard; Karen C Johnson; Jane Morley Kotchen; Judith Ockene
Journal:  JAMA       Date:  2002-07-17       Impact factor: 56.272

10.  A stimulus to define informatics and health information technology.

Authors:  William Hersh
Journal:  BMC Med Inform Decis Mak       Date:  2009-05-15       Impact factor: 2.796

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  6 in total

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2.  Preparing family medicine trainees for the information revolution: Pearls, potential, promise, and pitfalls.

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Review 3.  Big Data in Health: a Literature Review from the Year 2005.

Authors:  Isabel de la Torre Díez; Héctor Merino Cosgaya; Begoña Garcia-Zapirain; Miguel López-Coronado
Journal:  J Med Syst       Date:  2016-08-13       Impact factor: 4.460

Review 4.  Big Data in Public Health: Terminology, Machine Learning, and Privacy.

Authors:  Stephen J Mooney; Vikas Pejaver
Journal:  Annu Rev Public Health       Date:  2017-12-20       Impact factor: 21.981

5.  Innovation of health data science curricula.

Authors:  Miriam Isola; Jacob Krive
Journal:  JAMIA Open       Date:  2022-08-27

6.  Teaching Hands-On Informatics Skills to Future Health Informaticians: A Competency Framework Proposal and Analysis of Health Care Informatics Curricula.

Authors:  A Hasan Sapci; H Aylin Sapci
Journal:  JMIR Med Inform       Date:  2020-01-21
  6 in total

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