Literature DB >> 25006136

Creating value in health care through big data: opportunities and policy implications.

Joachim Roski1, George W Bo-Linn2, Timothy A Andrews3.   

Abstract

Big data has the potential to create significant value in health care by improving outcomes while lowering costs. Big data's defining features include the ability to handle massive data volume and variety at high velocity. New, flexible, and easily expandable information technology (IT) infrastructure, including so-called data lakes and cloud data storage and management solutions, make big-data analytics possible. However, most health IT systems still rely on data warehouse structures. Without the right IT infrastructure, analytic tools, visualization approaches, work flows, and interfaces, the insights provided by big data are likely to be limited. Big data's success in creating value in the health care sector may require changes in current polices to balance the potential societal benefits of big-data approaches and the protection of patients' confidentiality. Other policy implications of using big data are that many current practices and policies related to data use, access, sharing, privacy, and stewardship need to be revised. Project HOPE—The People-to-People Health Foundation, Inc.

Entities:  

Keywords:  Cost of Health Care; Information Technology; Quality Of Care; Research And Technology

Mesh:

Year:  2014        PMID: 25006136     DOI: 10.1377/hlthaff.2014.0147

Source DB:  PubMed          Journal:  Health Aff (Millwood)        ISSN: 0278-2715            Impact factor:   6.301


  56 in total

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2.  Role of Health Services Research in Producing High-Value Rehabilitation Care.

Authors:  Sean D Rundell; Adam P Goode; Janna L Friedly; Jeffrey G Jarvik; Sean D Sullivan; Brian W Bresnahan
Journal:  Phys Ther       Date:  2015-08-27

3.  Pharmacy Practice, Education, and Research in the Era of Big Data: 2014-15 Argus Commission Report.

Authors:  Jeffrey N Baldwin; J Lyle Bootman; Rodney A Carter; Brian L Crabtree; Peggy Piascik; Jeffrey O Ekoma; Lucinda L Maine
Journal:  Am J Pharm Educ       Date:  2015-12-25       Impact factor: 2.047

4.  Commentary: Epidemiology in the era of big data.

Authors:  Stephen J Mooney; Daniel J Westreich; Abdulrahman M El-Sayed
Journal:  Epidemiology       Date:  2015-05       Impact factor: 4.822

5.  Perioperative and ICU Healthcare Analytics within a Veterans Integrated System Network: a Qualitative Gap Analysis.

Authors:  Seshadri Mudumbai; Ferenc Ayer; Jerry Stefanko
Journal:  J Med Syst       Date:  2017-07-06       Impact factor: 4.460

6.  Ethics and Epistemology in Big Data Research.

Authors:  Wendy Lipworth; Paul H Mason; Ian Kerridge; John P A Ioannidis
Journal:  J Bioeth Inq       Date:  2017-03-20       Impact factor: 1.352

7.  Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services.

Authors:  Suranga N Kasthurirathne; Joshua R Vest; Nir Menachemi; Paul K Halverson; Shaun J Grannis
Journal:  J Am Med Inform Assoc       Date:  2018-01-01       Impact factor: 4.497

Review 8.  Big data analytics to improve cardiovascular care: promise and challenges.

Authors:  John S Rumsfeld; Karen E Joynt; Thomas M Maddox
Journal:  Nat Rev Cardiol       Date:  2016-03-24       Impact factor: 32.419

9.  PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Authors:  Khader Shameer; Kipp W Johnson; Alexandre Yahi; Riccardo Miotto; L I Li; Doran Ricks; Jebakumar Jebakaran; Patricia Kovatch; Partho P Sengupta; Sengupta Gelijns; Alan Moskovitz; Bruce Darrow; David L David; Andrew Kasarskis; Nicholas P Tatonetti; Sean Pinney; Joel T Dudley
Journal:  Pac Symp Biocomput       Date:  2017

Review 10.  Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.

Authors:  Jenna Wiens; Erica S Shenoy
Journal:  Clin Infect Dis       Date:  2018-01-06       Impact factor: 9.079

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