Literature DB >> 27738817

Big Data: Will It Improve Patient-Centered Care?

Denzil G Fiebig1.   

Abstract

Within a generation, empirical researchers have experienced unprecedented increases in the availability of data. 'Big data' has arrived with considerable hype and a sense that these are dramatic shifts in the research environment that have wide-reaching implications across many disciplines. There is no doubt that the analysis of new and varied sources of data currently available to researchers in health have the potential to better measure, monitor and describe health outcomes of patients and to uncover interesting patterns in how patients respond to treatments and interact with the health system. What is less clear is whether answers are readily available to more nuanced and substantive research questions. Here, the data-rich environment needs to be complemented by considerable research effort developing novel research designs and generating new and improved methods of analysis. Importantly, this will require researchers to be able to combine data from multiple sources and to be pro-active in data collection.

Entities:  

Mesh:

Year:  2017        PMID: 27738817     DOI: 10.1007/s40271-016-0201-0

Source DB:  PubMed          Journal:  Patient        ISSN: 1178-1653            Impact factor:   3.883


  19 in total

1.  The case of the Indians and the teen-age widows.

Authors:  A J Coale; F F Stephan
Journal:  J Am Stat Assoc       Date:  1962-06       Impact factor: 5.033

2.  Preferences for new and existing contraceptive products.

Authors:  Denzil G Fiebig; Stephanie Knox; Rosalie Viney; Marion Haas; Deborah J Street
Journal:  Health Econ       Date:  2010-11-24       Impact factor: 3.046

3.  "Big data" versus "big brother": on the appropriate use of large-scale data collections in pediatrics.

Authors:  Janet Currie
Journal:  Pediatrics       Date:  2013-04       Impact factor: 7.124

4.  Causal inference in economics and marketing.

Authors:  Hal R Varian
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-05       Impact factor: 11.205

5.  Patient preferences for managing asthma: results from a discrete choice experiment.

Authors:  Madeleine T King; Jane Hall; Emily Lancsar; Denzil Fiebig; Ishrat Hossain; Jordan Louviere; Helen K Reddel; Christine R Jenkins
Journal:  Health Econ       Date:  2007-07       Impact factor: 3.046

6.  Prediction Policy Problems.

Authors:  Jon Kleinberg; Jens Ludwig; Sendhil Mullainathan; Ziad Obermeyer
Journal:  Am Econ Rev       Date:  2015-05

7.  The "medicine in Australia: balancing employment and life (MABEL)" longitudinal survey--protocol and baseline data for a prospective cohort study of Australian doctors' workforce participation.

Authors:  Catherine M Joyce; Anthony Scott; Sung-Hee Jeon; John Humphreys; Guyonne Kalb; Julia Witt; Anne Leahy
Journal:  BMC Health Serv Res       Date:  2010-02-25       Impact factor: 2.655

8.  Randomised trials for the Fitbit generation.

Authors:  Walter Dempsey; Peng Liao; Pedja Klasnja; Inbal Nahum-Shani; Susan A Murphy
Journal:  Signif (Oxf)       Date:  2015-12-01

9.  Combining individual-level discrete choice experiment estimates and costs to inform health care management decisions about customized care: the case of follow-up strategies after breast cancer treatment.

Authors:  Tim M Benning; Merel L Kimman; Carmen D Dirksen; Liesbeth J Boersma; Benedict G C Dellaert
Journal:  Value Health       Date:  2012-06-22       Impact factor: 5.725

10.  The Oregon experiment--effects of Medicaid on clinical outcomes.

Authors:  Katherine Baicker; Sarah L Taubman; Heidi L Allen; Mira Bernstein; Jonathan H Gruber; Joseph P Newhouse; Eric C Schneider; Bill J Wright; Alan M Zaslavsky; Amy N Finkelstein
Journal:  N Engl J Med       Date:  2013-05-02       Impact factor: 91.245

View more
  1 in total

1.  Changing Health-Related Behaviors 6: Analysis, Interpretation, and Application of Big Data.

Authors:  Randy Giffen; Donald Bryant
Journal:  Methods Mol Biol       Date:  2021
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.