Literature DB >> 18755988

Advancing the framework: use of health data--a report of a working conference of the American Medical Informatics Association.

Meryl Bloomrosen1, Don Detmer.   

Abstract

The fields of health informatics and biomedical research increasingly depend on the availability of aggregated health data. Yet, despite over fifteen years of policy work on health data issues, the United States (U.S.) lacks coherent policy to guide users striving to navigate the ethical, political, technical, and economic challenges associated with health data use. In 2007, building on more than a decade of previous work, the American Medical Informatics Association (AMIA) convened a panel of experts to stimulate discussion about and action on a national framework for health data use. This initiative is being carried out in the context of rapidly accelerating advances in the fields of health informatics and biomedical research, many of which are dependent on the availability of aggregated health data. Use of these data poses complex challenges that must be addressed by public policy. This paper highlights the results of the meeting, presents data stewardship as a key building block in the national framework, and outlines stewardship principles for the management of health information. The authors also introduce a taxonomy developed to focus definitions and terminology in the evolving field of health data applications. Finally, they identify areas for further policy analysis and recommend that public and private sector organizations elevate consideration of a national framework on the uses of health data to a top priority.

Mesh:

Year:  2008        PMID: 18755988      PMCID: PMC2585531          DOI: 10.1197/jamia.M2905

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  4 in total

1.  Toward a national framework for the secondary use of health data: an American Medical Informatics Association White Paper.

Authors:  Charles Safran; Meryl Bloomrosen; W Edward Hammond; Steven Labkoff; Suzanne Markel-Fox; Paul C Tang; Don E Detmer
Journal:  J Am Med Inform Assoc       Date:  2006-10-31       Impact factor: 4.497

2.  State-of-the-art anonymization of medical records using an iterative machine learning framework.

Authors:  György Szarvas; Richárd Farkas; Róbert Busa-Fekete
Journal:  J Am Med Inform Assoc       Date:  2007 Sep-Oct       Impact factor: 4.497

3.  Rapidly retargetable approaches to de-identification in medical records.

Authors:  Ben Wellner; Matt Huyck; Scott Mardis; John Aberdeen; Alex Morgan; Leonid Peshkin; Alex Yeh; Janet Hitzeman; Lynette Hirschman
Journal:  J Am Med Inform Assoc       Date:  2007-06-28       Impact factor: 4.497

4.  Evaluating the state-of-the-art in automatic de-identification.

Authors:  Ozlem Uzuner; Yuan Luo; Peter Szolovits
Journal:  J Am Med Inform Assoc       Date:  2007-06-28       Impact factor: 4.497

  4 in total
  21 in total

1.  The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.

Authors:  Caitlin M Cusack; George Hripcsak; Meryl Bloomrosen; S Trent Rosenbloom; Charlotte A Weaver; Adam Wright; David K Vawdrey; Jim Walker; Lena Mamykina
Journal:  J Am Med Inform Assoc       Date:  2012-09-08       Impact factor: 4.497

Review 2.  Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature.

Authors:  John H Holmes; Thomas E Elliott; Jeffrey S Brown; Marsha A Raebel; Arthur Davidson; Andrew F Nelson; Annie Chung; Pierre La Chance; John F Steiner
Journal:  J Am Med Inform Assoc       Date:  2014-03-28       Impact factor: 4.497

3.  Facilitating Clinical Research through the Health Information Exchange: Lipid Control as an Example.

Authors:  Vivienne J Zhu; Wanzhu Tu; Marc B Rosenman; J Marc Overhage
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

Review 4.  Update on Data Reuse in Health Care.

Authors:  C Safran
Journal:  Yearb Med Inform       Date:  2017-09-11

5.  Reducing patient re-identification risk for laboratory results within research datasets.

Authors:  Ravi V Atreya; Joshua C Smith; Allison B McCoy; Bradley Malin; Randolph A Miller
Journal:  J Am Med Inform Assoc       Date:  2012-07-21       Impact factor: 4.497

6.  Visual cluster analysis in support of clinical decision intelligence.

Authors:  David Gotz; Jimeng Sun; Nan Cao; Shahram Ebadollahi
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

7.  A framework for understanding cancer comparative effectiveness research data needs.

Authors:  William R Carpenter; Anne-Marie Meyer; Amy P Abernethy; Til Stürmer; Michael R Kosorok
Journal:  J Clin Epidemiol       Date:  2012-11       Impact factor: 6.437

Review 8.  Data for cancer comparative effectiveness research: past, present, and future potential.

Authors:  Anne-Marie Meyer; William R Carpenter; Amy P Abernethy; Til Stürmer; Michael R Kosorok
Journal:  Cancer       Date:  2012-04-19       Impact factor: 6.860

9.  Sick patients have more data: the non-random completeness of electronic health records.

Authors:  Nicole G Weiskopf; Alex Rusanov; Chunhua Weng
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

10.  Health data use, stewardship, and governance: ongoing gaps and challenges: a report from AMIA's 2012 Health Policy Meeting.

Authors:  George Hripcsak; Meryl Bloomrosen; Patti FlatelyBrennan; Christopher G Chute; Jim Cimino; Don E Detmer; Margo Edmunds; Peter J Embi; Melissa M Goldstein; William Ed Hammond; Gail M Keenan; Steve Labkoff; Shawn Murphy; Charlie Safran; Stuart Speedie; Howard Strasberg; Freda Temple; Adam B Wilcox
Journal:  J Am Med Inform Assoc       Date:  2013-10-29       Impact factor: 4.497

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