Literature DB >> 30242819

Should Electronic Health Record-Derived Social and Behavioral Data Be Used in Precision Medicine Research?

Brittany Hollister1, Vence L Bonham2.   

Abstract

Precision medicine research initiatives aim to use participants' electronic health records (EHRs) to obtain rich longitudinal data for large-scale precision medicine studies. Although EHRs vary widely in their inclusion and formatting of social and behavioral data, these data are essential to investigating genetic and social factors in health disparities. We explore possible biases in collecting, using, and interpreting EHR-based social and behavioral data in precision medicine research and their consequences for health equity.
© 2018 American Medical Association. All Rights Reserved.

Entities:  

Year:  2018        PMID： 30242819     DOI： 10.1001/amajethics.2018.873

Source DB:  PubMed          Journal:  AMA J Ethics


  9 in total

1.  Psychosocial phenotyping as a personalization strategy for chronic disease self-management interventions.

Authors:  Miyong T Kim; Kavita Radhakrishnan; Elizabeth M Heitkemper; Eunju Choi; Marissa Burgermaster
Journal:  Am J Transl Res       Date:  2021-03-15       Impact factor: 4.060

2.  Artificial Intelligence and Precision Medicine: A Perspective.

Authors:  Jacek Lorkowski; Oliwia Kolaszyńska; Mieczysław Pokorski
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

3.  Advocacy and actions to address disparities in access to genomic health care: A report on a National Academies workshop.

Authors:  Janet K Williams; Vence L Bonham; Catherine Wicklund; Bernice Coleman; Jacquelyn Y Taylor; Ann K Cashion
Journal:  Nurs Outlook       Date:  2019-06-18       Impact factor: 3.315

Review 4.  Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature.

Authors:  Casey Overby Taylor; Peter Tarczy-Hornoch
Journal:  Yearb Med Inform       Date:  2019-08-16

5.  The anatomy of electronic patient record ethics: a framework to guide design, development, implementation, and use.

Authors:  Tim Jacquemard; Colin P Doherty; Mary B Fitzsimons
Journal:  BMC Med Ethics       Date:  2021-02-04       Impact factor: 2.652

6.  Antihypertensive effects of yoga in a general patient population: real-world evidence from electronic health records, a retrospective case-control study.

Authors:  Nadia M Penrod; Jason H Moore
Journal:  BMC Public Health       Date:  2022-01-27       Impact factor: 3.295

Review 7.  Expectations for Artificial Intelligence (AI) in Psychiatry.

Authors:  Scott Monteith; Tasha Glenn; John Geddes; Peter C Whybrow; Eric Achtyes; Michael Bauer
Journal:  Curr Psychiatry Rep       Date:  2022-10-10       Impact factor: 8.081

8.  Examination and diagnosis of electronic patient records and their associated ethics: a scoping literature review.

Authors:  Tim Jacquemard; Colin P Doherty; Mary B Fitzsimons
Journal:  BMC Med Ethics       Date:  2020-08-24       Impact factor: 2.652

9.  Linking Electronic Health Records and In-Depth Interviews to Inform Efforts to Integrate Social Determinants of Health Into Health Care Delivery: Protocol for a Qualitative Research Study.

Authors:  Annemarie Hirsch; T Elizabeth Durden; Jennifer Silva
Journal:  JMIR Res Protoc       Date:  2022-03-11
  9 in total

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