Literature DB >> 35033797

The passivists: Managing risk through institutionalized ignorance in genomic medicine.

Kellie Owens1.   

Abstract

As the era of big data transforms modern medicine, clinicians have access to more health data than ever. How do medical providers determine which data are relevant to patient care, which are irrelevant, and which may be inappropriately used to justify potentially harmful interventions? One of the most prominent medical fields to address these questions head on - clinical genomics - is actively debating how to assess the value of genomic data. In-depth interviews with clinicians and a content analysis of policy documents demonstrate that while many clinicians believe that collecting as much patient data as possible will lead to better patient care, a sizeable minority of clinicians preferred to collect less data. These clinicians worried that large genomic tests provided too much data, leading to confusion and inappropriate treatment. Clinical geneticists have also started developing the concept of "actionability" to assess which types of genomic data are worth collecting and interpreting. By classifying data as useful when it can or should lead to action, clinicians can formalize and institutionalize what types of data should be ignored. But achieving consensus about what counts as "actionable" has proven difficult and highlights the different values and risk philosophies of clinicians. At the same time, many clinicians are fighting against the ignorance arising from genomic databases predominantly filled with samples from European ancestry populations. Debates about how and when to institutionalize ignorance of health data are not unique to clinical genomics, but have spread throughout many fields of medicine. As the amount of health data available to clinicians and patients grows, social science research on the politics of knowledge and ignorance should inform debates about the value of data in medicine.
Copyright © 2022 The Author. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Biomedicine; Clinical genomics; Data; Ignorance; Knowledge; Risk

Mesh:

Year:  2022        PMID: 35033797      PMCID: PMC8821417          DOI: 10.1016/j.socscimed.2022.114715

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  24 in total

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Authors:  P Franks; C M Clancy; P A Nutting
Journal:  N Engl J Med       Date:  1992-08-06       Impact factor: 91.245

2.  The Actionability of Exome sequencing testing results.

Authors:  Tanya Stivers; Stefan Timmermans
Journal:  Sociol Health Illn       Date:  2017-11

3.  Lack Of Diversity In Genomic Databases Is A Barrier To Translating Precision Medicine Research Into Practice.

Authors:  Latrice G Landry; Nadya Ali; David R Williams; Heidi L Rehm; Vence L Bonham
Journal:  Health Aff (Millwood)       Date:  2018-05       Impact factor: 6.301

4.  Invisibilizing politics: Accepting and legitimating ignorance in environmental sciences.

Authors:  June Jeon
Journal:  Soc Stud Sci       Date:  2019-09-09       Impact factor: 3.885

5.  Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement.

Authors: 
Journal:  Ann Intern Med       Date:  2009-11-17       Impact factor: 25.391

Review 6.  The converged experience of risk and disease.

Authors:  Robert A Aronowitz
Journal:  Milbank Q       Date:  2009-06       Impact factor: 4.911

7.  Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics.

Authors:  Sarah S Kalia; Kathy Adelman; Sherri J Bale; Wendy K Chung; Christine Eng; James P Evans; Gail E Herman; Sophia B Hufnagel; Teri E Klein; Bruce R Korf; Kent D McKelvey; Kelly E Ormond; C Sue Richards; Christopher N Vlangos; Michael Watson; Christa L Martin; David T Miller
Journal:  Genet Med       Date:  2016-11-17       Impact factor: 8.822

8.  A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genome-scale sequencing.

Authors:  Jonathan S Berg; Ann Katherine M Foreman; Julianne M O'Daniel; Jessica K Booker; Lacey Boshe; Timothy Carey; Kristy R Crooks; Brian C Jensen; Eric T Juengst; Kristy Lee; Daniel K Nelson; Bradford C Powell; Cynthia M Powell; Myra I Roche; Cecile Skrzynia; Natasha T Strande; Karen E Weck; Kirk C Wilhelmsen; James P Evans
Journal:  Genet Med       Date:  2015-08-13       Impact factor: 8.822

9.  ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing.

Authors:  Robert C Green; Jonathan S Berg; Wayne W Grody; Sarah S Kalia; Bruce R Korf; Christa L Martin; Amy L McGuire; Robert L Nussbaum; Julianne M O'Daniel; Kelly E Ormond; Heidi L Rehm; Michael S Watson; Marc S Williams; Leslie G Biesecker
Journal:  Genet Med       Date:  2013-06-20       Impact factor: 8.822

10.  Opportunistic genomic screening. Recommendations of the European Society of Human Genetics.

Authors:  Guido de Wert; Wybo Dondorp; Angus Clarke; Elisabeth M C Dequeker; Christophe Cordier; Zandra Deans; Carla G van El; Florence Fellmann; Ros Hastings; Sabine Hentze; Heidi Howard; Milan Macek; Alvaro Mendes; Chris Patch; Emmanuelle Rial-Sebbag; Vigdis Stefansdottir; Martina C Cornel; Francesca Forzano
Journal:  Eur J Hum Genet       Date:  2020-11-22       Impact factor: 4.246

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