Literature DB >> 30242817

What Should Oversight of Clinical Decision Support Systems Look Like?

Emily L Evans1, Danielle Whicher2.   

Abstract

A learning health system provides opportunities to leverage data generated in the course of standard clinical care to improve clinical practice. One such opportunity includes a clinical decision support structure that would allow clinicians to query electronic health records (EHRs) such that responses from the EHRs could inform treatment recommendations. We argue that though using a clinical decision support system does not necessarily constitute a research activity subject to the Common Rule, it requires more ethical and regulatory oversight than activities of clinical practice are generally subjected to. In particular, we argue that the development and use of clinical decision support systems should be governed by a framework that (1) articulates appropriate conditions for their use, (2) includes processes for monitoring data quality and developing and validating algorithms, and (3) sufficiently protects patients' data.
© 2018 American Medical Association. All Rights Reserved.

Entities:  

Year:  2018        PMID: 30242817     DOI: 10.1001/amajethics.2018.857

Source DB:  PubMed          Journal:  AMA J Ethics


  8 in total

Review 1.  Decision fusion in healthcare and medicine: a narrative review.

Authors:  Elham Nazari; Rizwana Biviji; Danial Roshandel; Reza Pour; Mohammad Hasan Shahriari; Amin Mehrabian; Hamed Tabesh
Journal:  Mhealth       Date:  2022-01-20

2.  Association of Disparities in Family History and Family Cancer History in the Electronic Health Record With Sex, Race, Hispanic or Latino Ethnicity, and Language Preference in 2 Large US Health Care Systems.

Authors:  Daniel Chavez-Yenter; Melody S Goodman; Yuyu Chen; Xiangying Chu; Richard L Bradshaw; Rachelle Lorenz Chambers; Priscilla A Chan; Brianne M Daly; Michael Flynn; Amanda Gammon; Rachel Hess; Cecelia Kessler; Wendy K Kohlmann; Devin M Mann; Rachel Monahan; Sara Peel; Kensaku Kawamoto; Guilherme Del Fiol; Meenakshi Sigireddi; Saundra S Buys; Ophira Ginsburg; Kimberly A Kaphingst
Journal:  JAMA Netw Open       Date:  2022-10-03

3.  How Should Clinicians' Performance Be Assessed When Health Care Organizations Implement Behavioral Architecture That Generates Negative Consequences?

Authors:  Safiya Richardson
Journal:  AMA J Ethics       Date:  2020-09-01

4.  Machine Learning Classification of Inflammatory Bowel Disease in Children Based on a Large Real-World Pediatric Cohort CEDATA-GPGE® Registry.

Authors:  Nicolas Schneider; Keywan Sohrabi; Henning Schneider; Klaus-Peter Zimmer; Patrick Fischer; Jan de Laffolie
Journal:  Front Med (Lausanne)       Date:  2021-05-24

Review 5.  Clinical Information Systems - Seen through the Ethics Lens.

Authors:  Ursula H Hübner; Nicole Egbert; Georg Schulte
Journal:  Yearb Med Inform       Date:  2020-08-21

6.  Barriers and Facilitators for Implementation of a Computerized Clinical Decision Support System in Lung Cancer Multidisciplinary Team Meetings-A Qualitative Assessment.

Authors:  Sosse E Klarenbeek; Olga C J Schuurbiers-Siebers; Michel M van den Heuvel; Mathias Prokop; Marcia Tummers
Journal:  Biology (Basel)       Date:  2020-12-25

Review 7.  Stakeholder bias in best practice advisories: an ethical perspective.

Authors:  Aaron Baird; Bryan Kibbe; Jason Lesandrini
Journal:  JAMIA Open       Date:  2020-06-28

8.  Teasing out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine.

Authors:  Mark Henderson Arnold
Journal:  J Bioeth Inq       Date:  2021-01-07       Impact factor: 2.216

  8 in total

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