2018
DOI: 10.1001/amajethics.2018.857
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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… Show more

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Cited by 11 publications
(4 citation statements)
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References 7 publications
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“…Learning health systems with their intentionally blurred boundaries between research and care - particularly in the case of EHR decision support - require a new approach of oversight to be adopted. Measures towards securing enough insight into the certainty and reliability of algorithms and offering additional recommendations, e.g ., from guidelines, together with monitoring data quality and preserving confidentiality need particular oversight to be implemented via establishing an independent body of experts with the capability to enforce the rules 47 . The AMIA working group Ethical, Legal, and Social Issues 48 worked on patient access to EHRs in a learning health system rather from the opportunity than from the risk position.…”
Section: Resultsmentioning
confidence: 99%
“…Learning health systems with their intentionally blurred boundaries between research and care - particularly in the case of EHR decision support - require a new approach of oversight to be adopted. Measures towards securing enough insight into the certainty and reliability of algorithms and offering additional recommendations, e.g ., from guidelines, together with monitoring data quality and preserving confidentiality need particular oversight to be implemented via establishing an independent body of experts with the capability to enforce the rules 47 . The AMIA working group Ethical, Legal, and Social Issues 48 worked on patient access to EHRs in a learning health system rather from the opportunity than from the risk position.…”
Section: Resultsmentioning
confidence: 99%
“…Exemplary, there are systems for risk evaluation, pre-processing or pre-sorting of telemetric and visual data, differentiation of patients into subgroups or integration into diagnostic procedures. Overall, the application of artificial intelligence in medicine is beneficial but requires ethical oversight in implementation and usage ( 36 ).…”
Section: Discussionmentioning
confidence: 99%
“…Professionals raised concerns about reliability of the output generated by the system and the adaptability of the system to local and contextual needs (CFIR: Characteristics of Individuals). Previous research confirmed that frequently found errors in data processing and output of clinical decision support tools negatively affect users' perception as unsuitable suggestions for decision-making lead to doubts about safety and accuracy [25][26][27]. Resistance was also expressed regarding the potential lack of clinical nuances for psychosocial factors in the well-structured patient overview provided by the first component (CFIR: Characteristics of Individuals).…”
Section: Relation To Other Studiesmentioning
confidence: 99%