Activity ID
10760Expires
August 31, 2024Format Type
Journal-basedCME Credit
1Fee
$30CME Provider: AMA Journal of Ethics
Description of CME Course
A significant proportion of elderly and psychiatric patients do not have the capacity to make health care decisions. We suggest that machine learning technologies could be harnessed to integrate data mined from electronic health records (EHRs) and social media in order to estimate the confidence of the prediction that a patient would consent to a given treatment. We call this process, which takes data about patients as input and derives a confidence estimate for a particular patient’s predicted health care-related decision as an output, the autonomy algorithm. We suggest that the proposed algorithm would result in more accurate predictions than existing methods, which are resource intensive and consider only small patient cohorts. This algorithm could become a valuable tool in medical decision-making processes, augmenting the capacity of all people to make health care decisions in difficult situations.
Disclaimers
1. This activity is accredited by the American Medical Association.
2. This activity is free to AMA members.
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ABMS Lifelong Learning CME Activity
Allergy and Immunology
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Commercial Support?
NoNOTE: If a Member Board has not deemed this activity for MOC approval as an accredited CME activity, this activity may count toward an ABMS Member Board’s general CME requirement. Please refer directly to your Member Board’s MOC Part II Lifelong Learning and Self-Assessment Program Requirements.
Educational Objectives
At the end of this activity, you will be able to:
1. Explain a new or unfamiliar viewpoint on a topic of ethical or professional conduct;
2. Evaluate the usefulness of this information for health care practice, teaching, or conduct;
3. Decide whether and when to apply the new information to health care practice, teaching, or conduct.
Keywords
Ethics, Health Informatics, Electronic Health Records
Competencies
Medical Knowledge, Professionalism
CME Credit Type
AMA PRA Category 1 Credit
DOI
10.1001/amajethics.2018.910
