Journal-based CME Course: Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm

Activity ID

10760

Expires

August 20, 2027

Format Type

Journal-based

CME Credit

Fee

$30

CME 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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NOTE: 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.

General Information on CME Activity

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