Peer-reviewed article by Camillo Lamanna and Lauren Byrne.
Published in AMA Journal of Ethics — Case and Commentary. The case to which this commentary is a response was developed by the editorial staff.
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.
This journal-based CME activity is designated for one AMA PRA Category 1 Credit™.