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The Proxy Predicament: Making Medical Decisions for Others is Hard

Leave your comment: 2 comments so far

Most of us will lose our ability to make medical decisions for ourselves as we get closer to the last phase of life. At this point, our proxy decision makers will have to make decisions for is. It is impossible for us to truly know what another person may want for themselves in terms of medical decisions. Most proxy decision makers are usually stressed to the maximum in trying to weigh the pros and cons and make decisions for the patient. This process is so much easier if every adult takes 10 minutes to complete the Letter Project form and answer a few simple questions that will clarify what they truly want for themselves. In fact, this will prevent us from burdening our family members with the stressful process of guessing what we may want and what our values and preferences for care are.

Here is what you need to do:

1. Go online to http://med.stanford.edu/letter.html and use the online form (available in many languages) to clarify what matters most to you

(or)

2. Go to the Apple Appstore (https://itunes.apple.com/us/app/stanf…) or Google Playstore (https://play.google.com/store/apps/de…) and download the free Stanford Letter Project App.

Invest ten minutes time in writing your letter. Do not stress your loved ones later; write your letter now so everyone knows what you want. It is free, easy and extremely important.

To read more please check out recent article Pitfalls for Proxies published by the New York Times.

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    Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding"

    Julia Adler-Milstein, PhD1; Jonathan H. Chen, MD, PhD; Gurpreet Dhaliwal, MD

    Improving the diagnostic process is a quality and safety priority.With the digitization of health records and rapid expansion of health data, the cognitive demand on the diagnostician has increased. The use of artificial intelligence (AI) to assist human cognition has the potential to reduce this demand and associated diagnostic errors. However, current AI tools have not realized this potential, due in part to the long-standing focus of these tools on predicting final diagnostic labels instead of helping clinicians navigate the dynamic refinement process of diagnosis. This Viewpoint highlights the importance of shifting the role of diagnostic AI from predicting labels to “wayfinding” (interpreting context and providing cues that guide the diagnostician).