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Surrogate Decision Makers' Interpretation of Prognostic Information FREE

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The summary below is from the full report titled “Surrogate Decision Makers' Interpretation of Prognostic Information. A Mixed-Methods Study.” It is in the 6 March 2012 issue of Annals of Internal Medicine (volume 156, pages 360-366). The authors are L.S. Zier, P.D. Sottile, S.Y. Hong, L.A. Weissfield, and D.B. White.

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Summaries for Patients are presented for informational purposes only. These summaries are not a substitute for advice from your own medical provider. If you have questions about this material, or need medical advice about your own health or situation, please contact your physician. The summaries may be reproduced for not-for-profit educational purposes only. Any other uses must be approved by the American College of Physicians.

Ann Intern Med. 2012;156(5):I-26. doi:10.7326/0003-4819-156-5-201203060-00002
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What is the problem and what is known about it so far?

Individuals who make decisions for patients with advanced critical illness are frequently asked to determine whether life support is consistent with a patient's values and goals. To answer this question, these “surrogate decision makers” need a clear understanding of the patient's values as well as the likely outcomes of treatment (the “prognosis”). But even after a doctor explains the prognosis of a patient to a surrogate decision maker, they often differ in their views. In particular, surrogates may have overly optimistic expectations about the prognosis. Little is known about why this occurs—it is possible that they misunderstand or misinterpret the doctors' prognosis or that optimism or denial leads them to overestimate the likelihood of a positive outcome.

Why did the researchers do this particular study?

To learn about how surrogates interpret prognostic statements and to explore factors influencing their interpretations of prognostic information.

Who was studied?

Eighty individuals (“surrogates”) involved in decision making for incapacitated, critically ill patients in the intensive care unit of 1 of 3 hospitals in San Francisco.

How was the study done?

Between June 2006 and January 2009, the researchers administered a questionnaire to surrogates, who interpreted 16 prognostic statements that were hypothetical and unrelated to their loved one's prognosis. For example, one prognostic statement read, “If a doctor says ‘He will definitely survive’, what does that mean to you?” Participants answered by placing a mark on a probability scale corresponding the patient's chances of survival, from “Will NOT survive (0% chance of survival)” to “Will survive (100% chance of survival).”

After the surrogates completed the questionnaire, a researcher screened the responses. The researcher invited surrogates whose interpretation of the prognostic statements differed from the actual meaning to be interviewed. During the interview, the researcher asked questions in an effort to learn the possible reasons for the difference.

What did the researchers find?

Surrogates were able to accurately interpret statements expressing a high probability of a good outcome (such as “90% chance of surviving”) but not those expressing a high risk for death (such as “5% chance of surviving” or “50% chance of surviving”). Interpretations of statements conveying a high risk for death were more optimistic than the actual meaning. On the basis of the interviews, the researchers identified themes explaining the surrogates' interpretations of prognostic statements. These included the need to register optimism and the view that grim prognostic estimates should not necessarily be taken at face value.

What were the limitations of the study?

The surrogates' interpretations were obtained in an experimental setting rather than in actual clinician–surrogate conversations.

What are the implications of the study?

Inaccurate interpretations of doctors' prognostications arise partly from optimistic biases rather than simply from misunderstandings. Helping surrogates attain realistic expectations about patients' likely outcomes is more complex than just giving clear information.





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