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Published in: BMC Emergency Medicine 1/2013

Open Access 01-12-2013 | Research article

The accuracy of surrogate decision makers: informed consent in hypothetical acute stroke scenarios

Authors: Jessica Bryant, Lesli E Skolarus, Barbara Smith, Eric E Adelman, William J Meurer

Published in: BMC Emergency Medicine | Issue 1/2013

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Abstract

Background

Over one third of stroke patients have cognitive or language deficits such that they require surrogate consent for acute stroke treatment or enrollment into acute stroke trials. Little is known about the agreement of stroke patients and surrogates in this time-sensitive decision-making process. We sought to determine patient and surrogate agreement in 4 hypothetical acute stroke scenarios.

Methods

We performed face to face interviews with ED patients at an academic teaching hospital from June to August 2011. Patients and the surrogates they designated were asked to make decisions regarding 4 hypothetical stroke scenarios: 2 were treatment decisions; 2 involved enrollment into a clinical trial. Percent agreement was calculated as measures of surrogate predictive ability.

Results

A total of 200 patient/surrogate pairs were interviewed. Overall patient/surrogate percent agreement was 76.5%. Agreement for clinical scenarios ranged from 87% to 96% but dropped to 49%-74% for research scenarios.

Conclusions

Surrogates accurately predict patient preferences for standard acute stroke treatments. However, the accuracy decreases when predicting research participation suggesting that the degree of surrogate agreement is dependent on the type of decision being made. Further research is needed to more thoroughly characterize surrogate decision-making in acute stroke situations.
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Metadata
Title
The accuracy of surrogate decision makers: informed consent in hypothetical acute stroke scenarios
Authors
Jessica Bryant
Lesli E Skolarus
Barbara Smith
Eric E Adelman
William J Meurer
Publication date
01-12-2013
Publisher
BioMed Central
Published in
BMC Emergency Medicine / Issue 1/2013
Electronic ISSN: 1471-227X
DOI
https://doi.org/10.1186/1471-227X-13-18

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