Clin Exp Emerg Med.  2019 Mar;6(1):70-76. 10.15441/ceem.17.293.

Prognostic value of a modified surprise question designed for use in the emergency department setting

• Haydar SA
• Strout TD
• Bond AG
• Han PK

• KMID: 2447311
• DOI: http://doi.org/10.15441/ceem.17.293

Abstract

OBJECTIVE
Few reliable and valid prognostic tools are available to help emergency physicians identify patients who might benefit from early palliative approaches. We sought to determine if responses to a modified version of the surprise question, "Would you be surprised if this patient died in the next 30 days" could predict in-hospital mortality and resource utilization for hospitalized emergency department patients.
METHODS
For this observational study, emergency physicians responded to the modified surprise question with each admission over a five-month study period. Logistic regression analyses were completed and standard test characteristics evaluated.
RESULTS
6,122 visits were evaluated. Emergency physicians responded negatively to the modified surprise question in 918 (15.1%). Test characteristics for in-hospital mortality were: sensitivity 32%, specificity 85%, positive predictive value 6%, negative predictive value 98%. The risk of intensive care unit use (relative risk [RR], 1.87; 95% confidence interval [CI], 1.45 to 2.40), use of "˜comfort measures' orders (RR, 3.43; 95% CI, 2.81 to 4.18), palliative-care consultation (RR, 3.06; 95% CI, 2.62 to 3.56), and in-hospital mortality (RR, 2.18; 95% CI, 1.72 to 2.76) were greater for patients with negative responses.
CONCLUSION
The modified surprise question is a simple trigger for palliative care needs, accurately identifying those at greater risk for in-hospital mortality and resource utilization. With a negative predictive value of 98%, affirmative responses to the modified surprise question provide reassurance that in-hospital death is unlikely.

Keyword

Palliative medicine; Terminal care; Emergency service, hospital; Surprise question

MeSH Terms

Emergencies*
Emergency Service, Hospital*
Hospital Mortality
Humans
Intensive Care Units
Logistic Models
Observational Study
Palliative Care
Palliative Medicine
Sensitivity and Specificity
Terminal Care