TY - CHAP
T1 - Outcome Prediction and Shared Decision-Making in Neurocritical Care
AU - Sharrock, Matthew F.
AU - Stevens, Robert D.
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - The neurointensive care physician is frequently called upon to lead in the determination of neurological prognosis and in the decision-making that follows. This is a complex task that must integrate objective clinical information and test results together with published evidence and professional guidelines or recommendations when available. A number of scoring systems have been developed on the basis of multivariable models that typically integrate clinical severity indicators as well as features extracted from neuroimaging and neurophysiological testing and, in some cases, serum biomarkers. Performance of these models, evaluated with indices of discrimination and calibration, is often insufficient to enable prediction at the individual patient level—perhaps due to underpowered samples, lack of external validation, and failure to consider treatments as predictive features. The aim of effectively delivering prognostic information may fail because of the lack of consistency and coordination in communication between treatment teams and families and the unqualified use of population-based evidence to formulate point estimates of individual outcome. To help overcome this barrier, a model of “shared decision-making” has been proposed in which providers, patients, and surrogate decision-makers work collaboratively to make medical decisions that consider the best scientific evidence while integrating the patient’s values, goals, and preferences.
AB - The neurointensive care physician is frequently called upon to lead in the determination of neurological prognosis and in the decision-making that follows. This is a complex task that must integrate objective clinical information and test results together with published evidence and professional guidelines or recommendations when available. A number of scoring systems have been developed on the basis of multivariable models that typically integrate clinical severity indicators as well as features extracted from neuroimaging and neurophysiological testing and, in some cases, serum biomarkers. Performance of these models, evaluated with indices of discrimination and calibration, is often insufficient to enable prediction at the individual patient level—perhaps due to underpowered samples, lack of external validation, and failure to consider treatments as predictive features. The aim of effectively delivering prognostic information may fail because of the lack of consistency and coordination in communication between treatment teams and families and the unqualified use of population-based evidence to formulate point estimates of individual outcome. To help overcome this barrier, a model of “shared decision-making” has been proposed in which providers, patients, and surrogate decision-makers work collaboratively to make medical decisions that consider the best scientific evidence while integrating the patient’s values, goals, and preferences.
KW - Outcome prediction
KW - Prognostication
KW - Shared decision-making
KW - Stroke
KW - Traumatic brain injury
UR - http://www.scopus.com/inward/record.url?scp=85084641948&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084641948&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-36548-6_21
DO - 10.1007/978-3-030-36548-6_21
M3 - Chapter
AN - SCOPUS:85084641948
T3 - Current Clinical Neurology
SP - 293
EP - 300
BT - Current Clinical Neurology
PB - Humana Press Inc.
ER -