Grounded in Science

Quant HC is dedicated to leveraging the data and predictive analytics in the hospital setting to advance healthcare and improve patient outcomes

Development and validation of eCART

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Multicenter development and validation of a risk stratification tool for ward patients.

Am J Respir Crit Care Med. 2014;190:649-55.

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Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards.

Crit Care Med. 2014;42:841-8.

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Derivation of a cardiac arrest prediction model using ward vital signs.

Crit Care Med. 2012;40:2102-8.

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Risk and stratification on the ward

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Differences in vital signs between elderly and nonelderly patients prior to ward cardiac arrest.

Crit Care Med. 2015;43:816-22.

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A prospective study of nighttime vital sign monitoring frequency and risk of clinical deterioration.

JAMA Intern Med. 2013;173:1554-5.

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Predicting clinical deterioration in the hospital: the impact of outcome selection.

Resuscitation. 2013;84:564-8.

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Risk stratification of hospitalized patients on the wards.

Chest. 2013;143:1758-65.

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Predicting cardiac arrest on the wards: a nested case-control study.

Chest. 2012;141:1170-6.

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