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ACUITY 2016 Predictive Modeling NOW AVAILABLE!


The ACUITY 2016 severity scoring system offers the most contemporary set of predictive equations available and is more accurate than APACHE IV,  providing a a better snapshot of an ICU’s adjusted mortality, LOS, and duration of mechanical ventilation. For more, Click here.


‘Revalidation of ACUITY 2016’ | Download paper

This paper includes results indicating the continuing accuracy of ACUITY 2016 equations and how it remains the most contemporary set of predictive equations.


The Revealing Signs of Outdated ICU Predictive Models | Watch

Dr. Andrew Kramer of Prescient Healthcare Consulting  ( explains why the Case Mix Index

(CMI) and APACHE IV are substandard models for evaluating today's ICUs along with introducing his latest and greatest predictive models, ACUITY 2016.

ACUITY 2018 Predictive Modeling COMING SOON!


The best gets better with the new ACUITY 2018 predictive modeling system.

ACUITY 2018 provides fully automated severity adjusted outcome measures with no manual data collection ever

and uses more current data than APACHE Models - improving accuracy - with observed and predicted values nearly identical!

MDN PHOENIX Critical Care Software


MDN PHOENIX is comprehensive, easy to use, provides clear insights into the performance of your Critical Care Units and includes our unique ACUITY 2016 Severity Scoring System. For more,  Click here.


What is a Standardized Mortality Ratio (SMR)?  | Watch

Dr. Andrew Kramer of Prescient Healthcare Consulting ( speaks at the SCCM Conference

in Orlando, Florida on his new model, ACUITY 2016,  and the value of severity adjusted modeling and standardized  mortality ratios (SMR) in evaluating ICUs.

GlucoStabilizer® Insulin Dosing System


FDA cleared GlucoStabilizer is integrated inpatient software for IV insulin management with the mission of improving glycemic control. 

Simple to use, it aids in reducing the frequency, risk, and cost of hyperglycemia, hypoglycemia and glycemic varibility


To visit the GlucoStabilizer website, Click here.

Variations in Case-Mix–Adjusted Duration of Mechanical Ventilation Among ICUs*
Kramer, Andrew A. PhD; Gershengorn, Hayley B. MD; Wunsch, Hannah MD, MSc; Zimmerman, Jack E. MD, FCCM, Critical Care Medicine, June 2016


The author's objectives were to develop a model that predicts the duration of mechanical ventilation and then to use this model to
compare observed versus expected duration of mechanical ventilation across ICUs. The setting included eighty-six eligible ICUs at 48 U.S. hospitals,

with ICU patients receiving mechanical ventilation on day 1 (n = 56,336) admitted from January 2013 to September 2014.

Measurements and Main Results: We developed and validated a multivariable logistic regression model for predicting duration of mechanical ventilation using ICU

day 1 patient characteristics. Mean observed minus expected duration of mechanical ventilation was then obtained across patients and for each ICU. The accuracy of the model was assessed using R2. We defined better performing units as ICUs that had an observed minus expected duration of mechanical ventilation less than –0.5 days and a p value of less than 0.01; and poorer performing units as ICUs with an observed  minus expected duration of mechanical ventilation greater than +0.5 days and a p value of less than 0.01.  For the rest of the study, click here to receive a copy.

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