Literature DB >> 24158174

Comparison of the Mortality Probability Admission Model III, National Quality Forum, and Acute Physiology and Chronic Health Evaluation IV hospital mortality models: implications for national benchmarking*.

Andrew A Kramer1, Thomas L Higgins, Jack E Zimmerman.   

Abstract

OBJECTIVE: To examine the accuracy of the original Mortality Probability Admission Model III, ICU Outcomes Model/National Quality Forum modification of Mortality Probability Admission Model III, and Acute Physiology and Chronic Health Evaluation IVa models for comparing observed and risk-adjusted hospital mortality predictions.
DESIGN: Retrospective paired analyses of day 1 hospital mortality predictions using three prognostic models.
SETTING: Fifty-five ICUs at 38 U.S. hospitals from January 2008 to December 2012. PATIENTS: Among 174,001 intensive care admissions, 109,926 met model inclusion criteria and 55,304 had data for mortality prediction using all three models.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: We compared patient exclusions and the discrimination, calibration, and accuracy for each model. Acute Physiology and Chronic Health Evaluation IVa excluded 10.7% of all patients, ICU Outcomes Model/National Quality Forum 20.1%, and Mortality Probability Admission Model III 24.1%. Discrimination of Acute Physiology and Chronic Health Evaluation IVa was superior with area under receiver operating curve (0.88) compared with Mortality Probability Admission Model III (0.81) and ICU Outcomes Model/National Quality Forum (0.80). Acute Physiology and Chronic Health Evaluation IVa was better calibrated (lowest Hosmer-Lemeshow statistic). The accuracy of Acute Physiology and Chronic Health Evaluation IVa was superior (adjusted Brier score = 31.0%) to that for Mortality Probability Admission Model III (16.1%) and ICU Outcomes Model/National Quality Forum (17.8%). Compared with observed mortality, Acute Physiology and Chronic Health Evaluation IVa overpredicted mortality by 1.5% and Mortality Probability Admission Model III by 3.1%; ICU Outcomes Model/National Quality Forum underpredicted mortality by 1.2%. Calibration curves showed that Acute Physiology and Chronic Health Evaluation performed well over the entire risk range, unlike the Mortality Probability Admission Model and ICU Outcomes Model/National Quality Forum models. Acute Physiology and Chronic Health Evaluation IVa had better accuracy within patient subgroups and for specific admission diagnoses.
CONCLUSIONS: Acute Physiology and Chronic Health Evaluation IVa offered the best discrimination and calibration on a large common dataset and excluded fewer patients than Mortality Probability Admission Model III or ICU Outcomes Model/National Quality Forum. The choice of ICU performance benchmarks should be based on a comparison of model accuracy using data for identical patients.

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Year:  2014        PMID: 24158174     DOI: 10.1097/CCM.0b013e3182a66a49

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  9 in total

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2.  The Effect of Intensive Care Unit Admission Patterns on Mortality-based Critical Care Performance Measures.

Authors:  Ian J Barbash; Tri Q Le; Francis Pike; Amber E Barnato; Derek C Angus; Jeremy M Kahn
Journal:  Ann Am Thorac Soc       Date:  2016-06

3.  The Global Open Source Severity of Illness Score (GOSSIS).

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4.  Retrospective Descriptive Study of an Intensive Care Unit at a Ugandan Regional Referral Hospital.

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Journal:  World J Surg       Date:  2016-12       Impact factor: 3.352

5.  Simultaneous Prediction of New Morbidity, Mortality, and Survival Without New Morbidity From Pediatric Intensive Care: A New Paradigm for Outcomes Assessment.

Authors:  Murray M Pollack; Richard Holubkov; Tomohiko Funai; John T Berger; Amy E Clark; Kathleen Meert; Robert A Berg; Joseph Carcillo; David L Wessel; Frank Moler; Heidi Dalton; Christopher J L Newth; Thomas Shanley; Rick E Harrison; Allan Doctor; Tammara L Jenkins; Robert Tamburro; J Michael Dean
Journal:  Crit Care Med       Date:  2015-08       Impact factor: 7.598

6.  Performance of three prognostic models in patients with cancer in need of intensive care in a medical center in China.

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7.  Developing well-calibrated illness severity scores for decision support in the critically ill.

Authors:  Christopher V Cosgriff; Leo Anthony Celi; Stephanie Ko; Tejas Sundaresan; Miguel Ángel Armengol de la Hoz; Aaron Russell Kaufman; David J Stone; Omar Badawi; Rodrigo Octavio Deliberato
Journal:  NPJ Digit Med       Date:  2019-08-15

8.  The Ability of the Acute Physiology and Chronic Health Evaluation (APACHE) IV Score to Predict Mortality in a Single Tertiary Hospital.

Authors:  Jae Woo Choi; Young Sun Park; Young Seok Lee; Yeon Hee Park; Chaeuk Chung; Dong Il Park; In Sun Kwon; Ju Sang Lee; Na Eun Min; Jeong Eun Park; Sang Hoon Yoo; Gyu Rak Chon; Young Hoon Sul; Jae Young Moon
Journal:  Korean J Crit Care Med       Date:  2017-08-31

9.  Inter-Rater Reliability and Impact of Disagreements on Acute Physiology and Chronic Health Evaluation IV Mortality Predictions.

Authors:  Michelle Simkins; Ayesha Iqbal; Audrey Gronemeyer; Lisa Konzen; Jason White; Michael Koenig; Chris Palmer; Paul Kerby; Sara Buckman; Vladimir Despotovic; Christine Hoehner; Walter Boyle
Journal:  Crit Care Explor       Date:  2019-10-30
  9 in total

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