Andrew A Kramer

Summary

Affiliation: Cerner Corporation
Country: USA

Publications

  1. pmc Predictive mortality models are not like fine wine
    Andrew A Kramer
    Cerner Corporation, 1953 Gallows Road, Suite 570, Vienna, VA 22182, USA
    Crit Care 9:636-7. 2005
  2. ncbi request reprint Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients
    Jack E Zimmerman
    George Washington University, Washington, DC, USA
    Crit Care Med 34:1297-310. 2006
  3. doi request reprint The association between ICU readmission rate and patient outcomes
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 41:24-33. 2013
  4. doi request reprint Intensive care unit readmissions in U.S. hospitals: patient characteristics, risk factors, and outcomes
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 40:3-10. 2012
  5. doi request reprint The relationship between hospital and intensive care unit length of stay
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 39:1015-22. 2011
  6. doi request reprint Institutional variations in frequency of discharge of elderly intensive care survivors to postacute care facilities
    Andrew A Kramer
    Cerner Corporation, Washington, DC, USA
    Crit Care Med 38:2319-28. 2010
  7. pmc A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay
    Andrew A Kramer
    Cerner Corporation, Suite 500, Vienna, Virginia 22182, USA
    BMC Med Inform Decis Mak 10:27. 2010
  8. doi request reprint Predicting outcomes for cardiac surgery patients after intensive care unit admission
    Andrew A Kramer
    Cerner Corporation, Vienna, Virginia 22182, USA
    Semin Cardiothorac Vasc Anesth 12:175-83. 2008
  9. ncbi request reprint Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 35:2052-6. 2007
  10. ncbi request reprint Intensive care unit length of stay: Benchmarking based on Acute Physiology and Chronic Health Evaluation (APACHE) IV
    Jack E Zimmerman
    George Washington University, Washington, DC, USA
    Crit Care Med 34:2517-29. 2006

Collaborators

Detail Information

Publications18

  1. pmc Predictive mortality models are not like fine wine
    Andrew A Kramer
    Cerner Corporation, 1953 Gallows Road, Suite 570, Vienna, VA 22182, USA
    Crit Care 9:636-7. 2005
    ..Thus, the updated SAPS II model may be interesting for historical purposes, but it is doubtful that it can be an accurate tool for benchmarking data from contemporary populations...
  2. ncbi request reprint Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients
    Jack E Zimmerman
    George Washington University, Washington, DC, USA
    Crit Care Med 34:1297-310. 2006
    ..To improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) method for predicting hospital mortality among critically ill adults and to evaluate changes in the accuracy of earlier APACHE models...
  3. doi request reprint The association between ICU readmission rate and patient outcomes
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 41:24-33. 2013
    ..To examine the association between ICU readmission rates and case-mix-adjusted outcomes...
  4. doi request reprint Intensive care unit readmissions in U.S. hospitals: patient characteristics, risk factors, and outcomes
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 40:3-10. 2012
    ..To examine which patient characteristics increase the risk for intensive care unit readmission and assess the association of readmission with case-mix adjusted mortality and resource use...
  5. doi request reprint The relationship between hospital and intensive care unit length of stay
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 39:1015-22. 2011
    ..To assess variations in case-mix-adjusted hospital and intensive care unit length of stay and to examine the relationship between intensive care unit and hospital stay...
  6. doi request reprint Institutional variations in frequency of discharge of elderly intensive care survivors to postacute care facilities
    Andrew A Kramer
    Cerner Corporation, Washington, DC, USA
    Crit Care Med 38:2319-28. 2010
    ....
  7. pmc A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay
    Andrew A Kramer
    Cerner Corporation, Suite 500, Vienna, Virginia 22182, USA
    BMC Med Inform Decis Mak 10:27. 2010
    ..Early identification of patients at risk for a prolonged length of stay can lead to quality enhancements that reduce ICU stay. This study developed and validated a model that identifies patients at risk for a prolonged ICU stay...
  8. doi request reprint Predicting outcomes for cardiac surgery patients after intensive care unit admission
    Andrew A Kramer
    Cerner Corporation, Vienna, Virginia 22182, USA
    Semin Cardiothorac Vasc Anesth 12:175-83. 2008
    ..Thus, the equations are not designed for predicting individual patients' outcome but have proven useful in performance comparisons and for quality improvement initiatives...
  9. ncbi request reprint Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 35:2052-6. 2007
    ..To examine the Hosmer-Lemeshow test's sensitivity in evaluating the calibration of models predicting hospital mortality in large critical care populations...
  10. ncbi request reprint Intensive care unit length of stay: Benchmarking based on Acute Physiology and Chronic Health Evaluation (APACHE) IV
    Jack E Zimmerman
    George Washington University, Washington, DC, USA
    Crit Care Med 34:2517-29. 2006
    ..To revise and update the Acute Physiology and Chronic Health Evaluation (APACHE) model for predicting intensive care unit (ICU) length of stay...
  11. doi request reprint A multicenter prospective study of interobserver agreement using the Full Outline of Unresponsiveness score coma scale in the intensive care unit
    Andrew A Kramer
    Cerner Corporation, Vienna, VA, USA
    Crit Care Med 40:2671-6. 2012
    ..This manuscript reports on a study that examined the inter-rater reliability of the Full Outline of Unresponsiveness score in five intensive care units...
  12. doi request reprint Outcome prediction in critical care: the Acute Physiology and Chronic Health Evaluation models
    Jack E Zimmerman
    Anesthesia and Critical Care Medicine, The George Washington University, Washington, District of Columbia, USA
    Curr Opin Crit Care 14:491-7. 2008
    ..We also compare APACHE IV with other systems and address the issue of model complexity...
  13. doi request reprint A model for identifying patients who may not need intensive care unit admission
    Jack E Zimmerman
    The Department of Anesthesia and Critical Care Medicine, George Washington University, Washington, DC, USA
    J Crit Care 25:205-13. 2010
    ..This study presents a new model for identifying patients who might be too well to benefit from intensive care unit (ICU) care...
  14. doi request reprint 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 Kramer
    1Cerner Corporation, Vienna, VA 2Department of Biostatistics, Kansas University Medical Center, Kansas City, MO 3Critical Care Division, Baystate Medical Center, Springfield, MA 4Department of Medicine, Tufts University School of Medicine, Boston, MA 5Department of Anesthesiology and Critical Care Medicine, George Washington University, Washington, DC
    Crit Care Med 42:544-53. 2014
    ....
  15. ncbi request reprint Transferring critically ill patients out of hospital improves the standardized mortality ratio: a simulation study
    Jeremy M Kahn
    Division of Pulmonary and Critical Care, Harborview Medical Center, University of Washington, Seattle WA, USA
    Chest 131:68-75. 2007
    ..We sought to quantify the effect of out-of-hospital transfers on the standardized mortality ratio (SMR), an outcome-based measure of ICU performance...
  16. ncbi request reprint Assessing contemporary intensive care unit outcome: an updated Mortality Probability Admission Model (MPM0-III)
    Thomas L Higgins
    Critical Care Division, Baystate Medical Center, Springfield, MA, USA
    Crit Care Med 35:827-35. 2007
    ..To update the Mortality Probability Model at intensive care unit (ICU) admission (MPM0-II) using contemporary data...
  17. doi request reprint Validating predictive models of mortality: more than meets the eye
    Andrew A Kramer
    Crit Care Med 36:1357-8. 2008
  18. ncbi request reprint Hospital volume and the outcomes of mechanical ventilation
    Jeremy M Kahn
    Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle 98104, USA
    N Engl J Med 355:41-50. 2006
    ..The relationship between the number of patients admitted (hospital volume) and outcome among patients with critical illnesses is unknown...