Predictive and prognostic models: implications for healthcare decision-making in a modern recession.

Various modeling tools have been developed to address the lack of standardized processes that incorporate the perspectives of all healthcare stakeholders. Such models can assist in the decision-making process aimed at achieving specific clinical outcomes, as well as guide the allocation of healthcare resources and reduce costs. The current efforts in Congress to change the way healthcare is financed, reimbursed, and delivered have rendered the incorporation of modeling tools into the clinical decision-making all the more important. Prognostic and predictive models are particularly relevant to healthcare, particularly in the clinical decision-making, with implications for payers, patients, and providers. The use of these models is likely to increase, as providers and patients seek to improve their clinical decision process to achieve better outcomes, while reducing overall healthcare costs.

[1]  Ian Roberts,et al.  Systematic review of prognostic models in traumatic brain injury , 2006, BMC Medical Informatics Decis. Mak..

[2]  E. Feskens,et al.  Performance of a predictive model to identify undiagnosed diabetes in a health care setting. , 1999, Diabetes care.

[3]  John J Mahoney Value-based benefit design: using a predictive modeling approach to improve compliance. , 2008, Journal of managed care pharmacy : JMCP.

[4]  Ian Graham,et al.  Evidence-based medicine and the practicing clinician , 1999, Journal of General Internal Medicine.

[5]  Nicolette F de Keizer,et al.  Performance of prognostic models in critically ill cancer patients – a review , 2005, Critical care.

[6]  A. Abu-Hanna,et al.  Prognostic Models in Medicine , 2001, Methods of Information in Medicine.

[7]  J. Wyatt,et al.  Commentary: Prognostic models: clinically useful or quickly forgotten? , 1995 .

[8]  K. Covinsky,et al.  Assessing the Generalizability of Prognostic Information , 1999, Annals of Internal Medicine.

[9]  N. Cook Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. , 2008, Clinical chemistry.

[10]  C. Dueker A predictive model for survival after in-hospital cardiopulmonary arrest. , 2005, Resuscitation.

[11]  W. McClellan,et al.  Validation of the pneumonia severity index. Importance of study-specific recalibration. , 1999, Journal of general internal medicine.

[12]  M. Fine,et al.  Validation of a pneumonia prognostic index using the MedisGroups Comparative Hospital Database. , 1993, The American journal of medicine.

[13]  Jose Salinas,et al.  A predictive model for massive transfusion in combat casualty patients. , 2008, The Journal of trauma.

[14]  M. Fine,et al.  Comparison of a disease-specific and a generic severity of illness measure for patients with community-acquired pneumonia , 1995, Journal of General Internal Medicine.