A key issue in improving overall quality of the health care system is identifying heterogeneity among providers in outcomes-based performance measures. But to be valid, outcome-based quality monitoring efforts must properly account for inherent variability in risk associated with differences in baseline characteristics among patients as well as differences in procedural complexity. Thus optimal risk adjustment is a precondition for monitoring quality of care and interpreting public reports of hospital outcomes.
Many current risk adjustment measures have been criticized for including baseline variables that are too difficult to obtain for all patients or for inadequately adjusting for high-risk patients. We developed highly predictive risk adjustment models for 30-day mortality and morbidity based only on a small number of standardly-available preoperative baseline characteristics.
Our risk models include as inputs the Current Procedural Terminology code corresponding to the patient's primary procedure (American Medical Association), American Society of Anesthesiologists Physical Status, and age (for mortality) or hospitalization (inpatient vs. outpatient, for morbidity).
The development and validation of the risk models are described in detail within the following article:
Dalton JE, Kurz A, Turan A, Mascha EJ, Sessler DI, and Saager L (2011). Risk Quantification for 30-Day Postoperative Mortality and Morbidity in Non-Cardiac Surgical Patients. Anesthesiology
The R software for obtaining risk estimates for 30-day mortality and composite 30-day morbidity/mortality is available at the following links: