Escobar, Gabriel J., Kipnis, Patricia, Kerlin, Meeta Prasad, Bayes, Brian, Courtright, Katherine R., Raneses, Eli, Harhay, Michael O., Halpern, Scott D.
Objectives: Objectives:Without widely available physiologic data, a need exists for ICU risk adjustment methods that can be applied to administrative data. We sought to expand the generalizability of the Acute Organ Failure Score by adapting it to a commonly used administrative database.
Design: Design:Retrospective cohort study.
Setting: Setting:One hundred fifty-one hospitals in Pennsylvania.
Patients: Patients:A total of 90,733 ICU admissions among 77,040 unique patients between January 1, 2009, and December 1, 2009, in the Medicare Provider Analysis and Review database.
Measurements and Main Results: Measurements and Main Results:We used multivariable logistic regression on a random split cohort to predict 30-day mortality, and to examine the impact of using different comorbidity measures in the model and adding historical claims data. Overall 30-day mortality was 17.6%. In the validation cohort, using the original Acute Organ Failure Score model’s β coefficients resulted in poor discrimination (C-statistic, 0.644; 95% CI, 0.639–0.649). The model’s C-statistic improved to 0.721 (95% CI, 0.711–0.730) when the Medicare cohort was used to recalibrate the β coefficients. Model discrimination improved further when comorbidity was expressed as the COmorbidity Point Score 2 (C-statistic, 0.737; 95% CI, 0.728–0.747; p < 0.001) or the Elixhauser index (C-statistic, 0.748; 95% CI, 0.739–0.757) instead of the Charlson index. Adding historical claims data increased the number of comorbidities identified, but did not enhance model performance.
Conclusions: Conclusions:Modification of the Acute Organ Failure Score resulted in good model discrimination among a diverse population regardless of comorbidity measure used. This study expands the use of the Acute Organ Failure Score for risk adjustment in ICU research and outcomes reporting using standard administrative data.