Variation in Do-Not-Resuscitate Orders and Implications for Heart Failure Risk-Adjusted Hospital Mortality Metrics

Abstract

Objectives: This study evaluated the effect of patient do-not-resuscitate (DNR) status on hospital risk-adjusted heart failure mortality metrics.

Background: Do-not-resuscitate orders limit the use of life-sustaining therapies. Patients with DNR orders have increased in-hospital mortality, and DNR rates vary among hospitals. Variations in DNR rates could strongly confound risk-adjusted hospital mortality rates for heart failure.

Methods: We identified a cohort of adults with primary diagnosis of heart failure by using the 2011 California State Inpatient Database, a claims database that captures "early DNR," within 24 h of admission. Hospital-level risk-standardized in-hospital mortality was determined using random effects logistic regression. We explored changes in outlier status in models with and without early DNR status.

Results: Among 55,865 patients from 290 hospitals hospitalized with heart failure, 12.1% (11.8% to 12.4%) had an early DNR order. Hospitals with higher risk-standardized DNR rates had higher risk-standardized mortality (ρ = 0.241; 95% confidence interval [CI]: 0.129 to 0.346; p < 0.001). Including DNR in models used to benchmark hospital mortality improved model performance (c-statistic from 0.821 [95% CI: 0.812 to 0.830] to 0.845 [95% CI: 0.837 to 0.853]; increased model explanatory power by 17%). Including DNR resulted in reclassification of 9.3% of hospitals' outlier status. Agreement in hospital outlier designation between models with and without DNR was low to moderate (kappa coefficient: 0.492; 95% CI: 0.331 to 0.654).

Conclusions: Accounting for DNR status resulted in a change in estimated risk-standardized mortality rates and classification of hospitals as performance "outliers." Given public reporting of heart failure mortality measurements and their influence on reimbursement, accounting for the presence of early DNR orders in quality measures should be considered.

Keywords: Centers for Medicare and Medicaid Services; Healthcare Cost and Utilization Project; state inpatient database; value-based purchasing.