Abstract

Background: Little information is available on hospital performance following percutaneous coronary intervention (PCI) using all-comer populations. Using a fully Bayesian approach, Massachusetts has publicly reported all-cause in-hospital mortality (IHM) following PCI procedures performed since 04/01/2003 in all non-federal hospitals. Methods: Trained data managers prospectively collected information using the ACC-NCDR instrument supplemented by Mass-DAC specific elements. Operators and data managers adjudicated selected elements via chart review. Bayesian hierarchical regression models of IHM were estimated annually for two cohorts: (1) cardiogenic shock or ST-elevation myocardial infarction (STEMI); and (2) no shock and no STEMI. Posterior risk-standardized IHM rates were estimated. The odds of death for a patient treated at a hospital 1 SD below average quality relative to treatment at a hospital 1 SD above average quality quantified variation. Results: Presence of shock; emergent or salvage status; and compassionate use were changed after adjudication for more than one-quarter of adjudicated cases. No Shock and No STEMI Cohort: Between 04/03-09/08, the number of annual PCI admissions ranged from 11121-14504; number of hospitals from 14-22; and median post-PCI length of stay (LOS) remained unchanged (2 days). The crude IHM declined from 0.76% (81 of 10689) in 2003 to 0.50% (56 in 11275)in 2007. Model discrimination using 9 risk factors was high (ROC = 0.86). The odds of death at lower versus higher quality hospital ranged between 1.38 and 2.14. Shock or STEMI Cohort: the number of PCI admissions ranged from 2606-2800; number of hospitals from 18-24; and median post-PCI LOS remained unchanged (4 days). IHM declined from 6.86% (135 in 1968) in 2003 to 4.78% (130 in 2721)in 2008. Model discrimination was excellent using 7 covariates (ROC = 0.89). The odds of death at lower versus higher quality hospital ranged from 1.49 to 6.35. Conclusions: Key clinical factors, including shock, status of PCI, and compassionate use require adjudication. A small number of risk factors have excellent discrimination of in-hospital survivors at the patient level. Estimates of between-hospital variation can be used to quantify performance at the hospital level.

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