Provider-hospital "fit" and patient outcomes: evidence from Massachusetts cardiac surgeons, 2002-2004

Abstract

Objective: To examine whether the "fit" of a surgeon with hospital resources impacts cardiac surgery outcomes, separately from hospital or surgeon effects.

Data sources: Retrospective secondary data from the Massachusetts Department of Public Health's Data Analysis Center, on all 12,983 adult isolated coronary artery bypass surgical admissions in state-regulated hospitals from 2002 through 2004. Clinically audited chart data was collected using Society of Thoracic Surgeons National Cardiac Surgery Database tools and cross-referenced with administrative discharge data in the Division of Health Care Finance and Policy. Mortality was followed up through 2007 via the state vital statistics registry.

Study design: Analysis was at the patient level for those receiving isolated coronary artery bypass surgery (CABG). Sixteen outcomes included 30-day mortality, major morbidity, indicators of perioperative, and predischarge processes of care. Hierarchical crossed mixed models were used to estimate fixed covariate and random effects at hospital, surgeon, and hospital × surgeon level.

Principal findings: Hospital volume was associated with significantly reduced intraoperative durations and significantly increased probability of aspirin, β-blocker, and lipid-lowering discharge medication use. The proportion of outcome variability due to unobserved hospital × surgeon interaction effects was small but meaningful for intraoperative practices, discharge destination, and medication use. For readmissions and mortality within 30 days or 1 year, unobserved patient and hospital factors drove almost all variability in outcomes.

Conclusions: Among Massachusetts patients receiving isolated CABG, consistent evidence was found that the hospital × surgeon combination independently impacted patient outcomes, beyond hospital or surgeon effects. Such distinct local interactions between a surgeon and hospital resources may play an important part in moderating quality improvement efforts, although residual patient-level factors generally contributed the most to outcome variability.

Figure 1

Surgeon and Hospital Random Effects for Major Morbidity Logistic Mixed Model

Figure 2

Surgeon and Hospital × Surgeon Interaction Random Effects for Major Morbidity