Provider-Hospital “Fit” and Patient Outcomes: Evidence from Massachusetts Cardiac Surgeons, 2002–2004

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.