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

Do the processes of care that drive quality in a hospital interact with individual physicians? Such interactions might be separate from physician effects (e.g., intrinsic skill) or hospital effects (e.g., advanced technology or efficient processes). For example, a positive interaction effect could stem from a well-fitting surgical team where a cardiac surgeon is matched with distinct hospital-based resources (e.g., a particular operating room, familiar scrub nurses, or anesthesiologists). If hospital–surgeon interactions did contribute meaningfully to the variability in patient outcomes, then improving quality would require more than monitoring and enhancing individual provider quality or fine-tuning hospital processes. An additional imperative would then be to match providers to hospital assets in teams that “fit” together better. We hypothesize that the “fit” between hospital and surgeon could thus moderate the impact of the average process of care in a hospital or the impact of the average surgeon's practice pattern. The potential sign of such moderation is not clear. For example, high familiarity among members of a surgical care team could improve outcomes (Pisano, Bohmer, and Edmondson 2001; Reagans, Argote, and Brooks 2005;). Poor surgeon–hospital combinations might lead to stark deviations from best practice as in pediatric cardiac surgery at the Royal Infirmary (Kennedy Commission, 2001). Scattered empirical evidence hints at such moderation. Recent work by Carey et al. (2008) suggests that a cardiac surgeon's effect on mortality is less beneficial when working across multiple high-volume hospitals than when concentrating cases within one high-volume hospital. Other work finds that the outcomes of the same surgeon vary across different hospitals (Hannan et al. 2003; Huckman and Pisano 2006; Miyata et al. 2008;). Case studies also point to the existence of interaction effects. For instance, the successful adoption of new minimally invasive techniques was moderated by surgeons' styles of interacting with their operating teams (Edmondson et al. 2003). We investigate these important questions using a novel approach and rich observational data on cardiac surgeries in Massachusetts. The patient records comprise clinically audited, chart data, allowing accurate and comprehensive control for patient risk (Torchiana and Meyer 2005; Tsai et al. 2006;). Our use of hierarchical models extends prior use of random effects for physicians (Bronskill et al. 2002; Pietz et al. 2002; Ferraris et al. 2008;), for hospitals (Hannan et al. 2003; Peterson et al. 2004; Carey et al. 2008; Marcin et al. 2008;), or for both (Austin, Tu, and Alter 2003; Hirth et al. 2009;). Our approach hinges on two-way crossed mixed models with random effects for hospital, surgeon, and the hospital × surgeon interaction. The interaction effects are identified because surgeons are not exclusively nested within hospitals. Our outcomes of interest also extend beyond traditional endpoints of 30-day mortality, long-term follow-up mortality, and major morbidity events. We hypothesize that unobservable hospital × surgeon interactions could also impact perioperative measures such as total skin-to-skin, cross-clamp, and perfusion durations, and the use of internal mammary artery grafts, off-pump techniques, and particular discharge medications. These quality metrics are in keeping with the recent focus on processes of care in cardiac surgery (Shahian 2004; Shahian et al. 2007; Shahian and Normand 2008;).