This study has several main findings. First, interhospital transfers of critically ill patients are common in fee-for-service Medicare, involving approximately 1 in 20 Medicare critical care stays of any length. Second, hospitals transfer critically ill patients to several other hospitals, in contrast to the hub-and-spoke model often invoked to conceptually explain secondary and tertiary care. Third, the network appears to systematically move patients towards better resourced hospitals.
These findings reveal the existence of an organic network of critical care transfers. Our main interpretation is that network analysis of the type reported in this paper can help define the criteria for a successful system of critical care transfers as well as suggest efficient ways to get there. For example, we observe that more central hospitals have more technologic capability, suggesting that the general flow of critically ill patients is toward better resourced hospitals. However, not all patients flow in this direction. Some move in the opposite direction and many patients do not move at all. Whether we rely on measures of hospital resources or, in the future, measures of hospitals’ clinical performance, the ICU transfer network we observe among Medicare beneficiaries reveals substantial promise for quality improvement. We might ask which patients should remain where they are, which should be transferred to better performing hospitals and which, perhaps, should be sent to less resourced hospitals to improve efficiency or free capacity for sicker patients who need it more.
Approximately 1 in 1,000 of possible interhospital connections actually occurred during 2005. In a low density network such as this, careful analysis may reveal quality-improving transfer relationships that are not currently established. Some hospitals may not be transferring patients to nearby facilities able to provide better care; some highly resourced hospitals may not be accepting patients from nearby less capable hospitals. Some hospitals may not currently have optimal capabilities to support the load of incoming critically ill patients, and WE COULD target those hospitals for improvement or redirection of patients. No current incentive arrangement suggests that the existing network will optimize itself, but network analyses can help policy makers see and shape an aggregate structure that is invisible to the individual hospitals and patients. Network analyses are widely used in other areas, including sociology, (22
) physics, (33
) molecular biology, (33
) management, (34
) and military operations, (35
) but only rarely in the study of health care systems. (37
The existing transfer system is not a simple hierarchy. Small community hospitals do not exist as satellites of single local centers, which then refer to dominant regional centers. This is true even within fee-for-service Medicare, so the heterogeneity of referrals is not the result of differing insurance plans within a hospital. While the secondary / tertiary hospital model may have some heuristic value, the implied hierarchy (in which secondary hospitals send but do not receive patients and tertiary hospitals receive but do not send patients) does not appear to be present in our data. Instead, hospitals appear to maintain diverse portfolios of other facilities to which they transfer patients. There are several potential reasons for this. There may be significant congestion at referral centers, with more central hospitals not able to accept all patients in a timely manner. Providers may be optimizing their referral patterns for local expertise based on particular patients’ illness. Families may have important roles in choosing closer, more prestigious, or better advertised hospitals. Differentiating among these hypotheses is essential to evaluating the extent to which the system is working to meet diverse, legitimate values, or is simply operating inefficiently.
The present work has a number of limitations. First, our data are derived from Medicare for a single year, and thus we cannot evaluate whether transfer patterns are different for non-Medicare patients or how they might change over time. However, over half of ICU patients are elderly, (41
) and Medicare is a domain of public policy interest in its own right. Second, our data reflect transfers between critical care hospitalizations; limitations in the data prevent us from examining only direct ICU-to-ICU transfers. It is possible that some of the transfers we have identified include patients who were discharge from the ICU to the floor at the first hospital, then transferred to a second hospital floor bed where they decompensated, requiring a distinct episode of ICU care. Our data cannot estimate the frequency with which this occurs. As a sensitivity test, we repeated our analyses using only transfers where the patients were
in the initial sending hospital for 1 day, and the patterns we report were all replicated. Third, while we have demonstrated that patients are in general transferred toward better-resourced hospitals, further work remains to estimate the effects of transfer on quality and cost using patient-level data, and how those outcomes might be further improved. Fourth, interhospital transfers are one part of the system for transferring critically ill patients, which includes transfers directly from Emergency Departments and, indeed, field triage by EMS units. A comprehensive approach to improving the efficiency of care for the critically ill will complement the analyses presented here with similarly detailed examinations of other areas, then integrate across systems..
Network analyses such as these provide structure, metrics and analytic tools to characterize and improve the relationships among hospitals. These networks likely have implications for the efficiency and adaptability of providers (42
), the diffusion of innovation (43
), and the spread of infections and other conditions (44
). As we work towards a health care system that provides the best patient care with existing resources, the network analysis in this study reveals how much we have achieved already, and how much more we might achieve as well.