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Michael Ong, MD, PhD; Alan Bostrom, PhD; Arpana Vidyarthi, MD; Charles McCulloch, PhD; Andrew Auerbach, MD, MPH

Arch Intern Med. 2007;167(1):47-52.

Background  House staff work-hour regulations have required residency programs to reengineer inpatient services. However, few data describe how house staff workload on a patient's day of admission or on subsequent hospital days influences patient outcomes.

Methods  Retrospective cohort analysis of 5742 adults admitted to an academic general medical service between July 1, 1998, and June 30, 2001.

Results  After multivariate risk adjustment for patient severity and other structural factors, we found that 2 different measures of house staff workload significantly affected patient outcomes. House staff workload increases on the day of admission, defined as each additional team admission on a patient's admission day, increased length of stay (difference, 3.09%; 95% confidence interval [CI], 2.22%-3.96%), total costs (difference, 2.31%; 95% CI, 1.29%-3.33%), and risk of inpatient mortality (odds ratio, 1.09; 95% CI, 1.02-1.15). Patients had an even higher mortality risk when more than 9 patients were admitted to their team on their admission day. In contrast, house staff workload increases during the patient's entire stay, defined as every additional patient added to the team average census, reduced length of stay (difference, –5.30%; 95% CI, –4.54% to –6.07%) and total costs (difference, –5.11%; 95% CI, –4.20% to –6.00%). Reductions in length of stay and costs were most striking when the team average census exceeded 15 patients.

Conclusions  Our findings suggest that higher house staff workload on admitting days—when fewer backup resources are available—increases resource use and may increase inpatient mortality. Conversely, a higher average team census was associated with reduced resource use, perhaps reflecting service-level adaptations to workload. Future studies should confirm these findings in larger trials.

Author Affiliations: Department of Medicine, University of California, Los Angeles (Dr Ong); and Departments of Epidemiology and Biostatistics (Drs Bostrom and McCulloch) and Medicine (Drs Vidyarthi and Auerbach), University of California, San Francisco.

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