Overnight cross-coverage on hospital medicine services: perceived workload based on patient census, pager volumes, and patient acuity

ABSTRACT

Objective

Little is understood about what contributes to perceived workload for those providing overnight coverage to hospitalized patients overnight, which limits the ability to modify these factors or to proactively identify appropriate staffing levels. The objective of this study is to understand the major contributors to perceived overnight cross-coverage workload.

Methods

Cross-covering advanced practice providers (APPs) in a large academic hospitalist group completed the National Aeronautics and Space Administration Task Load Index (NASA-TLX) at the end of each night shift. Other shift characteristics were collected, including patient load, assigned action items, watcher/unstable patients, newly admitted patients, number of units covered, total pages, peak pager density, rapid response team (RRT) activations, and intensive care unit (ICU) transfers.

Results

For 14 APP participants, who completed 271 post-shift surveys, the mean (SD) patient load was 49.9 (6.4) patients per night, and providers received a mean (SD) of 40.8 (13.7) total pages per shift. Mean (SD) NASA-TLX score was 35.1 (19.0). In multivariate modeling, total pages, action items, and any RRT or ICU transfer were associated with significant increases in the mean NASA-TLX score, with estimated effect sizes of 0.5, 0.8, and 14.3, respectively, per 1-unit increase in each shift characteristic. The greatest cumulative contributor to perceived workload was total number of pages, followed by the presence of any RRT activation/ICU transfer, with estimated effect sizes of 20.4 and 14.9, respectively.

Conclusions

Total number of pages was the greatest contributor to perceived workload. This study suggests that quality improvement initiatives designed to improve pager communication may considerably improve provider-perceived workload.

KEYWORDS:

• Cross-coverage
• paging
• advanced practice providers
• NASA-TLX
• workload

Acknowledgments

We thank Ivana T. Croghan, PhD, M. Caroline Burton, MD, and Darrell R. Schroeder for their assistance in preparing this manuscript.

Declaration of interest

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Reviewers disclosure

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

The authors received financial support in the form of an internal grant from the Department of Medicine.