Areeba Kara1,2,3, Mindy E Flanagan4, Rachel Gruber4, Kathleen A Lane5, Na Bo5, Kurt Kroenke2,4, Michael Weiner2,4,6. 1. Indiana University Health Physicians, Indianapolis, Indiana. 2. Indiana University School of Medicine, Indianapolis, Indiana. 3. ASPIRE Scholar Division of General Internal Medicine and Geriatrics, Indianapolis, Indiana. 4. William M. Tierney Center for Health Services Research, Regenstrief Institute, Indianapolis, Indiana. 5. Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana. 6. US Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center Indianapolis, Indiana.
Abstract
BACKGROUND: Geographic cohorting (GCh) localizes hospitalists to a unit. Our objective was to compare the GCh and non-GCh workday. METHODS: In an academic, Midwestern hospital we observed hospitalists in GCh and non-GCh teams. Time in patient rooms was considered direct care; other locations were considered 'indirect' care. Geotracking identified time spent in each location and was obtained for 17 hospitalists. It was supplemented by in-person observation of four GCh and four non-GCh hospitalists for a workday each. Multilevel modeling was used to analyze associations between direct and indirect care time and team and workday characteristics. RESULTS: Geotracking yielded 10,522 direct care episodes. GCh was associated with longer durations of patient visits while increasing patient loads were associated with shorter visits. GCh, increasing patient loads, and increasing numbers of units visited were associated with increased indirect care time. In-person observations yielded 3,032 minutes of data. GCh hospitalists were observed spending 56% of the day in computer interactions vs non-GCh hospitalists (39%; P < .005). The percentage of time spent multitasking was 18% for GCh and 14% for non-GCh hospitalists (P > .05). Interruptions were pervasive, but the highest interruption rate of once every eight minutes in the afternoon was noted in the GCh group. CONCLUSION: GCh may have the potential to increase patient-hospitalist interactions but these gains may be attenuated if patient loads and the structure of cohorting are suboptimal. The hospitalist workday is cognitively intense. The interruptions noted may increase the time taken for time-intensive tasks like electronic medical record interactions.
BACKGROUND: Geographic cohorting (GCh) localizes hospitalists to a unit. Our objective was to compare the GCh and non-GCh workday. METHODS: In an academic, Midwestern hospital we observed hospitalists in GCh and non-GCh teams. Time in patient rooms was considered direct care; other locations were considered 'indirect' care. Geotracking identified time spent in each location and was obtained for 17 hospitalists. It was supplemented by in-person observation of four GCh and four non-GCh hospitalists for a workday each. Multilevel modeling was used to analyze associations between direct and indirect care time and team and workday characteristics. RESULTS: Geotracking yielded 10,522 direct care episodes. GCh was associated with longer durations of patient visits while increasing patient loads were associated with shorter visits. GCh, increasing patient loads, and increasing numbers of units visited were associated with increased indirect care time. In-person observations yielded 3,032 minutes of data. GCh hospitalists were observed spending 56% of the day in computer interactions vs non-GCh hospitalists (39%; P < .005). The percentage of time spent multitasking was 18% for GCh and 14% for non-GCh hospitalists (P > .05). Interruptions were pervasive, but the highest interruption rate of once every eight minutes in the afternoon was noted in the GCh group. CONCLUSION: GCh may have the potential to increase patient-hospitalist interactions but these gains may be attenuated if patient loads and the structure of cohorting are suboptimal. The hospitalist workday is cognitively intense. The interruptions noted may increase the time taken for time-intensive tasks like electronic medical record interactions.