Model simulates effects of proposed changes to hospital staffing and wards

Researchers simulated four scenarios: geographically localizing housestaff and patients, adding a nursing unit, adding a hospitalist team, and adding both a nursing unit and a hospitalist team.


Simulation modeling allowed one hospital to predict the impact of changing the staffing and organization of its general inpatient medicine units, a recent study showed.

Researchers gathered administrative data about admissions and discharges, conducted a time-motion study, and applied expert opinion on workflow to create and validate a simulation of the hospitals' medicine units. They then simulated four potential changes: aligning medical teams with nursing units by localizing housestaff and patients; adding a 26-bed nursing unit; adding a hospitalist team; and adding both a nursing unit and a hospitalist team with four additional admissions per day. Results were published by the Journal of Hospital Medicine on Nov. 28.

The simulation showed that the first change (geographic localization) would decrease rounding time and patient dispersion for the teams but increase length of stay and ED boarding times. The second change (adding a nursing unit) did the opposite. Adding an additional hospitalist team did not have a significant effect on patients' average time in the system or the number of patients waiting for a bed but did decrease average team census, team utilization, and patient dispersion. The final change (adding a unit and a hospitalist team) increased admission volume while maintaining utilization and time in the hospital and ED but increased rounding time and patient dispersion.

“The outcomes for these what-if scenarios provided some important insights about the secondary effect of system changes and the need for multiple, simultaneous interventions,” the study authors said. “Leaders who want to increase capacity may need to consider both adding a hospitalist team and a nursing unit, and model the impact of each choice as described with a simulation.” They cautioned that such modeling is not simple and that all simulations are limited by the assumptions underlying their models. Other data and variables could be added to the model and affect the results, they said.

“This study is a breakthrough in the scientific rigor of hospital operations,” said an accompanying editorial. However, the editorialists noted a number of other factors they thought could be helpful to include in the modeling, such as the effects of multidisciplinary workflow and transfers; impacts of changes on burnout, patient satisfaction, and other wards' function; and calculation of costs.