The short-term inpatient care work planning problem consists of assigning tasks to hourly rounds. Due to the fast pace of healthcare systems and the cognitive limitations of humans, work planning strategies are often static and may be inadequate on certain workdays. This study analyzes work planning policies that can be applied by healthcare workers using limited computational resources. The problem was formulated as a variation of the 0-1 generalized assignment problem with nonlinear capacity constraints. Current, optimal, and practical work planning strategies were evaluated in terms of quality and cognitive complexity. With Monte Carlo Simulation the strategies were compared using scenarios based on data collected from an inpatient care hospital. The practical work planning strategies resulted in worse performance than the optimal solution but still performed better than the current strategy in terms of tardiness, one of the quality metrics evaluated. The results also indicated that the practical strategies, even though they were more complex than the current strategies, can be applied without requiring additional computational resources.