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Learning Objective 1: establish an understanding of how continuity of care and delegation relates to workload among nursing staff
Learning Objective 2: identify how data management within a shared governance model can assist with improving workload
Staff from each of the 35 units participated in identifying the type and number of interventions routinely performed in their respective unit using a process called Work Complexity Assessment (WCA). Nursing Interventions Classification (NIC) was used to categorize levels of care intensity and parameters for delegation within licensure. Resulting data from the WCA were combined with unit level data derived from the Nursing Management Minimum Data Set (NMMDS) and the Healthcare Environment Survey (HES). The NMMDS and HES are psychometrically tested tools that collect data for qualtiy indicators and job satisfaction, respectively.
Correlation analysis of the WCA data with the NMMDS and HES data revealed units that had the most activity that did not require the licensure of a registered nurse had the most frustration with workload. Stepwise regression analysis revealed that 66% of workload was predicated by the nurse being able to take care of the same pateint from admission to discahrge from their respective unit.
Using data that is derived from staff, facilitates valid and accurate data for refinement of the organization. In addition, using tools that complement one another in areas of acuity assessment, nurse sensitive indicators, and job satisfaction of nursing staff facilitates development of models that are specific for unit level research, action planning, and refinement.