Engineering a learning healthcare system: using health information technology to develop an objective nurse staffing tool

Abstract

Nurses represent the largest proportion of direct healthcare providers. Overstaffed or understaffed units will have implications for the quality, cost, patient, and nurse satisfaction. It is vital that nurses are armed with appropriate instruments and data to help them plan and implement efficient and effective nursing teams. A compelling case is made for the association between nursing care and clinical, quality, and financial outcomes. Even though there is a great body of work on the correlation, there is little agreement on the best approach to determine the correct balance between the patient-to-nurse ratios. The sheer number of variables depicted in the literature suggests why precise evidenced based formulas are difficult to achieve. This paper will describe a practice based knowledge generation mixed methods study using detailed observation and electronic health record abstraction to generate a structural equation for use in predicting staffing needs.

Figure 1

Figure 2

Direct Care Observation

Figure 3

Figure 4

Figure 5