Using Patient-Staff Ratio to Improve Patient Care Outcomes

The persistence of nurse scarcity has been documented by many researchers as the leading problem in the critical care setting. A high nurse to patient ratio leads to poor healthcare outcomes associated with increased nurse burn out, medical errors, and low-quality care services. Solving the issue of nurse scarcity is still a challenge due to lack of an effective multidimensional staffing model. In this project, a multidimensional staffing model was developed based on the relationship between patient-to-staff ratio, together with and other factors in the care environment which impacts patient outcome. The project was framed on Donabedian's structure, process, and outcomes model. The research question involved establishing the multidimensional staffing model on the interaction between staffing levels and other contextual factors in a critical care setting. The research methodology involved a systematic review of 13 articles to develop the evidence-based best practice multidimensional staffing. The inclusion criteria were articles published between 2014 and 2019 and had been developed from quantitative methods, mixed methods, systematic reviews, or meta-analyses. A thematic analysis was used as the main data analysis method to develop meanings, subjectively, from the collected data. The results show that the best staffing model for nurses in a critical care unit is the nurse-to-patient ratio model. The proposed nurse-to-patient ratio is 1:2. These findings have strong implications for the nursing practice and the patients since the nurse-to-patient ratio model will lead to an increased number of nurses, reduced workload, and improve patient outcomes