A hypothesis test study allows determining if a hypothesis is true based on research findings. For example, concluding whether an increased nurse-to-patient ratio results in improved patient health outcomes would help make decisions about the desired staffing levels (Giuliano, Danesh, & Funk, 2016). The present paper will describe a study to test the proposed hypothesis.
Prior to beginning the study, it is essential to identify the research and null hypotheses. The research hypothesis is that an increased nurse-to-patient ratio results in a decreased rate of readmissions. The null hypothesis is that there is no correlation between the nurse-to-patient ratio and readmissions rate. The independent variable in the proposed study is the nurse-to-patient ratio, whereas the dependent variable is the rate of readmissions at 30 days after discharge.
To test the hypothesis, it would be necessary to study readmission rates at two separate acute care hospitals with different nurse staffing levels. The data should be recorded for at least three months to make viable conclusions. It is expected that the difference in 30-day readmission rates would be comparable to those in nurse-to-patient ratios. For instance, if Hospital 1 has a 20% higher nurse-to-patient ratio than Hospital 2, it can be guessed that the readmissions rate in Hospital 1 will be 15-20% lower than in Hospital 2.
The outcomes of this hypothesis test study could help in administrative decision-making and patient advocacy. If the null hypothesis were rejected, it would mean that a higher nurse-to-patient ratio contributes to patient health and improves patient safety. Nurses would be able to use these results to show hospital leaders that it is critical to increasing the number of nurses employed to enhance patient outcomes.
Reference
Giuliano, K. K., Danesh, V., & Funk, M. (2016). The relationship between nurse staffing and 30-day readmission for adults with heart failure. The Journal of Nursing Administration, 46(1), 25-29.