It has been concluded that the problem of nurse understaffing negatively influences the work setting, the quality of care provided to patients, as well as patients’ health outcomes. However, among the identified implications, poor health outcomes of patients that received care in a facility that experiences understaffing is an issue that needs the most attention. Therefore, in order to evaluate the success of Evidence-Based Practice project, it is crucial to first create an understaffing indicator variable based on nurse staffing data in order to use it for examining patient information (Twigg, Gelder, & Myers, 2015). Moreover, it is necessary to create a variable that would indicate a number of understaffed shifts at the Palmetto Hospital, which patients experienced during their stay at the facility. To determine the statistical significance, logistic regression can be used due to its effectiveness in determining the odds of nurse-related patients’ health outcomes for individuals who have been exposed to understaffed shifts (Twigg et al., 2015). Targeting efforts at preventing and eliminating understaffing at the Palmetto Hospital is associated with considerations for improving the quality of care provided to patients.
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Staffing ratios are variables that may also be associated with decreases or increases in patient mortality rates because a facility was incapable of saving the lives of patients who experienced complications. In this case, measuring workload at the patient level can be effective in determining understaffing ratios at a healthcare facility. Patient-level workloads can be developed from therapeutic variables that are associated with patients’ conditions (Carayon & Gurses, 2008); for example, a Therapeutic Intervention Scoring System may be used in this case. Moreover, the situation-level workload is a variable that can explain the workload nurses have to deal with in a context of a specific health care microsystem established in a healthcare facility (Carayon & Gurses, 2008). The characteristics of such a microsystem include the following variables: poor physical work environment, lack of supplies, and ineffective communication between interdisciplinary teams. Collecting these variables can be effective for evaluating the success of an EBP project implemented in a healthcare facility. Lastly, measuring nurses’ workload at the job level is also important for evaluating the effectiveness of an EBP project since examining the problem of understaffing is impossible without determining the level of stress nurses experience, burnout indicators, as well as overall job satisfaction.
Correlational analysis can be conducted to determine the statistical significance of the mentioned variables because it will evaluate the strength of relationships that may exist between understaffing and burnout, understaffing and physical work environment, and so on. If there is a negative correlation between understaffing, and, for example, physical work environment at the Palmetto Hospital, then the future efforts targeted at eliminating the issue of understaffing among nurses should focus on improving the work environment since it has been proven to enhance job satisfaction in the workplace (Raziq & Maulabakhsh, 2015). The usage of correlational statistics during the EBP project can give valuable information to the healthcare facility’s stakeholders for improving those factors that happen to be correlated to nurse understaffing.
To conclude, the problem of nurse understaffing in a healthcare facility negatively influences the health outcomes of patients that have been exposed to understaffed shifts. Therefore, key stakeholders should collect data on factors that may contribute to understaffing and determine whether they are correlated to this issue.
Carayon, R., & Gurses, A. (2008). Nursing workload and patient human factors engineering perspective. In RG Hughes (Ed.), Patient safety and quality: An evidence-based handbook for nurses (pp. 110-130). Rockville, MD: Agency for Healthcare Research and Quality.
Raziq, A., & Maulabakhsh, R. (2015). Impact of working environment on job satisfaction. Procedia Economics and Finance, 23, 717-725.
Twigg, D., Gelder, L., & Myers, H. (2015). The impact of understaffed shifts on nurse-sensitive outcomes. Journal of Advanced Nursing, 71(7), 1564-1572.
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