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Nurse Staffing and Academic Knowledge Gaps
Introduction
The issue of an inadequate nurse-patient ratio is backed by a significant amount of studies. However, the findings of the studies often lack consistency and scientific rigor. The current literature review analyzes five studies on nurse staffing in order to identify the gaps in academic knowledge and suggest a potentially feasible direction for further research.
A Comparison of Research Questions
The studies selected for the literature review utilize both qualitative and quantitative approaches. For this reason, the research questions differ in both precision and scope. At this point, it should be mentioned neither of the studies contains an explicitly formulated question, which is a common occurrence in the studies with the qualitative design. However, in all cases, it can be extrapolated from the context and the stated purpose of the study.
For instance, a study by Backhaus, Verbeek, van Rossum, Capezuti, and Hamers (2014) explores the impact of nurse staffing on quality of care by summarizing the findings of the longitudinal studies. Therefore, it can be inferred that the research question was, Is there a consistent relationship between nurse staffing and quality of care in nursing homes? (Backhaus et al., 2014).
In a similar manner, the research question for the study by Cho et al. (2016) can be formulated as Is there an association between nurse staffing and overtime and nurse-perceived patient safety, nurse-perceived quality of care, and care left undone? The study by Hill (2017, p. 1) formulates the following research question: Do nurse-staffing levels affect patient mortality in acute secondary care? Dabney and Kalisch (2015) use the following research question: Is there an association between nurse staffing levels and missed care as reported by the patients? Finally, a research question inferred from the article by McHugh et al. (2016) is, Is there an association between nurse staffing and the mortality among in-hospital cardiac arrest patients?
The questions are similar in all five studies, with the difference being the clinical setting and, in some cases, a specific outcome. However, it should be emphasized that on three out of five occasions, the absence of a clearly formulated research question could compromise the reliability of findings.
A Comparison of Sample Populations
Three of the five studies used primary data in their analysis. The study by Dabney and Kalisch (2015) administered a survey to 729 inpatients in the setting compatible with the staffing criteria. Such size of the sample is sufficient to obtain statistically significant results representative of the population. Cho et al. (2016) collected the data by surveying the nurses from 60 out of 65 hospitals selected from the study. The departments which participated in the survey were selected randomly within each hospital, which eliminates the possibility of bias and further strengthens the feasibility of the results.
Finally, McHugh et al. (2016) retrieved data on 11160 patients in 75 hospitals across four states using three databases. Such a sample population is highly representative of the population in question and is consistent with the requirements of cross-sectional studies. Two other studies used secondary data for the analysis. In these cases, samples were comprised of the academic sources. Backhaus et al. (2014) employed 20 quantitative, longitudinal studies.
While such a sample is arguably insufficient for conducting a systematic review, it should be understood that it was most likely caused by the narrow scope of the inquiry and the rejection of cross-sectional studies that allowed for a more reliable result. Finally, Hill (2017) utilized 58 articles, all of which were verified for relevance, which can be considered a sufficient amount for the systematic review.
A Comparison of the Limitations of the Study
A study by Dabney and Kalisch (2015) has several limitations. For instance, the demographic data was not included in the analysis, which means that the applicability of the findings could not be established. In addition, the authors used a convenience sample, which means that the findings are not representative. Cho et al. (2016) specified that the cross-sectional method employed by their team could not be used to establish the causality among variables.
In addition, the data was based on the self-reports by the nurses rather than an objective evaluation, which reduces the studys objectivity. Finally, the obtained results were not positively verified for clinical significance despite the conclusive statistical significance determined by the analysis. McHugh et al. (2016) also point out that the cross-sectional design of their study prevents the researchers from definitively establishing the causality and the convenience nature of the sampling procedure undermines the reliability of the data.
In addition, the established relationship may be subject to certain confounding variables that may have been overlooked during the design phase. Backhaus et al. (2014) identify an inconsistency in the data selection criteria that permitted using longitudinal studies with no initial baseline measurement as well as the lack of uniformity of scales used in the initial studies. Hill (2017) does not identify the limitations, although it is apparent that the lack of uniformity across the sample and the inclusion of cross-sectional studies are two of the most evident limitations.
Conclusion
Despite the significant coverage in the current academic literature, several gaps can be identified in the understanding of the issue. Based on the literature review, it would be reasonable to suggest a longitudinal study with a properly conducted baseline measurement to eliminate ambiguity. It is also necessary to conduct a systematic review that would exclude results based on self-reports and establish the clinical significance of the outcomes obtained by the previous researchers.
References
Backhaus, R., Verbeek, H., van Rossum, E., Capezuti, E., & Hamers, J. P. (2014). Nurse staffing impact on quality of care in nursing homes: A systematic review of longitudinal studies. Journal of the American Medical Directors Association, 15(6), 383-393.
Cho, E., Lee, N. J., Kim, E. Y., Kim, S., Lee, K., Park, K. O., & Sung, Y. H. (2016). Nurse staffing level and overtime associated with patient safety, quality of care, and care left undone in hospitals: A cross-sectional study. International Journal of Nursing Studies, 60, 263-271.
Dabney, B. W., & Kalisch, B. J. (2015). Nurse staffing levels and patient-reported missed nursing care. Journal of Nursing Care Quality, 30(4), 306-312.
Hill, B. (2017). Do nurse-staffing levels affect patient mortality in acute secondary care? British Journal of Nursing, 26(12), 698-704.
McHugh, M. D., Rochman, M. F., Sloane, D. M., Berg, R. A., Mancini, M. E., Nadkarni, V. M.,& Aiken, L. H. (2016). Better nurse staffing and nurse work environments associated with increased survival of in-hospital cardiac arrest patients. Medical Care, 54(1), 74-80.
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