Nurse Staffing, Medical Staffing and Mortality in Intensive Care

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Introduction

The problems of nurse shortages and inadequate staffing remain to be serious in the healthcare institutions in the United States and globally. The issue requires further discussion because researchers point to the relationship between the workforce size and mortality of patients in hospitals, and this problem is one of the most challenging questions in nursing. In their article “Nurse Staffing, Medical Staffing and Mortality in Intensive Care: An Observational Study”, West et al. (2014) described the results of the quantitative observational study aimed at exploring the above-mentioned issue. The purpose of this paper is to provide a critical analysis of the article with a focus on its effectiveness and significance to the field of nursing.

Research Problem and Purpose

Patients with severe diseases and those who have no assistance from the family are often treated in intensive care units (ICUs). However, the problem is in the fact that ICUs should be well-staffed to provide high-quality care, but the costs of hiring an adequate number of staff are high. Focusing on the aspect of the disparity between the required staff-patient ratio and ICUs’ actual staff policies, West et al. (2014) concentrated on the problem of the relationship between the staffing approach in ICUs and patient outcomes or mortality. The researchers noted that the previous studies were mainly qualitative, and they did not demonstrate the actual relationship, or they argued that ICUs had no problems with staffing. West et al. (2014) observed the situation in discussing the problem with the focus on possible gaps. They formulated the purpose of the research that was to explore the relationship between the staff number in ICUs and the level of mortality or patients’ “survival chances” (West et al., 2014, p. 782). The rationale for the research was also supported by the statement that the main evidence on the topic was presented in the studies by only a few investigators from the United States. Therefore, the study aimed at contributing to the existing knowledge in the area of nursing.

Research Questions and Hypotheses

Instead of presenting the research questions, West et al. (2014) focused on formulating hypotheses based on the literature review. In order to discuss the contribution of different types of personnel to the survival of patients in ICUs, the researchers provided different hypotheses for the relationship between the number of nurses and rates of patient mortality, the number of consultants and rates of mortality, and the number of support staff and mortality. The hypotheses were based on the assumption that the higher number of different specialists working in an ICU is related to the lower rates of mortality among severely ill patients. The final hypothesis was formulated to explore the relationship between the workload and the survival rates. The decision to investigate the studied relationship separately for different groups of the staff can be discussed as effective to assist in understanding the role of nurses in influencing the patient mortality rates when the staffing policy is not appropriate.

Theoretical Framework and Study Variables

The researchers identified the patient mortality rates in ICUs as the dependent variable, but to overcome the bias and uncertainties in the results, West et al. (2014) also identified the risk adjustment factors to exclude the aspects that could influence the patients’ death without the focus on the staffing problem. Independent variables were determined according to the hypotheses, and they included the specific “number of nurses per bed,” the number of consultants, the presence of an intensivist, and the presence of the support staff (West et al., 2014, p. 786). To receive the most accurate results, the researchers chose to divide the important variable measuring the number of nurses per bed into two variables to focus on differences among direct care nurses and supernumerary nurses. The overall framework and identified variables can be viewed as effective to study the aimed relationships to provide reliable results.

Review of Literature

West et al. (2014) indicated the literature review as the discussion of the previous literature on the topic at the beginning of the article. The researchers examined 50 articles, among which only 11 articles reported the studies conducted within the 2009-2014 years. However, the researchers cited the seminal papers that influenced the further discussion of the topic by investigators. The literature was divided into such categories as articles on nurse staffing, medical staffing, and workload. This approach allowed the detailed discussion of aspects of the problem. Concentrating on the nurse staff problem, the authors referred to articles written by the American, English, Korean, and Belgian authors to demonstrate the international role of the issue (Cho, Hwang, & Kim, 2008; Kane, Shamliyan, Mueller, Duval, & Wilt, 2007; Tourangeau, Doran, Hall, & O’Brien Pallas, 2007; Van den Heede, Sermeus, Diya, & Clarke, 2009). However, the researchers noted that the majority of reviewed studies were qualitative, and they did not provide effective evidence to prove or reject the idea of the relationship between nurse staffing and patient mortality rates. The authors also examined the literature on the medical staff and workload in ICUs in detail, and it was found that the previous studies failed to demonstrate the role of the medical workforce and workload in affecting patient mortality in ICUs with references to the effective data (Griffiths, Jones, & Bottle, 2013). From this point, West et al. (2014) concentrated on overcoming the gap in the existing research on the topic.

Methodology, Sample, Setting, and Extraneous Variables

West et al. (2014) selected the quantitative methodology to complete the cross-sectional observational study that was retrospective in its nature. The cross-sectional observational studies are usually descriptive, and they are effective to examine the relationship between the factors and outcomes during a certain period (Keele, 2010). The method is appropriate to test the hypotheses. However, the sampling approach selected by the researchers can be viewed as rather inefficient to provide credible results. Even though the researchers focused on the national sampling frame and used the UK National Research Centre data on more than 38,000 patients registered in 65 ICUs, as well as on nurse and medical staffing in those facilities, the data were related to 1998, and they can be inappropriate to represent the current situation in the field. From this point, the strengths of the method and sampling include the possibilities to use the data referred to the large sample size, but weaknesses are associated with the use of rather outdated information that cannot illustrate the modern situation in ICUs. The other limiting factors are extraneous variables that can influence the results and add to the number of study errors (Hackshaw, 2015). To eliminate the effect of extraneous variables, West et al. (2014) focused on the additional analysis and control of such causes of patient mortality in ICUs as the patient’s age, the severity of the disease, and other risk factors. This approach contributed to decreasing the level of bias.

Measurement and Data Collection

The data for the analysis were collected from two sources, including the data of the Intensive Care National Audit and Research Centre on patient mortality in the United Kingdom and the data of the Audit Commission on the staffing in ICUs and hospitals. The researchers decided to collect the data for both types of healthcare institutions related to the period of 1998 to compare the results and prove the credibility of conclusions regarding ICUs. These data were important to discuss the case of transferring patients from ICUs to hospitals. It was critical to determine the measures of the variables, and the dependent variable of the patient mortality was assessed with references to the length of patients’ staying in ICUs and hospitals and the regular number of admissions. The number of transfers was also considered. This approach can be discussed as effective to measure the aimed variable (Harrison, Parry, Carpenter, Short, & Rowan, 2007). In addition, the measurement of the risk adjustment variable was added to reduce the bias. The authors discussed the measurement of independent variables while presenting the rationale for selecting them for the study. It was noted that participation in the study was voluntary, and the use of the data was agreed with the National Research Centre.

Analysis and Results

The multilevel regression was utilized to conduct the statistical analysis of the collected data. The appropriateness of the chosen statistical method to study the observations as unity is proved with references to the previous studies in the field (Gelman & Hill, 2006). It was found that more than 16% of patients died in the ICU in 1998, and more than 11% of patients died in the hospital after they were transferred from ICUs. The comparison of the mortality rates in ICUs and hospitals demonstrated that the rate was up to 34% in certain ICUs, and it was up to 48% in certain hospitals. The further analysis indicated that the highest level of mortality was in ICUs and hospitals with the lowest size of the nurse and medical staff. The researchers also found that the nurse-patient ratio played a more important role in influencing the patient’s survival than the presence of consultants. The researchers made an important conclusion that the support staff size was not statically significant to influence the patient mortality. West et al. (2014) also analyzed the role of the undesired factors to influence mortality, and the hypothesis regarding the positive relationship between the workload and patient mortality was also supported. The data analysis method was selected effectively to test the relationships, and the results allow the further calculations to predict how increases in the number of nurse staff can contribute to reducing the patient mortality rates.

Strengths and Limitations

It is possible to determine two main strengths associated with the study. The first one is the reliance on credible data related to the large sample of participants, ICUs, and hospitals. The other strength of the research is the use of effective data analysis methods to examine the relationships in these complex data. From this point, the researchers effectively chose the sample size, the source of the data, and the analytical tools. However, the study has limitations. The main limitation is the use of the data related to 1998. It is possible to expect that the staff size in the majority of researched ICUs changed under the impact of internal and external factors, including the healthcare policies. From this point, the practical value of the study is decreased. The other limitation is associated with the application of the cross-sectional study pattern instead of the longitudinal one because longitudinal studies can provide more valid results regarding the relationship between the determined variables.

Implications, Conclusions, Recommendations

The review of the literature and study results indicates that further research on the topic is possible. West et al. (2014) chose to analyze the relationship between the number of nurses and patient mortality in ICUs along with examining the relationship between the number of other medical and support staff and patient outcomes. These relationships were analyzed separately, but it is possible to assume that the impact of the combined nurse and medical staff’s assistance on the patients’ survival can also be observed. It is important to further research the role of the nursing staff in affecting the patients’ survival and the role of the medical staff’s professionalism in influencing the patients’ outcomes, as it was noted in previous studies (Kim, Bernato, Angus, Fleisher, & Kahn, 2010; Needleman, Buerhaus, Pankratz, Leibson, & Stevens, 2011). The researchers can study how the teamwork of nurses and physicians can contribute to increasing the chances of the patients’ survival and how many nurses should be scheduled for the shift to address the patients’ needs depending on the workload. The study of the nurse role is important in this case, and it is also necessary to focus on examining the workload effects on patient mortality.

The study results indicate that there is a direct positive relationship between the adequate high number of the nurse staff and medical staff and the high level of patients’ survival in ICUs. There is also a positive relationship between the high workload and the high patient mortality. The overall contribution of the study to the nursing field is significant, but the results are important to be used as the theoretical background for discussing the relationship between the principles of nurse staffing and the actual patient outcomes, including the rate of survival for severely ill patients or the rate of mortality. Still, the results provided by West et al. (2014) are not effective to be utilized in practice because they are general and based on outdated data sources.

The researchers also recommend using their findings in theoretical and qualitative studies. In addition, it is possible to recommend testing the findings with references to the severely ill patients in ICUs while discussing them as the group of persons who are highly dependent on the size of the nurse staff in the facility. Further studies should also include the focus on the other influential factors that were excluded in this study. It is also recommended to test the suggestion that the decreased workload in ICUs and the increased number of nurses can positively affect the high survival rates.

References

Cho, S. H., Hwang, J. H., & Kim, J. (2008). Nurse staffing and patient mortality in intensive care units. Nursing Research, 57(5), 322-330.

Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge, UK: Cambridge University Press.

Griffiths, P., Jones, S., & Bottle, A. (2013). Is “failure to rescue” derived from administrative data in England a nurse sensitive patient safety indicator for surgical care? International Journal of Nursing Studies, 50(2), 292–300.

Hackshaw, A. (2015). A concise guide to observational studies in healthcare. New York, NY: John Wiley & Sons.

Harrison, D. A., Parry, G. J., Carpenter, J. R., Short, A., & Rowan, K. (2007). A new risk prediction model for critical care: The Intensive Care National Audit and Research Centre (ICNARC) model. Critical Care Medicine, 35(1), 1091–1098.

Kane, R. L., Shamliyan, T. A., Mueller, C., Duval, S., & Wilt, T. J. (2007). Nursing staffing and quality of patient care. Medical Care, 45(12), 1195–1204.

Keele, R. (2010). Nursing research and evidence-based practice. New York, NY: Jones & Bartlett Learning.

Kim, M. M., Bernato, A. E., Angus, D. C., Fleisher, L. F., & Kahn, J. M. (2010). The effect of multidisciplinary teams on Intensive Care Unit mortality. Archives of Internal Medicine, 170(4), 369-376.

Needleman, J., Buerhaus, P., Pankratz, S., Leibson, C. L., & Stevens, S. R. (2011). Nurse staffing and inpatient hospital mortality. New England Journal of Medicine, 364(1), 11-18.

Tourangeau, A. E., Doran, D. M., Hall, L. M., & O’Brien Pallas, L. (2007). Impact of hospital nursing care on 30‐day mortality for acute medical patients. Journal of Advanced Nursing, 57(1), 32-44.

Van den Heede, K., Sermeus, W., Diya, L., & Clarke, S. P., (2009). Nurse staffing and patient outcomes in Belgian acute hospitals: cross-sectional analysis of administrative data. International Journal of Nursing Studies, 46(7), 928–939.

West, E., Barron, D. N., Harrison, D., Rafferty, A. M., Rowan, K., & Sanderson, C. (2014). Nurse staffing, medical staffing and mortality in Intensive Care: An observational study. International Journal of Nursing Studies, 51(5), 781-794.

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