The following is the critique of the research article titled: “Measuring the nursing workload per shift in the ICU”.
Research problem/purpose: The purpose of the study is to evaluate the differences in nursing workload between consecutive shifts, using a nursing workload measurement tool. The aim of the study is to measure the workload of nurses between two consecutive shift using the Nursing Activities Score (NAS). This study is designed to solve a common problem related to handling of nursing manpower in the ICU. The research is in line with existing knowledge about man power placement and workload. This research addresses an important issue pertinent to managing the global problem of nurses man power shortage and finding ways to effectively utilize nursing staff. (Debergh et al., 2012)
Review of literature: The review of literature explores various concepts like: shortage of nurses, personal cost and expense of running an ICU, efficiency of staffing, technology, investment in manpower and technology and needs of patients in the ICU. The review also creates awareness about the ill effects of understaffing the ICU. Under-staffing are associated with high level of nosocomial infection, high mortality rates in ICU admission, increased level of post-operative complications, increased use of resources and long stay at hospitals. All these findings are backed by literature references. Just like understaffing, overstaffing can also be disadvantageous as it will increase hospital fund dissipation. Further, there is nurses shortage and thus, there is a need to identify the right level of staffing for each shift in the ICU. The review also presents different nursing workload measurement tools that were developed over the last 30 years. These tools were designed with the intension of optimizing nursing resource use. The literature also justifies why the researchers have chosen NAS as a tool to study workload of nurses per consecutive shift.
The references were not very recent, but are relevant to the problem being studied. Papers from 1974 to 2009 are considered for this study. Considering the unique nature of this research problem, the lack of current studies could be the reason for choosing literature that are not very recent. (Debergh et al., 2012)
Theoretical framework: The theoretical framework of research, are based on evidences presented by studies that are published in nursing research and based on sound scientific reasoning. The article does not provide any theoretical framework, however, one can infer the theories after reading the article. Though majority of the theories in this study are based on nursing discipline; few management theories are also relevant to this study. (Debergh et al., 2012)
Variable/Hypothesis/Research question/Assumptions: There is no clear identification of dependent and independent variable. The study involves non parametric data. The scores are based on a number of variables that generates non parametric data. The questionnaire used to measure work load, has a number of items, and each can be taken as a variable. Scores are provided to these variables. The operational definition of these variables are provided in the article. The different shifts could be considered as independent variable and the work load in each shift could be treated as dependent variable. The work load and the shift are defined elaborately in the paper. (Debergh et al., 2012)
There is no definite hypothesis in this study. It is an explorative research study. The research hypothesis and research problem are not stated in the article. The probable research question for this study would be: what is the workload of nurse between consecutive shifts?
Methodology: It is a prospective study with mixed research design, involving qualitative and quantitative research methods. The study is based on inductive reasoning that the work load is based on number of events in the ICU. On the other hand, the deduced score of NAS tool, is used to measure working load. It would be correct to suggest that the study is based on both inductive and deductive reasoning. (Debergh et al., 2012)
The participants in this study are the nurses working in the ICU ward. The patient demographic helps to identify the work load. The study was conducted in pediatric, medical and surgical ICU of Ghent University hospital. The NAS score card was completed based on the nurse’s response. The detailed methodology is provided by the researchers and is well explained. A total of 255 nurses responded to the NAS score. The number of nurses is not relevant to the study. The scoring is done for each shift: morning shift, evening shift and night shift. Nurses from a total of 3, 486 shifts participated in this study. The response rate of the nurses was close to 93%. All ICU nurses in Ghent hospitals were asked to participate in the study. It could be called random sampling. The researchers have taken care to avoid bias in scoring, by hiding from the respondent, the weightage given to each item in the questionnaire. (Debergh et al., 2012)
Nurses had to start scoring the NSA sheet when they start attending to patient in the ICU in each shift. Training was provided to nurses joining the ICU and mock trials were conducted to reduce error in actual experiment. No special description about sampling method and procedure is provided in the paper. It is a probability sampling technique, as all nurses who are likely to work in ICU are likely to participate in this survey. The NSA tool which is the key instrument used to find the work load for consecutive shifts, is a well-tested and validated tool. It is not specifically developed for this study, but adapted for use in this research. The reason for choosing this tool is discussed in the literature review. The ethical considerations of the research are addressed in the paper. The permission to conduct research was obtained from local ethical committee. The severity of the diseases of patients admitted to ICU, was separately estimated and is used to complement the original research problem. (Debergh et al., 2012)
Data Analysis: Statistical analysis of the score obtained for each shift was done using a social science statistical package suitable for non-parametric data. Two un-paired groups were compared using Mann-Whitney’s U test. The three unpaired groups (i.e the three shifts) were compared using KruskalWallis test. (Debergh et al., 2012)
The results were presented using written and graphical description. The results are divided into different sections for the ease of understanding of the reader. These sections include; response rate from the shift, nursing staff, occupancy staff, demographics, severity of illness, NAS score per shift per patient, NAS score per nurse per shift, NAS score per nurse week vs weekend, NAS score for workload per 24 hours. Occupancy rate refers to the filling rate of the beds in the ICU. It will provide information on the number of empty beds and this is important in calculating NAS score. (Debergh et al., 2012)
Graphical representation of the results was done using box plot. There were a total of one table and 3 figures to represent the results. Table 1 provides the demographics of the population being studied. Figure 1: is the box plot representing the mean NAS per nurses shift. Figure 2 is the box plot representing the mean NAS per nurse per shit for the different ICUs, Figure 3 is the box plot representing the mean NAS per nurse per shift per week vs weekend. The graphical representation makes it easy to appreciate the results. (Debergh et al., 2012)
The highest score for Nursing activities score per patient per shift was highest for the morning shift, followed by evening and lowest for night shift. The difference in score was significantly higher for morning shift when compared to night shift. The medical ICU had the lowest NAS score for night shift, while the difference in pediatric and surgery ICU was not significantly different. The NAS score was higher in the morning shift of work days, when compared to weekends. (Debergh et al., 2012)
Findings and Conclusion: Though morning shifts had high scores, there was not much of a huge variation in score between the shifts. Pediatric and surgical ICU had the highest work burden, as anyone would expect, when compared to Medical ICU. Medical ICU patients require less nursing care when compared to surgical and pediatric ICU. The study was able to quantitate these difference and this knowledge may be beneficial to nursing management. (Debergh et al., 2012). The findings are consistent with previous research findings. The severity score was high in the medical ICU, even then the workload was comparatively lower in MICU. This is an interesting finding. The authors have discussed their results in the light of previous studies. (Debergh et al., 2012)
This study is replete with limitations. Though the nurses score the patients at the start of entering ICU, patients can enter and leave after the score is entered. This can affect the workload. The NAS score is also having a number of limitations. In certain ICUs, the patients admitted have more or less uniform problem and require uniform attention. Like example: burn ICU, liver ICU, neurosurgical ICU, etc. The NAS has scores for the work done in monitoring, administration of medicines, hygiene related procedure, support to patient and relatives, etc. All these scores can vary between ICUs. Thus the findings of this study cannot be generalized.
The findings of this study can have implication in nursing care and administration. No implication for future research was suggested by the authors. The study was able to provide a partial answer to the problem of staffing ICUs. The paper is written in a clear and understandable fashion.
References:
Debergh, D., Myny, D., Van Herzeele, I., Van Maele, G., Miranda, D., & Colardyn, F. (2012). Measuring the nursing workload per shift in the ICU. Intensive Care Med, 38(9), 1438-1444. http://dx.doi.org/10.1007/s00134-012-2648-3
