Critique of Correlates and Predictors of Missed Nursing Care in Hospitals

This critique analyzes the article 'Correlates and Predictors of Missed Nursing Care in Hospitals' and discusses the significance of missed care, research design and methods, findings, and implications for healthcare policies.

Running head: CRITIQUE
Primary research paper
Name of the Student
Name of the University
Author note

1CRITIQUE
Introduction- Missed care is commonly defined as care that is unfinished, implicitly
rationed or left undone and represents a domain of health and social care that is underused
and creates significant negative impacts on the health and safety of patients (Jones, Hamilton
& Murry, 2015). One of the most crucial skills that are imperative for new nursing
professionals involve the capability to prioritize patient care at the time of admissions. It has
been found that variations in patient condition, medications or supplies, unobtainable
equipment, demand from physicians, and other unforeseeable circumstances often derail the
plan of care delivery (Blackman et al., 2015). This essay will contain a critical appraisal of
the article- Bragadóttir, H., Kalisch, B. J., & Tryggvadóttir, G. B. (2017). Correlates and
predictors of missed nursing care in hospitals. Journal of clinical nursing, 26(11-12), 1524-
1534. In order to address the consequences of missed nursing care (MNC) the researchers
tried to evaluate the correlates and predictors for the same.
Research problem and its significance- The researcher addressed a well-focused issue
based on the fact that errors in hospitals due to missed nursing care (MNC) has been
identified as a potential factor that leads to patient death (Bragadóttir, Kalisch &
Tryggvadóttir, 2017). Most patient safety initiatives place an emphasis on lowering the risks
of fatal errors that occur due to missed care. The research was based on the fact that
notwithstanding the nation and setting, some of the most commonly identified aspects of
MNC encompass mouth care, on time feeding patients, turning and ambulating patients,
comfort talk, patient education, documentation, medication administration, and
interdisciplinary rounds (Kalisch & Xie, 2014). In addition, the authors were also correct in
recognising the fact that magnet hospitals demonstrate a significant reduction in the overall
MNC rates, when compared to non-magnet counterparts, and some of the common reasons
that contribute to the situation include communication and labour resources (Friese et al.,
2015). In addition, the researchers were also correct in identifying poor work environment as

2CRITIQUE
a major predictor of MNC, which in turn resulted in a deterioration of health outcomes and
increased the rates of hospital readmissions (Bragadóttir, Kalisch & Tryggvadóttir, 2017).
Significance of the research problem can be accredited to the fact that missed care reduces
patient satisfaction. Hence, identification of the correlates and predictors would help
healthcare professionals take necessary efforts to enhance patient health and wellbeing
(Kalisch, Xie & Dabney, 2014). Owing to the fact that missed care forms a critical
component of medical error, the prominence of the research problem is that the findings will
help in making necessary changes in the healthcare policies of organisations, with the aim of
reducing the prevalence of MNC.
Research design and methods- The researchers adopted a cross-sectional design for
evaluating the predictors and correlates of MNC in hospitals. Adoption of this research
design is advantageous owing to the fact that it helps in proving assumptions, captures data
within a particular time frame, and also contains provides a snapshot of several variables
within the research duration. In addition, usage of data that has been routinely collected
facilitates the condition of large investigation at little or no expenditure. However, potential
limitations of this research design include the failure of this approach in determine causal
effect, and limitations in analysing particular behaviour over a definite time (Sedgwick,
2014). The researchers recruited 865 nursing professionals who were involved in providing
direct care to the patients, through the process of purposive sampling (Bragadóttir, Kalisch &
Tryggvadóttir, 2017). Hence, the sampling process was advantageous since selection of
participants was done on the basis of attributes that are relevant within the target population
group, which in turn facilitated generalisation of the collected data (Etikan, Musa &
Alkassim, 2016). Nonetheless, the process has been found to be enormously susceptible to
researcher bias.

3CRITIQUE
Following sample recruitment, the researchers collected data based on teamwork,
MNC, and background variables with the use of two questionnaires namely, Nursing
Teamwork Survey-Icelandic (NTS-Icelandic) and MISSCARE Survey-Icelandic
(Bragadóttir, Kalisch & Tryggvadóttir, 2017). Surveys are commonly used for data collection
in quantitative research owing to the fact that they are comparatively easy to administer, get
developed within a limited time frame, can be administered remotely, and help in the
collection of extensive responses to the questions present. Therefore, adoption of surveys for
collecting information on the predictors and correlated of MNC was a correct approach.
Nonetheless, presence of close-ended questions might make it difficult to interpret the actual
thoughts and perceptions behind specific responses, and the results are often subjective
(Holmes & Hazen, 2014). Taking into consideration the fact that the researchers had recruited
Icelandic population for the cross-sectional study, the survey questions had been translated
from English to the local language. This was followed by categorisation of the hospitals to
different units, following which several staff characteristic variables were determined
namely, gender, age, work hours, job title, experience, sick days, staffing adequacy, and
patients cared for.
While the MISSCARE Survey-Icelandic helped in determining answers related to
MSN activities and the reasons behind them, the Nursing Teamwork Survey-Icelandic was
used for assessing general teamwork and five features of teamwork namely, trust, team
orientation, common mental models, backup, and team leadership (Bragadóttir et al., 2015;
Bragadóttir et al., 2016). Response rate for the surveys was an estimated 69.3%. In addition,
the researchers conducted a bivariate and descriptive statistical analysis, by using the SPSS
22.0 software. While descriptive studies provided summarised information on the measures
and the samples, the bivariate analysis helped in determining the relation between different
variables.

4CRITIQUE
Findings- The results of the cross-sectional study suggested that there was a
significant correlation between MNC and the type of units and hospitals. In addition, MNC
rates were also influenced by other predictors such as, the role and age of participants, their
perceptions on presence of sufficient nurse staffing, and the amount of teamwork that was
operative within the hospital settings. On conducting a multiple regression analysis, it was
found that nurse role, unit type, staffing adequacy, and age predicted 16% of the difference in
MNC (Bragadóttir, Kalisch & Tryggvadóttir, 2017). The researchers also provided evidence
for the fact that on controlling the aforementioned predictors, nursing teamwork was also
responsible for predicting an extra 14% variance in MNC. Hence, the researchers were able
to provide adequate information on the correlates and predictors related to MNC in Iceland
hospitals.
High response rate of the nurse suggest that the findings can be applied to the local
population as well, and are in accordance to the theoretical framework of MNC model that
aims to predict the relationship between nursing processes, practice environment, and patient
health outcomes (Bragadóttir, Kalisch & Tryggvadóttir, 2017). The predictors identified
through the survey are congruent to the fact that labor resource allocation, education
level, nurse competencies, communication, nurse number and type, and teamwork are some
core traits that influence priority decision making, thereby causing MNC (Castner, Wu &
Dean-Baar, 2015). Hence, effective healthcare policies can be formulated by taking into
account the identified predictors, with the aim of addressing missed care.
The results will also benefit the enforcement of practice approaches that are based on
evaluation of administrative nurse staffing plans, patient complexities, surge in demand,
staffing adequacy, and skilled nursing (Department of Health, 2018). Furthermore,
identification of the factors that lead to MNC will also help in ensuring that the nurses deliver
care in accordance to localised policies, with the aim of ensuring that patients receive care

5CRITIQUE
services that are effective, safe, timely, and fitting to their needs, while maintaining the
professional practice standards.
Conclusion- To conclude, MNC is principally a concern of time pressure and
challenging demands, and suitable nurse staffing is desirable to avert it. Nurses play a crucial
role in maintaining patient safety and there is a well-defined link between nurse staffing and
patient health outcomes. The research analysed in the essay helped in determining the
correlates and predictors. However, lack of control units for the variables might have resulted
in bias in the research. Nonetheless, the researchers were able to conduct a the survey among
the complete population of Icelandic nurses, thus establishing the reliability and validity of
the study findings.

6CRITIQUE
References
Blackman, I., Henderson, J., Willis, E., Hamilton, P., Toffoli, L., Verrall, C., ... & Harvey, C.
(2015). Factors influencing why nursing care is missed. Journal of clinical
nursing, 24(1-2), 47-56.
Bragadóttir, H., Kalisch, B. J., & Tryggvadóttir, G. B. (2017). Correlates and predictors of
missed nursing care in hospitals. Journal of clinical nursing, 26(11-12), 1524-1534.
Bragadóttir, H., Kalisch, B. J., Smáradóttir, S. B., & Jónsdóttir, H. H. (2015). Translation and
psychometric testing of the Icelandic version of the MISSCARE
Survey. Scandinavian journal of caring sciences, 29(3), 563-572.
Bragadóttir, H., Kalisch, B. J., Smáradóttir, S. B., & Jónsdóttir, H. H. (2016). The
psychometric testing of the Nursing Teamwork Survey in Iceland. International
journal of nursing practice, 22(3), 267-274.
Castner, J., Wu, Y. W. B., & Dean-Baar, S. (2015). Multi-level model of missed nursing care
in the context of hospital merger. Western journal of nursing research, 37(4), 441-
461.
Department of Health. (2018). Policy and Practice. Retrieved from
https://ww2.health.wa.gov.au/Articles/N_R/Nursing-and-Midwifery-resources
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and
purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4.
Friese, C. R., Xia, R., Ghaferi, A., Birkmeyer, J. D., & Banerjee, M. (2015). Hospitals in
‘Magnet’program show better patient outcomes on mortality measures compared to
non-‘Magnet’hospitals. Health Affairs, 34(6), 986-992.

7CRITIQUE
Holmes, J., & Hazen, K. (Eds.). (2014). Research methods in sociolinguistics: A practical
guide (Vol. 5). John Wiley & Sons.
Jones, T. L., Hamilton, P., & Murry, N. (2015). Unfinished nursing care, missed care, and
implicitly rationed care: State of the science review. International journal of nursing
studies, 52(6), 1121-1137.
Kalisch, B. J., & Xie, B. (2014). Errors of omission: Missed nursing care. Western Journal of
Nursing Research, 36(7), 875-890.
Kalisch, B. J., Xie, B., & Dabney, B. W. (2014). Patient-reported missed nursing care
correlated with adverse events. American Journal of Medical Quality, 29(5), 415-422.
Sedgwick, P. (2014). Cross sectional studies: advantages and disadvantages. Bmj, 348,
g2276.