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Data Management

Data Management

Dr. Charrier,

Thank you for your response. Clearly prescribed data management procedures have several advantages, including increasing the productivity level of an organization. Good data management eases the employees’ work of finding and understanding information needed for a given task. A clearly prescribed data enhances a detailed conclusion on a study by allowing staff to easily validate the result (Engelhardt, 2017). In addition, good data management promotes the productivity of an organization by allowing the safe storage of information for future reference and easy retrieval. Effective data management renders an organization more cost-effective through the avoidance of unnecessary duplications. This ensures that employees never conduct the same research and analysis that was already done by other researchers. Finally, data management reduces the risk of data security. Properly managed data procedures prevent information from leaking to a third party (Engelhardt, 2017).


Engelhardt, M. A. (2017). Hitching healthcare to the chain: An introduction to blockchain technology in the healthcare sector. Technology Innovation Management Review7(10).

Responsing to Shibin Joseph Post


Thank you for this informative post. I agree that in descriptive analysis, data analysis is used to give a meaningful summary of data, and a generalized statement on a population based on a smaller sample size can be created using inferential data. Descriptive analysis refers to statistically describing or presenting the hypotheses of interest or the associations between these thoughts. A basis of quantitative data analysis is always achieved when a descriptive analysis is used with simple graphic analysis. While descriptive analysis simply describes what is presented by the data, inferential statistics will try to reach a conclusion that extends past the immediate data. For example, an inferential analysis may be used when there is a need to infer from the data sample what the population might think and to make a judgment of the probability that an observed variable group is dependable or that might have occurred by coincidental (Loed, et al., 2017).


Loeb, S., Dynarski, S., McFarland, D., Morris, P., Reardon, S., & Reber, S. (2017). Descriptive Analysis in Education: A Guide for Researchers. NCEE 2017-4023. National Center for Education Evaluation and Regional Assistance.


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Data Management

Data Management

ARTICLE: Al Ma’mari, Q., Sharour, L. A., & Al Omari, O. (2020). Fatigue, burnout, work environment, workload and perceived patient safety culture among critical care nurses. British journal of nursing29(1), 28-34.

 Purpose of the Study: 

Patient safety is among the most critical health issues across the globe (WHO, 2016). While patient safety is viewed as a critical factor in healthcare delivery, there are very few studies, as noted by the authors, that have been done in developing countries. In Oman, where the study took place, there were very few studies involving critical care nurses that had been conducted and which demonstrated the link between hypothesized factors and patient safety. Thus, the researchers aimed at identifying the patient safety perceived predictors among critical care nurses. The participants were drawn from two hospitals in Muscat, the capital city of Oman. The study explored whether there is a link between critical care nurses’ work environment, burnout, workload, and fatigue, and perceived patient safety

Research & Design: 

A descriptive cross-sectional study is where factors that are potentially related are measured for a defined population and at a specific time. This kind of study can be viewed as a snapshot of the characteristics and frequency of a population’s condition at a specific point in time (Solem, 2015). The current study used a descriptive cross-sectional method in assessing the patient safety perceived predictors among critical care nurses that work in two hospitals in Oman.


The participants for the study were drawn from two main government-owned hospitals in Muscat. The two hospitals were a teaching hospital- Sultan Qaboos University Hospital (SQUH) and the Royal Hospital. Initially, the number of nurses that were possible participants was 500, and these included all critical care nurses in the adult and pediatric ICUs, NICUs, post-cardiac surgery units, and coronary care units. However, the sample was large and needed to be reduced and remain representative without negatively impacting the final results. Hence, the researchers used Slovin’s formula to make an estimate of the required sample size (Tejada & Punzalan, 2012). The researchers also used a 95% confidence interval. The final number of participants was 222 though the survey was eventually circulated to 300 critical care nurses. The last step was done to mitigate attrition.

Data Collection:

The study used the Hospital Survey on Patient Safety Culture (HSOPSC) (Sorra and Dyer, 2010) to evaluate staff in hospital settings’ patient safety views; the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) for evaluating the burnout experience of participants; Fatigue Assessment Scale (FAS) to assess the fatigue levels of staff; and the NASA task load index (NASA TLX) for measuring the subjective workload. Additionally, the researchers used the Practice Environment Scale of the Nursing Work Index (PESNWI) to evaluate the work environment of the participants. The demographic data on the participants was collected through a self-reported questionnaire. The participants filled in their details, including gender, age, income, education level, hospital type, nationality, years of experience, and working hours per week.

Data Analysis:

The researchers used Pearson’s coefficient (r) in the identification of correlations between the individual independent variables-work environment, burnout, workload, and fatigue- and the overall patient safety perception, which was the dependent variable. The Pearson’s r is used in measuring a statistical association or relationship between two variables which are continuous and also provides information on the association’s magnitude as well as the relationship’s direction (Mukaka, 2012). In this study, the continuous single variable was the overall patient safety perception as the dependent variable, while the independent continuous variables were work environment, burnout, workload, and fatigue. SPSSv23 was used, and simple multiple regression analyses as well.


The study was cross-sectional, which constrained its ability to make an interpretation of the causal relationship between the collected data and study variables; this is because these were self-reported hence, possible bias may have influenced the responses. Therefore, it was impossible to make an evaluation of the causal relationship between the independent and dependent variables. Nonetheless, the researchers, sought to offer an initial understanding of the variables that made a prediction of the overall culture of patient safety perception among the participants. Additionally, the researchers pointed out that the cultural differences may have impacted the tools’ consistency. This is because the tools were initially created for the Western cultures, a culture that is different from that in Oman. These cultural context differences may have contributed to the differences as well as the lower values of internal consistency in the study for all the four independent variables.


The research showed that fatigue had a negative and detrimental effect on the overall patient safety perception by nurses. Also, the nurse workloads were shown not to be correlated with the overall patient safety perceptions. Further, the findings indicated a positive relationship between the work environment and the perception of nurses on the dependent variable. Emotional exhaustion and depersonalization had negative correlations with the overall patient safety perceptions while personal accomplishment, which was the third burnout subscale, was positively correlated with patient safety overall perceptions. The researchers noted that it was critical for the study to identify the predictors of patient safety perceptions so as to offer insights to the hospitals and other healthcare facilities, on areas to focus on when putting up strategies for changing the nurses’ attitudes and improving patient safety.

Reading Research Literature:

It is important to read and understand literature because it gives a process description of how a research was conducted and how the conclusion was reached. It also allows for the reader to point out any weaknesses or robustness of the research. Additionally, by reading the article, the reader gets an idea of how to conduct a similar research or a different research using a similar research method. I have learned no matter how many mitigating steps are taken a research will always have a limitation or two. In this case, the researcher carefully chose the tools to use, but because of the cultural context differences, the results were affected.


Al Ma’mari, Q., Sharour, L. A., & Al Omari, O. (2020). Fatigue, burnout, work environment, workload and perceived patient safety culture among critical care nurses. British journal of nursing29(1), 28-34.

Mukaka, M. M. (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi medical journal24(3), 69-71.

Solem, R. C. (2015). Limitation of a cross-sectional study. American Journal of Orthodontics and Dentofacial Orthopedics148(2), 205.

Sorra, J. S., & Dyer, N. (2010). Multilevel psychometric properties of the AHRQ hospital survey on patient safety culture. BMC health services research10(1), 1-13.

Tejada, J. J., & Punzalan, J. R. B. (2012). On the misuse of Slovin’s formula. The Philippine Statistician61(1), 129-136.

World Health Organization. Patient safety assessment manual. 2nd ed. 2016. (accessed 12 June 2021)

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