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Descriptive statistics that provide an overview of a specific data collection, which may be a sample of the population or a representation of the full population.are measures of variability  and central tendency are the two categories into which descriptive statistics are divided. The mean, median, and mode are examples of measurements of central tendency, and the standard deviation, variance, minimum and maximum variables, kurtosis, and skewness are examples of measures of variability.

     Descriptive statistics are analyzed by nurses to find trends and possible problems in patient data, such as blood sugar levels, allowing for prompt treatments. Descriptive statistics are analyzed by nurses to find trends and possible problems in patient data, such as blood sugar levels, allowing for prompt treatments. There is a growing demand on nurses to lead and engage in quality-improvement and evidence-based practice initiatives. Many healthcare organizations mandate that nurses participate in these activities in order to reach higher standards, including those seeking or currently holding Magnet designation from the American Nurses Credentialing Center(Lasater, et al 2019). 

     Descriptive analysis was the first method used to analyze the data. It has advanced to include increasingly quantitative methods. Logistic regression is one very helpful method.  It is very helpful when measuring results. Instead of calculating the probabilities of other possible outcomes, it computes the probability of one. This process is anticipated to become more crucial to nursing research due to the present clinical interest in forecasting nursing practice outcomes.  Some descriptive statistics  utilized in the Magnet designation requirements include: 

  1. The percentage of nursing turnover rates.
  2. Patient satisfaction satisfaction score averages.
  3. RN to patient ratio.
  4. The proportion of advanced-certified nurses

(Doucette, et al, 2022). 

 

References: 

     Lasater, K. B., Richards, M. R., Dandapani, N. B., Burns, L. R., & McHugh, M. D. (2019). Magnet hospital recognition in hospital systems over time. Health care management review, 44(1), 19–29. https://doi.org/10.1097/HMR.0000000000000167

     Doucette, Jeffrey N. DNP, RN, NEA-BC, FAAN, FACHE. Weighing the value of Magnet® recognition. Nursing Management (Springhouse) 53(9):p 48, September 2022. | DOI: 10.1097/01.NUMA.0000855932.63275.59

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