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Clinical significance can be defined as the magnitude of the actual treatment effect which will determine whether the results of the trial are likely to impact current medical practice. Statistical significance on the other hand quantifies the probability of a study’s results being due to chance (Ranganathan, Pramesh, & Buyse, 2015). In clinical practice, the clinical significance of a result is dependent on its implications on existing practice. The clinical significance should reflect the extent of change, whether the change makes a real difference, how long the effect lasts, cost effectiveness and ease of implementation. Unlike statistical significance that has established traditionally accepted values; clinical significance is often based on the judgment of the health care provider and the patient.

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Statistical significance is majorly dependent on the study’s sample size; even with large sample sizes, small treatment effects can appear statistically significant and therefore the analyzer has to interpret carefully whether the significance is clinically meaningful. Statistical significance can be used to support positive outcomes in the EBP project by medical practitioners ensuring examination of the research outcomes in order to come up with the clinical significance. Several measures can be used to determine the clinical relevance required, confidence intervals and magnitude-based inferences. Statistical significance can also be used to achieve positive outcomes by analyzing the variability of subjects and the magnitude of effect on the patients during the research (Physical Therapy, 2014).


Physical Therapy, I. S. (2014). Beyond Statistical Significance: Clinical Interpretation of Rehabilitation Research Literature. International Journal of Sports Physical Therapy, 9(5), 726-736.

Ranganathan, P., Pramesh, C., & Buyse, M. (2015). Common Pitfalls in Statistical Analysis: Clinical versus Statistical Significance. Perspectives in Clinical research, 6(3), 169-170.


Clinical significance is defined as the practical value of an effect of treatment regardless of whether it has a real genuine, palpable, or noticeable effect on our everyday lives. Clinical significance reflects the impact on clinical practice. Statistical significance simply measures how probable any evident differences in outcome between control groups and treatment are. Statistical significance indicates the reliability of the study results. Clinically significant result occurs when medical experts believe that the finding is considered medically crucial and applied as a provision of care to patients. Clinical significance may help to validate whether a treatment effect has practical importance and if it has a real effect on daily life.

Since most statistically significant results are of clinical importance, it means that for a project to achieve positive outcomes, one must apply statistical significance. When the results are reliable, they can be applied to clinical significance. When the p-value value is positive, it means that it is not rejected; hence, the results will result in the projects achieving positive outcomes when applied to clinical significance. Although clinical significance is usually a subjective evaluation and cannot be established by a single experiential test, statistical significance must always be determined before determination of clinical significance in evidence based research practice.

I will be able to support positive outcomes and prove clinical significance of my project by ensuring that the results of decrease in 30 day readmission rates is statistically significant.

  Heavey, E.(2015). Differentiating statistical significance and clinical significance. American Nurse Today, 10(5): 26-28. Retrieved from https://www.brockport.edu/daily_eagle/doc/2015-04/item_8038_7659.pdf

Sedgwick, P. (2014). Clinical significance versus Statistical Significance. BMJ, 348(mar14 11), g2130-g2130. doi: http://dx.doi.org/10.1136/bmj.g2130

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