Clinical Data Analysis for Evidence-Based Practice

In this case, the door-to-balloon time covers the period from the STEMI patient arrival at the facility to the initial balloon inflation during PCI (Shiomi, et al., 2012). Hence, onset time and presentation periods are not included in the collected data.

In an effort to determine if strategies for reducing door-to-balloon time for STEMI patients are successful, data collected on time before and after the implementation of strategies would be analyzed using the Mann–Whitney U test to show median time between the two groups. Hence, the statistical analysis would ensure that the importance of median time for DTB is understood (Ali, et al., 2012).

The true difference between the times will be noted. Data for this test are not normally distributed and, therefore, the study will use the Mann-Whitney test. It has been shown that the Mann-Whitney U test can be used to identify the score in time before and after the implementation of the strategies to reduce a time for STEMI patients (Willson, et al., 2010). The mean value instead of mean ranking is the most suitable for this test. In this case, the Mann-Whitney U test is applied instead of the possible independent samples t-test. Both the Mann-Whitney U test and independent samples t-test use the same measure of central tendency. That is, both the mean for the t-test and the median for the Mann-Whitney U test are used to create a measure of central tendency. It is imperative to note that the Mann-Whitney U test is based on a further assumption regarding the shapes of the distribution. This implies that the time recorded before and after the implementation of the strategies should have the same shape as the distribution, including dispersion.

Categorical data would be analyzed using the Chi-square test (Willson, et al., 2010). This test shows how likely it is that an observed distribution could happen by chance. The Chi-square test, also known as the goodness of fit test, assesses how well the noted data distribution fits with the anticipated distribution of independent variables. It only analyzes categorical data. That is, all data will be identified and put into various categories. The Chi-square test does not work with continuous data or parametric data. Both numerical and categorical data are suitable for the test. The analysis would reveal the difference between various participants – variations between STEMI patients. It would allow the investigator to explore differences in demographic of participants, such as variations in age, sex, and history of chronic conditions among others. Care must be taken when working with the Chi-square test because it does not explore the meaningfulness of categorical data. Hence, the researcher will have to explore whether the categories are meaningful if need be and importance of the divisions. This implies that the researcher must understand the relevance of data organization before performing a Chi-square test.

Different groups will be evaluated by using the Student t-test for the continuous variables (Hosseini, et al., 2011).

All qualitative data collected from data points such as physicians, administrators, and nursing staff would be transcribed and analyzed to determine key themes in STEMI patient management to reduce door-to-balloon time (Adams, Wong, & Wijeysundera, 2015). Previously, researchers had concentrated on issues related to patients, care providers and hospitals to determine factors responsible for delays in door-to-balloon time for STEMI patients (Adams et al., 2015). Nurses and physicians can explain their experiences with STEMI patients while patients will provide data related to institutional factors and personal experiences. For instance, it is expected that quantitative study developed for in-depth interviews with nurses, physicians, and nurse administrators would provide important information related to commitment to reduce door-to-balloon time due to internal drives. The thematic analysis will also explore support from senior management at the facility and their views on reducing door-to-balloon time. Further, thematic analysis may reveal the hospital’s approach to standard practices and flexibility in executing new procedures, communication between various stakeholders, collaboration between different professionals, and feedback to gauge progress. Finally, it is expected that thematic analysis would help to determine hospital cultures that support or hinder efforts to improve door-to-balloon time for STEMI patients presented at the ED. The thematic analysis, therefore, will play a critical role in exploring the subject and presenting in-depth accounts of the situation and management factors related to door-to-balloon time improvement (Biancardi, 2013).

Demographic findings involving quantitative variables between the groups would be presented as mean standard deviation (Hosseini, et al., 2011). Categorical variable results will be presented as percentage (Hosseini, et al., 2011).

Overall, time presented would show the median times for DTB. Median periods would be analyzed using the Mann–Whitney U test, categorical data shall be analyzed using Chi-square test while continuous data for standard deviation would be analyzed using t test. These analyses would involve the use of SPSS (Willson, et al., 2010). Finally, thematic analyses would be considered for qualitative data. It is assumed that these data analysis techniques applied would help the researcher to present accurate findings of the study results and present them in simple forms for the target audience.


Adams, J., Wong, B., & Wijeysundera, H. C. (2015). Root causes for delayed hospital discharge in patients with ST-segment Myocardial Infarction (STEMI): a qualitative analysis. BMC Cardiovascular Disorders, 15, 107.

Ali, M. J., Zelevinsky, K., Normand, S.-L. T., Lovett, A., Nedeljkovic, Z. S., & Jacobs, A. K. (2012). Trends in Door-to-Balloon Time and Mortality in STEMI Patients Undergoing Primary PCI in Massachusetts. Circulation, 126, A18556.

Biancardi, M. A. (2013). Door-to-balloon time in primary percutaneous coronary itervention for patients with ST-segment Elevation Myocardial Infarction. Malta Medical Journal, 25(4), 2-9.

Hosseini, S. K., Soleimani, A., Salarifar, M., Pourhoseini, H., Nematipoor, E., Abbasi, S. H., & Abbasi, A. (2011). Demographics and Angiographic Findings in Patients under 35 Years of Age with Acute ST Elevation Myocardial Infarction. Journal of Tehran University Heart Center, 6(2), 62–67.

Shiomi, H., Nakagawa, Y., Morimoto, T., Furukawa, Y., Nakano, A., Shirai, S.,… Kimura, T. (2012). Association of onset to balloon and door to balloon time with long term clinical outcome in patients with ST elevation acute myocardial infarction having primary percutaneous coronary intervention: observational study. BMJ, 344, e3257. Web.

Willson, A. B., Mountain, D., Jeffers, J. M., Blanton, C. G., McQuillan, B. M., Hung, J.,… Nguyen, M. C. (2010). Door-to-balloon times are reduced in ST-elevation myocardial infarction by emergency physician activation of the cardiac catheterisation laboratory and immediate patient transfer. Medical Journal of Australia, 193(4), 207-212.

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