Analyzing Data in a Quantitative Study, Essay Example

A quantitative approach related to the topic I am studying would involve the application of an intervention that allows us to compare the incidence of medication errors prior to the intervention and incidence of medication errors following the intervention.

i and ii) Specifically, the records inserted into the electronic health record system could be used for this purpose. The data would be discrete and nominal because all results are dealing with incidence and frequency of occurrence.

iii and iv) The purpose of this data would be to find a change. As a result, the student’s t-test would be an ideal statistical application because it would help refute the null hypothesis that there will be no change in medication errors prior to and following the implementation of the intervention. The confidence level should be 95% because it is important to understand if the change observed is a consequence of the intervention or as a consequence of pure change.

iv and v) Since this is an intervention study, it makes the most sense to compare data in this manner. The statistics will be parametric because the incidence of medication errors is assumed to be normal. However, this would have to be confirmed using data from the electronic health record system prior to the experiment. The data will be examined to determine if there is a different between the baseline group and the intervention group. This will determine if the intervention is effective. Statistical programs such as excel or SPSS will be used to conduct the analysis, even though the expected analysis will likely be basic.

The study was initially designed to be both qualitative and quantitative in nature, so aspects of the study will need to be refined for the quantitative format. It is valuable to conduct statistical tests to determine the overall change in data between the two groups, but since the project was originally designed to contain categorical data, it will be necessary to determine how this information could be assessed as well. It would therefore be valuable to sort different types of medication errors and determine their individual incidences prior to the experiment to determine whether the change in medication errors is true for each category as a consequence of the intervention. The same statistical tests can be conducted to determine whether there is a variance between these two groups, but conducting the tests on a smaller scale will allow the researcher to determine whether the intervention has a general or specific effect.

Since quantitative information is being used, it would also be valuable to determine more than one intervention that could be tested over a period of time to determine what the best alternative to solve this problem is. However, doing so would ensure that the testing period would be lengthy because it takes several months for a high number of medical errors to occur naturally. Therefore, while this is an interesting research perspective, it may not be feasible in terms of the time available for such a project. Thus, even though quantitative data is useful, this type of project would still benefit from a combination of quantitative and qualitative data to gain a more complete understanding of medication errors within the health care institution and related phenomena being studied in this situation. Quantitative data is valuable because it shows a trend, but qualitative data could be used to explain these trends (Leedy & Omrod, 2012).

References

Leedy PD, Omrod JE. (2012). Practical Research: Planning and Design (10th Edition). Pearson.