Statistical Analysis: Recent Hypertensive Patients Essay (Critical Writing)

Brief description of the project

The purpose of this project is to assess hypertensive patients’ level of satisfaction with the provided service at outpatient clinics and the association with their medication adherence. The sample will incorporate adult patients older than 18 years attending the outpatient department for follow-up over the last six months. The study pursues two ultimate goals: to assess the hypertensive patients’ level of satisfaction and to establish the hypertensive patients’ level of adherence to antihypertensive medications. Statistical analysis will be used for getting the ultimate indicators.

First Objective: Prevalence of Newly Diagnosed Hypertensive Patients

• Type of variables: nominal;
• Type of test: Chi-Square;
• Type of chart: a histogram.

First of all, it is necessary to ascertain how relevant the problem of hypertension in the last six months is. For this objective, the nominal type of variables will be used. The subsequent variables are age and time of diagnosis.

The appropriate assumption is the null hypothesis that all patients are not related to each other in any way, thus they develop hypertension symptoms independently (Nahm, 2016). The subsequent statistical test is Chi-Square which answers the question of how the symptoms correlate with age. A histogram would be the best way of showcasing the category with the highest number of high blood pressure problems.

Second Objective: Perceived Level of Satisfaction among Male and Female Patients

• Type of variables: nominal;
• Type of test: T-test;
• Type of chart: a table.

The second objective is to assess the level of satisfaction that patients experience and how different it is between men and women. The nominal type of variables is the most appropriate in this case. Particularly, gender and marital status will serve as variables. There are two assumptions with the first one being a difference in the fundamental difference between male and female opinions. The second one is that married patients will have deeper satisfaction because of their partner’s psychological support.

The ultimate data will be discrete, with patients being either satisfied or dissatisfied, therefore, the T-test is used for this test. The resulting graphic representation is the table, which delineates patients’ satisfaction, gender, and marital status. The table works better than a graph because it allows writing down the specific numbers of patients who are married and satisfied or vice versa.

Third Objective: Level of Adherence to Antihypertensive Medications

• Type of variables: nominal;
• Type of test: Chi-Square;
• Type of chart: histogram.

Thirdly, it is necessary to ascertain how correct the patients are in following the medication regime. For this objective, the nominal type of variables will be used. Specifically, the time of diagnosis and type of medications will help pinpoint how consistently patients take the medications. This statistical objective assumes that all medications have an effect provided the regime is followed thoroughly. Chi-Square will serve as a statistical test with two histograms representing the results – one for monotherapy, the other for polytherapy.

Impact of Level of Support on Antihypertensive Medication Adherence

• Type of variables: nominal;
• Type of test: T-test;
• Type of chart: table.

Finally, it should be established how patients themselves support the treatment with antihypertensive medication. Nominal variables will be analyzed. The variables are income, level of education, monotherapy, and polytherapy. The overlaying assumption is that the more patients are educated and financially secure, the more they support using the medications.

It is also assumed that monotherapy and polytherapy receive different attitudes. The statistical approach would entail using a T-test, which would show how the level of education and income relates to support of antihypertensive medication. The graphical representation would constitute a table with four columns, one for the level of support, level of education, income, and the type of medication respectively.

Reference

Nahm, F. S. (2016). Nonparametric statistical tests for the continuous data: The basic concept and the practical use. Korean Journal of Anesthesiology, 69(1), 8-14. Web.