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Management of Diabetes Mellitus among Vulnerable Population – Hispanic Population

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Clinical Question and Intervention

The clinical question for this evidence-based practice project is as follows: “Is providing diabetes education and support through text messages combined with clinical support through phone calls effective in reducing HbA1c levels among Hispanic diabetes patients and enhancing patient satisfaction?” The planned intervention involves providing Hispanic diabetes patients with diabetes education and support through text messages in combination with telemedicine assistance from certified nurses participating in the intervention. The primary outcome for the intervention is the change in the HbA1c levels of participants, while the secondary outcomes include adherence to diabetes self-management practices and patient satisfaction. Based on evidence from research, sending text messages and offering clinical support through phone calls are effective in improving HbA1c levels and patient satisfaction among Hispanics diagnosed with diabetes (Philis-Timikas, Fortmann, Garcia, Ruiz, & Schultz, 2016; Arora, Peters, Burner, Lam, & Menchine, 2014). As such, it is expected that the intervention will result in a reduction in the HbA1c levels of the participants, will enable them to engage in diabetes self-management practices more and increase their satisfaction with the treatment plan.

Statistical Analysis

Different statistical tests will be used to analyze the data collected during the intervention. Since the intervention will not involve a comparison between two groups, univariate statistical tests will be used. HbA1c measurements will be collected four times in three-month intervals during the intervention after which the values will be compared for changes attributed to the proposed intervention. As such, the HbA1c levels will be analyzed using a univariate descriptive statistical test, particularly the measures of central tendency. Measures of central tendency include the mean, median, variance, and standard deviation. For the secondary outcomes, statistical analysis will be performed using the chi-square test to compare the actual frequency to the expected frequency of self-management practices among participants.

Statistical Analysis and Data Collection Tools

The above mentioned statistical analysis methods will be employed as they are the most appropriate for this kind of intervention and types of data collected. First, HbA1c results will be recorded only four times during the intervention and will be compared progressively to determine whether the intervention resulted in any change in the HbA1c values. As such, measures of central tendency are the most relevant in this regard since they will help to identify any changes in HbA1c levels of the study participants from baseline to the end of the intervention. Bi- and multivariate inferential statistical tests such as the chi-square, ANOVA, and t-tests are not effective in this regard as there is only one variable being studied (HbA1c levels) in the same group, with comparisons being conducted over time. Also, the information obtained from the analysis provides an answer to the clinical question in terms of the impact of the intervention on HbA1c levels. Obtaining information from the study participants collectively is also important in this project as its main aim is to determine the effect of the intervention on the target population rather than on individual patients.

The secondary outcomes of the intervention are qualitative in nature, as the data collected is mostly narrative. The questionnaires used to collect data will include closed-ended questions that seek responses on the frequency and extent to which a participant engages in various aspects of diabetes self-management practices such as proper nutrition, insulin administration, blood glucose monitoring, and symptom checks among others. For adherence to diabetes self-management practices, the questions will be formatted in Likert scales to assess the average frequency of a participant to engage in diabetes self-care actions. Likert scales will also be used to determine the extent of satisfaction of the participants, which will provide a more accurate answer to the clinical question.

Likert scales have been shown as highly effective in categorizing responses especially in qualitative analysis (Hartley, 2014). Also, patient satisfaction has been measured effectively using this type of scaling in several studies (Al Shabrani & Baraja, 2014; Hijat et al., 2011). In this case, the Likert scales will include five categories which rank the responses as follows:

1 – “Very dissatisfied”

2 – “Dissatisfied”

3 – “Neither satisfied nor dissatisfied”

4 – “Satisfied”

5 – “Very satisfied”

 The data obtained through the Likert scales will then be analyzed using the chi-square test to determine the difference between the expected and actual patient satisfaction scores.

Population Demographics and Expected Outcomes

The demographics that will be reported on the participants include the age, household income, highest level of education, occupation, and residence. The participants should be above 18 years, have a household income below the national poverty level, and live within the reach of the health centers involved in the intervention. This information is important for the intervention as it helps to identify the desired characteristics of the target population. The primary outcome of the intervention includes a reduction in the HbA1c levels of the participants as measured in intervals of three months from baseline up to nine months. Secondary outcomes involve increased adherence to routine diabetes self-management practices and enhanced patient satisfaction with the program.

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