WEEK 3 replies

Olga Benitez Perez

11/13/24, 9:18 AM 

NEW

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Evidence-Based Practice: Insights, Strategies, and Recommendations

November 13, 2024

Insights

From my literature review on the topic of digital health education to improve medication adherence in middle-aged diabetes patients, several unexpected and noteworthy findings have emerged. Huang et al. (2019) demonstrated that smartphone-based interventions significantly improved medication adherence by providing tailored support and reducing adherence barriers. This finding is striking because traditional interventions often rely on static, paper-based education, which fails to address the dynamic needs of patients, resulting in minimal engagement. Encouraging the healthcare system to integrate smartphone-based technology could prevent many patients from experiencing disease progression due to non-adherence, highlighting a critical need for more interactive, personalized interventions.

Likewise, Shaban et al. (2024) proved that digital health education could enhance diabetes self-care knowledge and self-efficacy scores. This finding challenges the assumption that patients with low health literacy struggle with digital tools. Instead, it reveals that patients facing literacy barriers can experience improved self-management outcomes with the proper support and tailored content. This sheds light on a significant gap in how educational materials are traditionally delivered to patients and suggests a shift toward digital, interactive approaches that engage users effectively.

Additionally, Rai et al. (2023) showed that smartphone platforms contributed to clinically meaningful reductions in HbA1c levels for veterans with uncontrolled diabetes. This finding was surprising because it directly counters the belief that technological interventions may be less effective in older or resistant patient populations. This study emphasizes the need for healthcare providers to reconsider biases around digital tools and their potential for widespread application by demonstrating tangible improvements.

In this sense, clinicians can more effectively bridge gaps in traditional care approaches by tailoring technology-based solutions to these populations' unique needs and challenges. Additionally, integrating patient values and preferences ensures that interventions remain relevant and culturally sensitive (Cipta et al., 2024). At Vida Health Care and other settings, embedding these strategies into current care frameworks could promote seamless and more accessible adoption, enhance patient trust, and drive sustained behavioral change.

Strategies

To effectively implement EBP, I formulated a straightforward, focused clinical question using the PICOT framework (Population, Intervention, Comparison, Outcome, and Time). This step ensures the inquiry is specific and relevant, providing direction for the evidence-gathering process.

Next, during the "Acquire" phase, I prioritize databases such as PubMed, CINAHL, and the Cochrane Library, which offer access to peer-reviewed articles, systematic reviews, and meta-analyses. For example, studies like Huang et al. (2019), Shaban et al. (2024), Rai et al. (2023), and Johnson et al. (2023) demonstrated the impact of smartphone-based tools using sound methodology, providing strong evidence that informed my approach.

In the "Appraise" step, I utilize appraisal tools such as the Critical Appraisal Skills Programme (CASP) checklists to critically assess study design, sample size, biases, and outcomes. As part of this process, I also incorporate patient preferences and values by engaging with patients to understand their unique needs, barriers, and cultural contexts. This ensures that the evidence I select aligns with patient-reported outcomes, enhancing the relevance and effectiveness of interventions. For example, in appraising studies like Shaban et al. (2024), I examine how digital interventions improve self-care behaviors and how they consider patients' lived experiences and preferences.

In the "Apply" phase, I translate the evidence into practice by integrating it with clinical expertise and my patient's specific values and preferences. This alignment ensures that interventions are scientifically supported while remaining tailored to meet individual patient needs and circumstances. In my project, integrating digital health education requires balancing research evidence, my professional knowledge, and the unique needs of middle-aged diabetes patients at Vida Health Care.

Finally, the "Assess/Audit" step involves evaluating the effectiveness of the implemented practice by analyzing patient outcomes, identifying adherence gaps, and gathering feedback to better understand patient experiences, needs, and cultural contexts (Cipta et al., 2024). This continuous improvement loop not only refines practice but also reinforces the holistic nature of EBP, ensuring that interventions are consistently aligned with evolving evidence, clinical expertise, and patient-centered care.

Recommendations

I recommend that my peers identify high-quality and relevant sources to support their projects, ensuring they are reliable, up-to-date, and based on solid scientific evidence (Paré & Kitsiou, 2023). For example, we can all include sources such as the Centers for Disease Control and Prevention (CDC) because they provide extensive, peer-reviewed, and up-to-date data on a wide range of public health topics. These sources are foundational to EBP due to their rigorous data collection and analysis processes, making them highly credible and authoritative.

Similarly, I believe that including quantitative studies is more appropriate because they provide measurable and statistically significant results, making it easier to interpret and apply findings to practice (Leung, 2021). These studies serve as reliable sources of EBP because they offer concrete data that can be used to make informed decisions, evaluate intervention effectiveness, and generate recommendations grounded in objective outcomes.

References

Cipta, D. A., Andoko, D., Theja, A., Utama, A. V. E., Hendrik, H., William, D. G., Reina, N., Handoko, M. T., & Lumbuun, N. (2024). Culturally sensitive patient-centered healthcare: a focus on health behavior modification in low and middle-income nations-insights from Indonesia.  Frontiers in medicine,  11, 1353037. https://doi.org/10.3389/fmed.2024.1353037

Huang, Z., Tan, E., Lum, E., Sloot, P., Boehm, B. O., & Car, J. (2019). A Smartphone App to Improve Medication Adherence in Patients With Type 2 Diabetes in Asia: Feasibility Randomized Controlled Trial.  JMIR mHealth and uHealth,  7(9), e14914. https://doi.org/10.2196/14914

Johnson, C. M., D'Eramo Melkus, G., Reagan, L., Pan, W., Amarasekara, S., Pereira, K., Hassell, N., Nowlin, S., & Vorderstrasse, A. (2023). Learning in a Virtual Environment to Improve Type 2 Diabetes Outcomes: Randomized Controlled Trial.  JMIR formative research,  7, e40359. https://doi.org/10.2196/40359

Leung L. (2021). Validity, reliability, and generalizability in qualitative research.  Journal of family medicine and primary care,  4(3), 324–327. https://doi.org/10.4103/2249-4863.161306

Paré, G., & Kitsiou, S. (2023). Chapter 9: Methods for literature reviews. In F. Lau & C. Kuziemsky (Eds.), Handbook of eHealth evaluation: An evidence-based approach [Internet]. University of Victoria. Available from https://www.ncbi.nlm.nih.gov/books/NBK481583/

Rai, A., Riddle, M., Mishra, R., Nguyen, N., Valine, K., & Fenney, M. (2023). Use of a Smartphone-Based Medication Adherence Platform to Improve Outcomes in Uncontrolled Type 2 Diabetes Among Veterans: Prospective Case-Crossover Study.  JMIR diabetes,  8, e44297. https://doi.org/10.2196/44297

Shaban, M. M., Sharaa, H. M., Amer, F. G. M., & Shaban, M. (2024). Effect of digital based nursing intervention on knowledge of self-care behaviors and self-efficacy of adult clients with diabetes.  BMC nursing,  23(1), 130. https://doi.org/10.1186/s12912-024-01787-2

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Olga Benitez Perez

11/13/24, 9:18 AM 

NEW

Top of Form

Evidence-Based Practice: Insights, Strategies, and Recommendations

November 13, 2024

Insights

From my literature review on the topic of digital health education to improve medication adherence in middle-aged diabetes patients, several unexpected and noteworthy findings have emerged. Huang et al. (2019) demonstrated that smartphone-based interventions significantly improved medication adherence by providing tailored support and reducing adherence barriers. This finding is striking because traditional interventions often rely on static, paper-based education, which fails to address the dynamic needs of patients, resulting in minimal engagement. Encouraging the healthcare system to integrate smartphone-based technology could prevent many patients from experiencing disease progression due to non-adherence, highlighting a critical need for more interactive, personalized interventions.

Likewise, Shaban et al. (2024) proved that digital health education could enhance diabetes self-care knowledge and self-efficacy scores. This finding challenges the assumption that patients with low health literacy struggle with digital tools. Instead, it reveals that patients facing literacy barriers can experience improved self-management outcomes with the proper support and tailored content. This sheds light on a significant gap in how educational materials are traditionally delivered to patients and suggests a shift toward digital, interactive approaches that engage users effectively.

Additionally, Rai et al. (2023) showed that smartphone platforms contributed to clinically meaningful reductions in HbA1c levels for veterans with uncontrolled diabetes. This finding was surprising because it directly counters the belief that technological interventions may be less effective in older or resistant patient populations. This study emphasizes the need for healthcare providers to reconsider biases around digital tools and their potential for widespread application by demonstrating tangible improvements.

In this sense, clinicians can more effectively bridge gaps in traditional care approaches by tailoring technology-based solutions to these populations' unique needs and challenges. Additionally, integrating patient values and preferences ensures that interventions remain relevant and culturally sensitive (Cipta et al., 2024). At Vida Health Care and other settings, embedding these strategies into current care frameworks could promote seamless and more accessible adoption, enhance patient trust, and drive sustained behavioral change.

Strategies

To effectively implement EBP, I formulated a straightforward, focused clinical question using the PICOT framework (Population, Intervention, Comparison, Outcome, and Time). This step ensures the inquiry is specific and relevant, providing direction for the evidence-gathering process.

Next, during the "Acquire" phase, I prioritize databases such as PubMed, CINAHL, and the Cochrane Library, which offer access to peer-reviewed articles, systematic reviews, and meta-analyses. For example, studies like Huang et al. (2019), Shaban et al. (2024), Rai et al. (2023), and Johnson et al. (2023) demonstrated the impact of smartphone-based tools using sound methodology, providing strong evidence that informed my approach.

In the "Appraise" step, I utilize appraisal tools such as the Critical Appraisal Skills Programme (CASP) checklists to critically assess study design, sample size, biases, and outcomes. As part of this process, I also incorporate patient preferences and values by engaging with patients to understand their unique needs, barriers, and cultural contexts. This ensures that the evidence I select aligns with patient-reported outcomes, enhancing the relevance and effectiveness of interventions. For example, in appraising studies like Shaban et al. (2024), I examine how digital interventions improve self-care behaviors and how they consider patients' lived experiences and preferences.

In the "Apply" phase, I translate the evidence into practice by integrating it with clinical expertise and my patient's specific values and preferences. This alignment ensures that interventions are scientifically supported while remaining tailored to meet individual patient needs and circumstances. In my project, integrating digital health education requires balancing research evidence, my professional knowledge, and the unique needs of middle-aged diabetes patients at Vida Health Care.

Finally, the "Assess/Audit" step involves evaluating the effectiveness of the implemented practice by analyzing patient outcomes, identifying adherence gaps, and gathering feedback to better understand patient experiences, needs, and cultural contexts (Cipta et al., 2024). This continuous improvement loop not only refines practice but also reinforces the holistic nature of EBP, ensuring that interventions are consistently aligned with evolving evidence, clinical expertise, and patient-centered care.

Recommendations

I recommend that my peers identify high-quality and relevant sources to support their projects, ensuring they are reliable, up-to-date, and based on solid scientific evidence (Paré & Kitsiou, 2023). For example, we can all include sources such as the Centers for Disease Control and Prevention (CDC) because they provide extensive, peer-reviewed, and up-to-date data on a wide range of public health topics. These sources are foundational to EBP due to their rigorous data collection and analysis processes, making them highly credible and authoritative.

Similarly, I believe that including quantitative studies is more appropriate because they provide measurable and statistically significant results, making it easier to interpret and apply findings to practice (Leung, 2021). These studies serve as reliable sources of EBP because they offer concrete data that can be used to make informed decisions, evaluate intervention effectiveness, and generate recommendations grounded in objective outcomes.

References

Cipta, D. A., Andoko, D., Theja, A., Utama, A. V. E., Hendrik, H., William, D. G., Reina, N., Handoko, M. T., & Lumbuun, N. (2024). Culturally sensitive patient-centered healthcare: a focus on health behavior modification in low and middle-income nations-insights from Indonesia.  Frontiers in medicine,  11, 1353037. https://doi.org/10.3389/fmed.2024.1353037

Huang, Z., Tan, E., Lum, E., Sloot, P., Boehm, B. O., & Car, J. (2019). A Smartphone App to Improve Medication Adherence in Patients With Type 2 Diabetes in Asia: Feasibility Randomized Controlled Trial.  JMIR mHealth and uHealth,  7(9), e14914. https://doi.org/10.2196/14914

Johnson, C. M., D'Eramo Melkus, G., Reagan, L., Pan, W., Amarasekara, S., Pereira, K., Hassell, N., Nowlin, S., & Vorderstrasse, A. (2023). Learning in a Virtual Environment to Improve Type 2 Diabetes Outcomes: Randomized Controlled Trial.  JMIR formative research,  7, e40359. https://doi.org/10.2196/40359

Leung L. (2021). Validity, reliability, and generalizability in qualitative research.  Journal of family medicine and primary care,  4(3), 324–327. https://doi.org/10.4103/2249-4863.161306

Paré, G., & Kitsiou, S. (2023). Chapter 9: Methods for literature reviews. In F. Lau & C. Kuziemsky (Eds.), Handbook of eHealth evaluation: An evidence-based approach [Internet]. University of Victoria. Available from https://www.ncbi.nlm.nih.gov/books/NBK481583/

Rai, A., Riddle, M., Mishra, R., Nguyen, N., Valine, K., & Fenney, M. (2023). Use of a Smartphone-Based Medication Adherence Platform to Improve Outcomes in Uncontrolled Type 2 Diabetes Among Veterans: Prospective Case-Crossover Study.  JMIR diabetes,  8, e44297. https://doi.org/10.2196/44297

Shaban, M. M., Sharaa, H. M., Amer, F. G. M., & Shaban, M. (2024). Effect of digital based nursing intervention on knowledge of self-care behaviors and self-efficacy of adult clients with diabetes.  BMC nursing,  23(1), 130. https://doi.org/10.1186/s12912-024-01787-2

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