Propose an evidence-based plan to improve the outcomes for your diagnosis

The paper outlines an evidence-based approach to improving medication adherence in adults with Type 2 Diabetes Mellitus (T2DM) using the Johns Hopkins Nursing Evidence-Based Practice (JHNEBP) model. It emphasizes structured interventions, including nurse-led education, behavioral techniques, and follow-up strategies, to enhance adherence and glycemic control. Key findings highlight the effectiveness of personalized, systematic approaches over generic education, supported by credible research. The proposed care plan involves patient assessment, tailored education, structured follow-ups, adherence tools, and interdisciplinary coordination to sustain long-term benefits while acknowledging implementation challenges. Also, we have written an extra video script sample at the bottom for your study referencing.

Create a 5–10 minute video of yourself, as a presenter, in which you propose an evidence-based plan to improve the outcomes for your diagnosis.

Introduction

As part of the critical role that EBP plays in nursing, professional nurses share their findings with their peers and others. A big part of research is sharing knowledge so that others can also learn. Professional nurses attend seminars and read journals specific to their practice, and they also publish and present what they have learned. This assessment prepares you to share your knowledge with others.

Instructions

For this assessment, you are a presenter! You will create a 5–10 minute video using Kaltura or similar software. In the video and written narrative:

• Review your findings from Assessment 3.
• Create a poster presentation based on your findings from Assessment 3 (see the samples in the Assessment 4: Poster Template Examples reading list). Include:
  • An explanation of the diagnosis.
  • The research question you developed using PICO(T).
  • A summary of your sources.
  • The answer to your PICO(T) question based on your analysis of evidence.
• Describe the key steps of care you are recommending based on your evidence.
• Give a professional presentation to your peers, showing your poster with your voice narration using Kaltura or similar software.
• Include your written narrative/script of the presentation in a Word document. Add the link to your video at the end of your written narrative.

Refer to Using Kaltura Campus resource as needed to record and upload your video.

Note: If you require the use of assistive technology or alternative communication methods to participate in this activity, please contact DisabilityServices@Capella.edu to request accommodations. If, for some reason, you are unable to record a video, please contact your faculty as soon as possible to explore options for completing the assessment.

Additional Requirements

Your assessment should also meet the following requirements:

• Length of video: 5–10 minutes.
• References: Cite at least three professional or scholarly sources of evidence to support the assertions you make in your video. Include additional properly cited references as necessary to support your statements.
• APA reference page: Submit a correctly formatted APA reference page that shows all the sources you used to create and deliver your video. Be sure to format the reference page according to current APA style.
• Video and narrative: You must submit a written narrative of all of your video content. Add the link to your video at the end of your written narrative.

Competencies Measured

By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and scoring guide criteria:

• Competency 2: Analyze the relevance and potential effectiveness of evidence when making a decision.
  • Explain a diagnosis in terms of outcomes, risks, and complications.
  • Summarize the content of at least three sources of evidence, including the credibility and relevance of the articles to a specific diagnosis issue.
• Competency 4: Plan care based on the best available evidence.
  • Describe a research question developed using the PICO(T) process to address a chosen issue related to a diagnosis.
  • Explain the answer to a PICO(T) question based on an analysis of the evidence.
  • Describe key steps of care based on the evidence.
• Competency 5: Apply professional, scholarly communication strategies to lead practice changes based on evidence.
  • Organize content in a poster presentation and written narrative so ideas flow logically with smooth transitions; contains few errors in grammar/punctuation, word choice, and spelling.
  • Communicate effectively in a professional audiovisual presentation with clear light and sound.
  • Apply APA formatting to in-text citations and references, exhibiting adherence to most aspects of APA format.

Scoring Guide

Use the scoring guide to understand how your assessment will be evaluated.

Criterion 1

Explain a diagnosis in terms of outcomes, risks, and complications.

Distinguished

Explains a diagnosis in terms of outcomes, risks, and complications, providing examples.

Proficient

Explains a diagnosis in terms of outcomes, risks, and complications.

Basic

Explains a diagnosis, but may not fully cover outcomes, risks, and complications in the explanation.

Non Performance

Does not explain a diagnosis in terms of outcomes, risks, and complications.

Criterion 2

Describe a research question developed using the PICO(T) process to address a chosen issue related to a diagnosis.

Distinguished

Describes a research question developed using the PICO(T) process to address a chosen issue related to a diagnosis, and identifies how the question meets each of the criteria of the PICO(T) process.

Criterion 3

Summarize the content of at least three sources of evidence, including the credibility and relevance of the articles to a specific diagnosis issue.

Distinguished

Summarizes the content of more than three sources of evidence, including the credibility and relevance of the articles to a specific diagnosis issue.

Proficient

Summarizes the content of at least three sources of evidence, including the credibility and relevance of the articles to a specific diagnosis issue.

Criterion 4

Explain the answer to a PICO(T) question based on an analysis of the evidence.

Distinguished

Explains the answer to a PICO(T) question based on an analysis of the evidence, identifying assumptions on which the analysis is based.

Proficient

Explains the answer to a PICO(T) question based on an analysis of the evidence.

Criterion 5

Describe key steps of care based on the evidence.

Distinguished

Describes key steps of care based on the evidence, and explains why these are the most appropriate steps.

Organize content in a poster presentation and written narrative so ideas flow logically with smooth transitions; contains few errors in grammar/punctuation, word choice, and spelling.

Criterion 7

Communicate effectively in a professional audiovisual presentation with clear light and sound.

Distinguished

Communicates effectively in a professional audiovisual presentation with clear light and sound. Content delivery is focused, smooth, and well-rehearsed. Video presentation is between 5 and 10 minutes.

Criterion 8

Apply APA formatting to in-text citations and references, exhibiting adherence to most aspects of APA format.

Distinguished

Exhibits adherence to most aspects of APA formatting of headings, in-text citations, and references. Correctly uses quotes and paraphrasing.

Applying the Johns Hopkins Nursing EBP Model to Improve Medication Adherence in Adults with Type 2 Diabetes Mellitus

Some problems in health care are stubborn, not because solutions are unknown, but because the path from evidence to bedside is bumpy. Medication adherence in adults with Type 2 Diabetes Mellitus (T2DM) is one of them. The science behind the benefits of consistent pharmacologic control is solid—glycemic stability reduces microvascular and macrovascular complications, delays disease progression, and improves quality of life (Davies et al., 2022). Yet adherence rates in many primary care and community settings hover around 60–70%. The gap is not purely a patient problem; it is often a systems problem. That is where structured evidence-based practice frameworks such as the Johns Hopkins Nursing Evidence-Based Practice (JHNEBP) model become more than a theoretical construct—they serve as a practical scaffolding for changing actual care delivery.

The JHNEBP model is not about replacing professional judgment with checklists. It is about organising thinking so that clinical questions are precise, the evidence sought is relevant, and implementation steps are deliberate. It revolves around three interdependent phases: Practice question, Evidence, and Translation (PET). In the case of T2DM medication adherence, the practice question phase is where a well-defined PICO(T) structure can set the tone for targeted inquiry.

For this scenario, the PICO(T) question reads:
In adults aged 18 years and older diagnosed with Type 2 Diabetes Mellitus (P), how does implementing nurse-led medication adherence interventions guided by the JHNEBP model (I) compared to standard educational approaches without a structured EBP model (C) affect adherence rates as measured by validated adherence scales or pharmacy refill data (O) over six months (T)?

That may sound like an academic exercise, but its precision forces a discipline: the “population” is not just ‘patients with diabetes’ but adults with T2DM; the “intervention” is not just ‘education’ but nurse-led, EBP-model-guided strategies; the “comparison” is explicit; the “outcome” is quantifiable; the “time” frame is clear. That makes the literature search phase more efficient and the results more actionable.

Evidence on this topic is not scarce. For example, Al-Alawi et al. (2022) evaluated multi-component nurse-led interventions—ranging from motivational interviewing to medication reminders—and found significant improvements in adherence rates and HbA1c reduction over six months. What is notable in such studies is not just that interventions work, but that their success depends on consistent delivery and contextual adaptation—precisely the translation step in JHNEBP. Similarly, a systematic review by Khunti et al. (2021) showed that structured educational and behavioural strategies tailored to patient readiness and literacy levels improved adherence, but warned that without sustained follow-up, gains faded within a year.

The credibility of these sources rests not only on their peer-reviewed status but also on methodological rigour—randomised controlled trials and high-quality systematic reviews offer stronger causal inference than observational reports. They also align directly with the diagnosis issue: they measure adherence using validated tools such as the Morisky Medication Adherence Scale (MMAS-8) and link adherence to clinical outcomes like HbA1c, not just self-reported behaviour.

Now, analysing the evidence through the JHNEBP lens changes the conversation. The model pushes us to ask: is the evidence strong enough, consistent enough, and applicable to our setting? The answer here is yes, but with caveats. Studies repeatedly show that nurse-led, structured interventions work, yet implementation barriers include staffing capacity, training gaps, and competing priorities in primary care. Translation in the JHNEBP model is not just about “rolling out” an intervention; it is about embedding it in a workflow so it survives beyond pilot enthusiasm.

From the synthesis, the answer to the PICO(T) question is clear: nurse-led adherence interventions grounded in a structured EBP framework like JHNEBP outperform generic education in improving short-term adherence in adults with T2DM. However, the sustainability of these gains depends on how well the intervention is tailored to patient context and how systematically it is integrated into ongoing care.

The key steps of care, therefore, follow logically from the evidence but also respect the operational realities of practice:

1. Patient Assessment Using a Standard Tool
   Before delivering any adherence intervention, nurses should assess baseline adherence and potential barriers using validated scales (e.g., MMAS-8) combined with a brief psychosocial screening. This step, supported by evidence from Ng et al. (2020), ensures interventions address actual barriers rather than presumed ones.

2. Individualised Education Anchored in Behavioural Techniques
   Instead of generic medication instructions, education sessions should incorporate motivational interviewing, teach-back methods, and goal-setting, as demonstrated effective in multiple trials (Khunti et al., 2021). This personalisation aligns with the evidence and enhances retention.

3. Structured Follow-up and Reinforcement
   Adherence is a behaviour, and behaviours decay without reinforcement. Monthly follow-up calls or visits in the first six months, guided by structured protocols, were shown in Al-Alawi et al. (2022) to sustain adherence gains.

4. Medication Adherence Support Tools
   Depending on patient preference and access, tools may include pillboxes, mobile reminders, or pharmacy refill synchronization. Technology is not a panacea, but in several studies, its adjunct use added measurable adherence improvements (Ng et al., 2020).

5. Interdisciplinary Coordination
   The nurse is central in delivering the intervention, but coordination with pharmacists, dietitians, and primary care physicians ensures messages are consistent and support is reinforced at multiple points of contact.

The rationale for these steps is simple: they are the points where evidence is strongest and most adaptable to diverse care environments. They also map neatly to the PET stages in JHNEBP—practice question defines the target; evidence supports the tools; translation embeds the steps into routine care.

Still, the application of JHNEBP here is not mechanical. For example, during translation, local adaptation might require modifying educational materials for linguistic diversity or integrating adherence checks into existing chronic disease visits to avoid patient fatigue. These adaptations do not dilute the model; they honour it by respecting context, which is one of its implicit strengths.

The broader implication of using JHNEBP for this problem is cultural. Nurses who consistently apply EBP frameworks start to see clinical decisions less as isolated acts and more as parts of a feedback loop: question, evidence, action, evaluation, revision. That loop not only improves adherence; it subtly shifts team dynamics towards more reflective practice.

Of course, evidence has limits. Most high-quality studies in this area are relatively short-term; few extend beyond 12 months, so long-term sustainability is an open question. There is also the perennial challenge of measuring adherence accurately—self-report is prone to bias, and refill data, while objective, does not guarantee ingestion. These limitations should temper overconfidence and remind practitioners to maintain ongoing evaluation as part of the intervention.

In sum, the JHNEBP model offers more than a tidy acronym for improving medication adherence in T2DM. It provides a mental discipline for moving from “we know adherence is a problem” to “here is a precise question, here is strong evidence, here is how we integrate it into care so it sticks.” When done well, it changes not just patient outcomes, but the way care teams think about problem-solving. And that shift—though harder to measure—might be its most enduring effect.

References

• Al-Alawi, N., Al Mandhari, A., Al Rawahi, N., Al-Busaidi, Z., and Patel, A. (2022) ‘Effectiveness of nurse-led interventions on medication adherence among adults with type 2 diabetes: A randomized controlled trial’, Journal of Diabetes Nursing, 26(3), pp. 102-112.

• Davies, M. J., D’Alessio, D. A., Fradkin, J., Kernan, W. N., Mathieu, C., Mingrone, G., Rossing, P., Tsapas, A., Wexler, D. J. and Buse, J. B. (2022) ‘Management of hyperglycemia in type 2 diabetes, 2022: A consensus report by the American Diabetes Association and the European Association for the Study of Diabetes’, Diabetologia, 65(12), pp. 1925-1966.

• Khunti, K., Gomes, M. B., Pocock, S., Shestakova, M. V., Pintat, S., Fenici, P., Hammar, N., Medina, J., Surmont, F., Kosiborod, M. and Nicolucci, A. (2021) ‘Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: A systematic review’, Diabetes essay examples, Obesity and Metabolism research paper, 23(1), pp. 103-119.

• Ng, S. M., Lee, J. Y. C., Toh, M. P. H. S., Ko, Y. and Tan, A. S. L. (2020) ‘Medication adherence and glycemic control among newly diagnosed diabetes patients’, Primary Care Diabetes, 14(4), pp. 405-412.

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Sample Video Script;

Remote Telemonitoring as a Lifeline for Chronic Heart Failure: Cutting Readmissions with Evidence

How remote telemonitoring, supported by recent meta-analyses, can lower mortality and readmissions in chronic heart failure patients.

Good morning, colleagues. I’m standing here today with a poster that lays out an evidence-based plan for tackling chronic heart failure, a condition that keeps landing patients back in our wards far too often. Let’s get straight into it, because I know you’re all busy and skeptical about yet another pitch on tech in nursing.

Chronic heart failure sneaks up on people, often after years of hypertension or coronary issues, leading to weakened pumping and fluid buildup. Patients face grim outcomes: about half die within five years of diagnosis, and readmission rates hover around 20-25% within 30 days post-discharge. Risks include sudden decompensation from non-adherence or undetected weight gain signaling fluid retention. Complications? Think acute kidney injury from over-diuresis or pulmonary edema that escalates quickly without intervention. Still, many patients manage at home until things spiral.

To address this, I framed a research question using the PICO(T) process: In adults with chronic heart failure (P), does remote telemonitoring (I) compared to standard outpatient care (C) reduce hospital readmissions (O) over 12 months (T)? This hits all PICO(T) elements—population specified, intervention clear, comparison realistic, outcome measurable, and time-bound for practicality.

I dug into three solid sources to answer this. First, a 2024 meta-analysis by Castaldo and colleagues reviewed 61 studies on telehealth in heart failure, finding telemonitoring cut one-year all-cause mortality by 16% and first hospitalizations by 19%. They pooled data from over 36,000 patients, emphasizing non-invasive monitoring like daily weight and blood pressure uploads. Credible? Absolutely—published in Heart & Lung, peer-reviewed, with low heterogeneity in key results. Relevant because it directly ties to readmission reductions through early alerts.

Next, Klersy et al.’s 2023 meta-analysis in the European Heart Journal crunched 92 studies, showing similar gains: 16% drop in mortality, 19% in first heart failure admissions, and 15% in total ones. They included both randomized trials and observational data up to 2022, with strong statistical power. The credibility shines through rigorous bias assessment, and it’s spot-on for our diagnosis, highlighting how monitoring vital signs prevents escalations.

Then there’s Adekunle et al. in 2022, a systematic review in the World Journal of Cardiology analyzing 38 trials with nearly 15,000 patients. They reported 17% lower all-cause mortality and 34% less cardiovascular death with telemonitoring. Published peer-reviewed, it focuses on digital transmissions, making it highly relevant for evidence-based shifts in care.

Based on this analysis, the answer to my PICO(T) question is yes—telemonitoring does reduce readmissions over 12 months. The pooled odds ratios across these sources consistently show 15-20% reductions, assuming we implement it thoughtfully. To be fair, some variability exists; shorter programs (under six months) show weaker effects, and patient buy-in matters. But the evidence holds when programs monitor multiple parameters like weight, heart rate, and symptoms.

So, what does this mean for a plan? My proposed steps build directly on the evidence. Start with patient selection and education right at discharge. Target those with recent admissions or NYHA class II-III, teaching them to use simple devices—Bluetooth scales, blood pressure cuffs, pulse oximeters. They transmit data daily via apps or hubs, no fancy setup needed. Nurses review uploads in real-time, flagging anomalies like a 2kg weight gain or systolic drop below 90mmHg. Consequently, we intervene early: adjust diuretics over phone, schedule urgent visits, or reinforce diet adherence.

Furthermore, integrate multidisciplinary input. Cardiologists tweak meds based on trends, while dietitians address sodium intake via virtual check-ins. Evidence from the meta-analyses shows this cuts readmissions by catching decompensation before ER visits. For instance, in nursing home settings, similar monitoring dropped 30-day readmits by over 25%, per integrative reviews.

Monitoring duration? At least 12 months, as shorter spans dilute benefits. Track adherence with app logs, and loop in family for support. Costs? Initial setup around $200 per patient, but savings from averted admissions—averaging $15,000 each—pay off quickly. Nonetheless, challenges like tech literacy persist; pair older patients with simplified interfaces or in-person demos.

In some ways, this reframes heart failure care from reactive to proactive. Imagine a patient like Mr. Jones, 72, post-MI with ejection fraction at 35%. Without monitoring, he misses subtle swelling, lands back in hospital. With it, his nurse spots the trend, ups furosemide, averts crisis. That’s the texture of real impact—lived stability over repeated chaos.

To wrap up, this plan leverages telemonitoring to slash readmissions, backed by robust data. Implementing it could transform outcomes, easing burdens on patients and systems alike. Thanks for listening; questions?

References

Adekunle, R.O., Irwin, R.B., Selvarajah, A., Ali, R., Bolger, A. and Siddiqui, S. (2022) Telemonitoring in heart failure patients: Systematic review and meta-analysis of randomized controlled trials. World Journal of Cardiology, 14(12), pp.626-640.

Castaldo, R., Montesinos, L., Wan, T.S., Serban, A., Paci, M. and Pecchia, L. (2024) Telehealth care and remote monitoring strategies in heart failure patients: A systematic review and meta-analysis. Heart & Lung, 64, pp.165-178.

Klersy, C., De Silvestri, A., Gabutti, G., Regoli, F. and Auricchio, A. (2023) Telemonitoring in heart failure patients: A meta-analysis. European Heart Journal, 44(31), pp.2911-2926.