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Journal Of Evaluation In Clinical Practice

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While searching research article specific to the research questions, it is important to use specific search terms so that search process is defined and appropriate article with the search term is retrieved. Use of keywords in electronic databases provides specificity to the search. These key words indicate the topic, which the database is able to retrieve after matching it with entered key words (Shariff et al. 2013).
There are various models that aids a nurse in clinical judgment. The Tanner’s model of clinical judgment and the evidence based practice framework are two relevant models to support nurse in clinical judgment during practice. Tanner’s model of clinical judgment proposes following the stage of recalling patient situation, noticing, interpreting, responding and reflection-on-action to engage in clinical learning and develop professionally in their career. This helps to analyze the biasness, ethical perspective, level of knowledge or experience in conducting a clinical task. This is a kind of self-assessment to judge clinical scenario and provide effective care to patients (Mariani et al. 2013). On the other hand, evidence based practices enables nurse to improve their clinical skills by integrating research evidence in nursing practice. This provide an extended role in which the Tanner’s model helps to identify the limitation in skills of nurses and the evidence based practice framework provides the opportunity to implement best practice by the application of best evidence in daily practice (Melnyk and Fineout-Overholt 2011).
Randomized controlled trial is the highest level of evidence, which aims to determine the cause-effect relationship between an intervention and outcome. The main advantage is that it reduces biasness in the study by means of the randomization process. On the contrary, the purpose of systematic review is to present the main findings of different research literature to identify the effectiveness of interventions. It is a means to summarize and appraise the research articles (Olivo et al. 2008).
The main of the research study was to examine the impact of telemonitoring based service design for the management of uncontrolled hypertension in patients. Research in this area was considered important due to the poor outcome seen from routine clinical procedure for hypertension treatment. This happened mainly due to infrequent monitoring of blood pressure by patients, poor treatment adherence and reluctance by doctors to intensify treatment. Hence, use of randomized controlled trial will help to evaluate the effect of intervention on health outcome.
The primary outcome for the study include mean daytime ambulatory systolic blood pressure six months after the intervention and secondary outcome include both the daytime ambulatory systolic and diastolic blood pressure. Other indicators of secondary outcome measures included adherence to drugs, cholesterol level of patients, exercise tolerance and health related quality of life (McKinstry et al. 2013).
In the study by McKinstry et al. (2013), participants were asked to self-measure their blood pressure twice every morning and evening by means of telemonitoring equipment. Through this means, the device could automatically transmit reading to mobile phones. Participants could share the feedback of blood pressure to other clinicians.
The sample size of 400 participants is adequate for the study because the researcher utilized statistical method to estimate the sample size requirement for the study. This consideration wass based on study design and by means of calculation regarding appropriate size that could help to identify difference between telemonitoring and usual care (Zhong 2011).
Post 6 months of intervention, the mean difference in daytime systolic ambulatory blood pressure between telemonitoring and usual care group was 4.3 mm Hg (95% confidence interval 2.0 to 6.5). This data tells that difference between blood pressure reading for telemonitoring and usual care arm. As the blood pressure fell between both group, the mean daytime systolic blood pressure revealed the difference for the two arms. On the other hand, 95% confidence interval means that of 100 different samples are taken, about 95 of the 100 confidence interval will contain the true mean value. Hence, the mean value within 95% confidence interval will lie between 2.0 to 6.5 and the value will fluctuate between this value.
The p value for the mean difference in daytime systolic ambulatory blood pressure between telemonitoring and usual care group was 0.0002. The p value is the probability of finding the observed results when the null hypothesis of a research question is true. In this study, null hypothesis means no difference between blood pressure between two groups. P-value of 0.0002 reveal a statistically high significant.
In case of telemonitoring group, the mean daytime ambulatory diastolic blood pressure fell from 87.4 mm Hg to 83.4 mm Hg. The difference in mean value for intervention and control group was 2.3 mm Hg. Although there was no difference in secondary outcome for both grpup, however telemonitoring was effective in lowering the blood pressure.
The randomized controlled trial study in patients with uncontrolled hypertension gave positive results such a decrease in daytime ambulatory systolic and diastolic blood pressure. More compliance with intervention was also found as patients were found to frequently monitor blood pressure readings through the telemonitoring equipment. The intervention was also cost-effective as expense was only required for equipment, training and consultation. I also propose to use telemonitoring for uncontrolled hypertension patients due to positive implications for clinical studies. I would also make it more cost-effective by reducing the duplication of effort due to the time spent in adapting the new technology. This will be done by providing adequate training to staff regarding the efficiently using the telemonitoring equipment so that they become confident in handling it. This would also eliminate the problem of non-compliance with treatment and little attention to constantly monitor the blood pressure. This intervention will promote easy access to constant blood pressure monitoring and seeking feedback from patients (McKinstry et al. 2013),

Number of patients with healed ulcer (good outcome) in control group (Bandage A)= 65%

Number of patients with no healed ulcer (bad outcome) in control group= 35%

Number of patients with healed ulcer (good outcome) in intervention group (Bandage B)= 85%

Number of patients with poor healing of ulcer (poor outcome) in intervention group (Bandage B)= 15%


Bad outcome

Good outcome


Intervention group

15% (A)

85% (B)


Control group

35% (C)

65% (D)



A+C= 50%

B+D= 150%


Relative risk of healing (RR)=   = (15/ 100)/(35/100)

= 0.428

Therefore, the relative risk of poor outcome in healing of leg ulcer is 0.428

If the risk is less than 1, it indicates that intervention group have less risk compared to control group.

Absolute risk difference (ARD)= Difference in absolute risk between control and intervention group= 85%-65%- 20%

Number needed to treat (NNT)= Inverse of absolute risk reduction= 1/ 20= 5

This indicates that atleast 5 people needed to treated to avoid poor outcome in healing leg ulcer

The value of RR according to calculation is 4.28. As relative risk is the proportion of risk present between intervention and control group, this value suggest that the risk of bad outcome is more in control group compared to intervention group.

The value for ARD is 20 %. This is simply the difference between risk compared to relative difference between risk.

NNT value of 5 indicates that a minimum of people is needed to be treated to avoid the risk of poor outcome in healing.

Bandage B is considered over Bandage for healing ulcer because its relative risk is low compared to Bandage A. While implementing any new intervention, it is necessary to evaluate the evaluate the chances of risk outcome. The minimum is the risk outcome, the more efficacious is the intervention. Hence, Bandage B should be considered over Bandage for treating leg ulcer.

Part three: Implementation of EBP

There are many barriers to implementing the new researching finding in clinical setting. These are:

  • Organizational barrier- Due to lack of support in encouraging staffs to utilize evidence based intervention, health care professional continue to use traditional method of care. T compromises the desired quality of care.
  • Issues in developing evidence based policy- To effectively integrate new research findings, appropriate policy development is needed. However, this is difficult due to the hectic procedure and initial arrangement to supply adequate information system.
  • Complexity and size of research- Nurses and staffs face barrier in interpreting the complex research data and evaluating their relevance in particular practice area.
  • Lack of training- When health care staffs are not adequately trained in evidence based care, it acts as a barrier in the integrating it in research practice (Sadeghi?Bazargani et al. 2014).
  • This subject helped me prepare for my role as a junior clinician as I got to learn new things about the ways to apply best evidence in practice. The evaluation and analysis of the randomized controlled trial gave me new insight regarding the purpose of such studies and how it contributes to clinical intervention. Secondly, use of different models such as evidence based framework and the Tanner’s model of clinical judgment supported me in developing my critical reflection skill. This tool can be effectively used to judge clinical situation, interpret issues and contemplate best action to solve patient issue. Currently, there is also a focus on implementing evidence based care in practice and the evidence based framework will effectively guide me in retrieving the best evidence that can be applied in clinical setting.


Mariani, B., Cantrell, M.A., Meakim, C., Prieto, P. and Dreifuerst, K.T., 2013. Structured debriefing and students' clinical judgment abilities in simulation. Clinical Simulation in nursing, 9(5), pp.e147-e155.

McKinstry, B., Hanley, J., Wild, S., Pagliari, C., Paterson, M., Lewis, S., Sheikh, A., Krishan, A., Stoddart, A. and Padfield, P., 2013. Telemonitoring based service redesign for the management of uncontrolled hypertension: multicentre randomised controlled trial. BMj, 346, p.f3030.

Melnyk, B.M. and Fineout-Overholt, E. eds., 2011. Evidence-based practice in nursing & healthcare: A guide to best practice. Lippincott Williams & Wilkins.

Olivo, S.A., Macedo, L.G., Gadotti, I.C., Fuentes, J., Stanton, T. and Magee, D.J., 2008. Scales to assess the quality of randomized controlled trials: a systematic review. Physical therapy, 88(2), p.156.

Sadeghi?Bazargani, H., Tabrizi, J.S. and Azami?Aghdash, S., 2014. Barriers to evidence?based medicine: a systematic review. Journal of evaluation in clinical practice, 20(6), pp.793-802.

Shariff, S.Z., Bejaimal, S.A., Sontrop, J.M., Iansavichus, A.V., Haynes, R.B., Weir, M.A. and Garg, A.X., 2013. Retrieving clinical evidence: a comparison of PubMed and Google Scholar for quick clinical searches. Journal of medical Internet research, 15(8), p.e164.

Zhong, B., 2011. How to calculate sample size in randomized controlled trial?. Journal of thoracic disease, 1(1), pp.51-54.

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