Introduction
Any researcher in the field of medicine is obliged to adequately evaluate the results of the proposed changes. Assessing the outcomes of changes being developed to improve patient health is an integral part of an evidence-based approach (Hande et al. 2017). If an intervention is proven to be effective, it will increase the credibility of the studies and speed up the implementation process, and hence improve the health of patients (Peterson et al., 2019). A sound assessment of the outcomes should include identifying appropriate indicators of the effectiveness of changes, collecting and evaluating data, and presenting the assessment findings in an accessible form.
Evidence Based Intervention
Evidence supports the effectiveness of interventions based on monitoring electronic health records (EHR). In this case, the evidence is considered to be a reduction in HbA1c levels compared to no intervention. Efficacy should be supported by statistical averages, but for this PICOT, focusing on racial differences in treatment approach and outcomes is important. Therefore, the ideal evidence for this PICOT would be to compare white and black patients for HbA1c levels after the intervention.
Change Indicator
Since the PICOT concerns patients with diabetes, the measurement of HbA1c levels is relevant for evaluating the effectiveness of the intervention. Researchers can also provide additional metrics to measure performance. It is desirable if the performance evaluation is based on several relevant criteria (Fineout-Overholt & Johnston, 2007). In the PICOT for diabetes, these indicators could be reduced doses of essential insulin medications, symptom assessment tests for the severity of diabetes symptoms, or self-reported health tests for patients.
Data Collection
EHRs will be the most effective way to collect data, as they reflect complete information for the health of the patient and help determine all related data. However, it is important to take into account the experience of patients in order to form a relevant opinion on the effectiveness of a particular practice (Melnyk & Fineout-Overholt, 2019). The survey of patients will be a qualitative addition to the obtained statistical data. Patients will be asked to answer questions about how they feel after the proposed intervention period.
Data Evaluation
Sufficient data must be collected to begin the analysis phase and ensure that a relevant sample has been selected for the study. The collected data should be located in a convenient tool for analysis, probably, in a table. It is necessary to take into account all the data obtained, both confirming the hypothesis and refuting it. Evaluation of data for this PICOT will include analysis of HbA1c levels and patient questionnaires, it is necessary to consider the number of those who believe that the state of health has not changed or has changed for the worse or better.
Statistics
After evaluating the data, it is important to present them statistically so that the conclusions of the study are clear for the medical community. An ideal statistic for this PICOT would include pre- and post-intervention HbA1c levels, disaggregated by racial factor. Complementing such a statistical inference would be a chart based on how many people responded positively or negatively to the question about improved health after the intervention.
Conclusion
Evaluation of the effectiveness of an intervention is an essential step in scientific research aimed at improving the health of patients. A sound evaluation of effectiveness is part of the overall responsibility for the credibility of the study’s findings and evidence that the proposed intervention will actually improve the situation. In the studied PICOT, the evaluation of effectiveness can be based on quantitative data – an assessment of the level of HbA1c and on qualitative – a self-questionnaire of the state of health for patients. Adequate and competent evaluation of effectiveness will increase the evidence of the intervention and, accordingly, increase the possibility of its implementation.
References
Fineout‐Overholt, E., & Johnston, L. (2007). Evaluation: an essential step to the EBP process. Worldviews on Evidence‐Based Nursing, 4(1), 54-59. Web.
Hande, K., Williams, C. T., Robbins, H. M., Kennedy, B. B., & Christenbery, T. (2017). Leveling evidence-based practice across the nursing curriculum. The Journal for Nurse Practitioners, 13(1), 17-22. Web.
Melnyk, B. M., & Fineout-Overholt, E. (2019). Evidence-based practice in Nursing & Healthcare: A guide to best practice (4th ed.). Wolters Kluwer.
Peterson, J. F., Roden, D. M., Orlando, L. A., Ramirez, A. H., Mensah, G. A., & Williams, M. S. (2019). Building evidence and measuring clinical outcomes for genomic medicine. The Lancet, 394(10198), 604-610. Web.