Instructor: Julie Menendez

Solvik, E., & Struksnes, S. (2018). Training Nursing Skills: A Quantitative Study of Nursing Students’ Experiences before and after Clinical Practice. Nursing Research and Practice, 2018(1), 1–9. https://doi.org/10.1155/2018/8984028

The research aims to assess the outcomes of various learning sessions on nursing students' preparedness for clinical settings utilizing a descriptive quantitative method infused with clinically guided trials. Carried out on the Norwegian University of Science and Technology students, this study had 160 first-year nursing significant students, with 80 students in the project group and 80 in the control group. Key highlights reveal that to enhance the student's level of confidence and mastery in clinical practice; more emphasis should be placed on training preparation and training sessions. The study pays much attention to student activities and learning, and it was established that moderation of student activities and learning, and the traditional approach recorded the best results in the study period. Such observations are valuable for clarifying practice-based knowledge about the effectiveness of training solutions for increasing the readiness of nursing students and the quality of patients’ care.

Gopal, D., Chetty, U., O’Donnell, P., Gajria, C., & Blackadder-Weinstein, J. (2021). Implicit bias in healthcare: Clinical practice, research, and decision making. Future Healthcare Journal, 8(1), 40–48. https://doi.org/10.7861/fhj.2020-0233

The given article is a non-systematic literature review that focuses on the influence of bias in health care. It describes how stereotype activation/in operation (subtle prejudices) and pre/post-possibility biases (flaws in reasoning) impact clinical conduct and result in service disparities. The investigation identifies significant shortcomings, such as prejudice against White individuals and females, which contributes to ethnic discrimination and disadvantageous treatment. The study focuses on the fact that even clinicians can be naturally prone to do a specific kind of prejudiced thinking that may influence their diagnoses and decisions on the treatment, and the patient may remain unaware of that. Identifying and eliminating these biases is critical to enhancing patient outcomes, succeeding in accurate diagnoses, and successful treatment of diverse groups of patients.

Costello, R., McDonagh, J., Hyrich, K. L., & Humphreys, J. H. (2021). Incidence and prevalence of juvenile idiopathic arthritis in the United Kingdom, 2000–2018: Clinical Practice Research Datalink results. Rheumatology, 61(6). https://doi.org/10.1093/rheumatology/keab714

This paper employed data collected from CPRD to estimate the incidence and prevalence of Juvenile Idiopathic Arthritis in the UK between 2000 and 2018. It was found that the frequency of cancer was 4,331 with the help of a broad code list and 2,705 frequencies with the help of a specific code list. Moreover, the hospital records of the patients were verified, and 1,649 cases were found to be cancerous. Some findings are as follows: The age-standardized incidence rate of the major was 5; 0 for incident rate with a distribution of 61 per 100,000 and a point prevalence of 43. The incidence rate in 2018 was five new cases per 100,000 of the population. Incidence rates were non-significantly constant but significantly different by age, region, females, and Scotland than other regions. For clinical practice, they are essential for the distribution of resources and enhancing patient care strategies.

Liau, S. J., Lalic, S., Sluggett, J. K., Cesari, M., Onder, G., Vetrano, D. L., Morin, L., Hartikainen, S., Hamina, A., Johnell, K., Tan, E. C. K., Visvanathan, R., & Bell, J. S. (2021). Medication Management in Frail Older People: Consensus Principles for Clinical Practice, Research, and Education. Journal of the American Medical Directors Association, 22(1), 43–49. https://doi.org/10.1016/j.jamda.2020.05.004

Most of the identified practice changes are regarding the IMMP, a package of international consensus principles for improving medication management in older frail people, created by the Optimizing Geriatric Pharmacotherapy through Pharmacoepidemiology Network. It synthesizes principles about practice, research, and education. This includes a medication reconciliation policy or guideline, an individualized patient management plan, the reduction of the complexity of the medication regimen, and effective communication across the clinical care teams. Trials should enroll frail people, use frailty as an effect measure, and use linked health data. In the educational field, it supports the inclusion of frailty into courses of study and the enhancement of medication stewardship. These principles can be applied in clinical practice since they offer a guideline that may help health practitioners ratify directions in the medication needed for frail older people to minimize the negative consequences of drugs and enhance the aggregate well-being of these populations.

Persson, R., Sponholtz, T., Vasilakis-Scaramozza, C., Hagberg, K. W., Williams, T., Kotecha, D., Myles, P., & Jick, S. S. (2021). Quality and Completeness of Myocardial Infarction Recording in Clinical Practice Research Datalink Aurum. Clinical Epidemiology, Volume 13, 745–753. https://doi.org/10.2147/clep.s319245

The findings from this validation study are related to the completeness and accuracy of MI diagnoses recorded within CPRD Aurum against HES data. Across the sample of 50,000 patients, the authors identified that 94% of the identified MIs in CPRD Aurum were accurate based on concordance with HES or high-quality supporting information. Completeness was lower, and the rates for HES-recorded MIs included only 74% of MIs documented in Aurum-CPRD. This study is of apparent clinical relevance since it backs the usage of the CPRD Aurum database in research and delineates the accuracy of MI diagnosis as extremely high. However, it also stresses the importance of data linkage in including all the cases, thus providing a complete picture of the patient and more reliable research findings.

Arana, A., Margulis, A. V., Varas‐Lorenzo, C., Bui, C. L., Gilsenan, A., McQuay, L. J., Reynolds, M., Rebordosa, C., Franks, B., Stefan de Vogel, Kwame Appenteng, & Perez‐Gutthann, S. (2020). Validation of cardiovascular outcomes and risk factors in the Clinical Practice Research Datalink in the United Kingdom. Pharmacoepidemiology and Drug Safety, 30(2), 237–247. https://doi.org/10.1002/pds.5150

This study's AMI and stroke algorithms in the UK CPRD GOLD database are externally verified using records from general practitioners’ databases and physicians’ questionnaires. The study shows that, throughout the algorithms’ development, there are high PPVs for AMI (>90%) and positive changes when it comes to identifying strokes (PPV up to 92% for definite stroke). Smoking was also an identified factor and correctly estimated were obesity and postmenopausal status. The study also emphasizes that cases validated by physicians offer IRRs that are more compatible with the trends from hospitalization and mortality data. In terms of clinical application, proper outcome definition, and risk assessment for the reliability of epidemiological studies and the enhancement of patient management in primary care.

References

Arana, A., Margulis, A. V., Varas‐Lorenzo, C., Bui, C. L., Gilsenan, A., McQuay, L. J., Reynolds, M., Rebordosa, C., Franks, B., Stefan de Vogel, Kwame Appenteng, & Perez‐Gutthann, S. (2020). Validation of cardiovascular outcomes and risk factors in the Clinical Practice Research Datalink in the United Kingdom. Pharmacoepidemiology and Drug Safety, 30(2), 237–247. https://doi.org/10.1002/pds.5150

Costello, R., McDonagh, J., Hyrich, K. L., & Humphreys, J. H. (2021). Incidence and prevalence of juvenile idiopathic arthritis in the United Kingdom, 2000–2018: results from the Clinical Practice Research Datalink. Rheumatology, 61(6). https://doi.org/10.1093/rheumatology/keab714

Gopal, D., Chetty, U., O’Donnell, P., Gajria, C., & Blackadder-Weinstein, J. (2021). Implicit bias in healthcare: Clinical practice, research and decision making. Future Healthcare Journal, 8(1), 40–48. https://doi.org/10.7861/fhj.2020-0233

Liau, S. J., Lalic, S., Sluggett, J. K., Cesari, M., Onder, G., Vetrano, D. L., Morin, L., Hartikainen, S., Hamina, A., Johnell, K., Tan, E. C. K., Visvanathan, R., & Bell, J. S. (2021). Medication Management in Frail Older People: Consensus Principles for Clinical Practice, Research, and Education. Journal of the American Medical Directors Association, 22(1), 43–49. https://doi.org/10.1016/j.jamda.2020.05.004

Persson, R., Sponholtz, T., Vasilakis-Scaramozza, C., Hagberg, K. W., Williams, T., Kotecha, D., Myles, P., & Jick, S. S. (2021). Quality and Completeness of Myocardial Infarction Recording in Clinical Practice Research Datalink Aurum. Clinical Epidemiology, Volume 13, 745–753. https://doi.org/10.2147/clep.s319245

Solvik, E., & Struksnes, S. (2018). Training Nursing Skills: A Quantitative Study of Nursing Students’ Experiences before and after Clinical Practice. Nursing Research and Practice, 2018(1), 1–9. https://doi.org/10.1155/2018/8984028