Readmission Rates in Cardiology: Study Design

Literature Review

Chronic heart failure (CHF), as well as other associated diseases and complications, turns out to be a serious problem for many hospitals and patients. The investigation of Aizawa, Imai, and Fushimi (2015) shows that more than 26 million American citizens live with CHF. This condition is a leading cause of frequent hospitalizations and readmissions among more than 5.7 million Americans (Ziaeian & Fonarow, 2016).

The rise of CHF incidence is explained by the rise of aging people around the whole globe (Deek, Skouri, & Noureddine, 2016). However, human factors cannot be neglected in the management of health care that should be offered to CHF patients. For example, Wan et al. (2017) recommend focusing on such guiding principles as “education and assessment rest and relaxation, exercise, interpersonal relationships, outlook, and dietary recommendations” (p. 2).

Avaldi et al. (2015) underline the role of general practitioners, specialists, and nurses in preventing readmissions of patients with CFH and focus on the necessity to promote patient education and evidence-based pharmacological treatment. Organizational and human factors have to be thoroughly investigated in order to identify appropriate interventions and transitional care conditions and to ensure patient satisfaction.

Hospital performance is a key factor in predicting CHF patients’ readmissions. The peculiar feature of the work of the medical staff is not only to help hospitalized patients and educate their families but also to promote phone calls after discharge for assessing symptoms and considering medication adherence during the next month (Wan et al., 2017). Each country demonstrates different organizational achievements and possibilities to prevent readmissions. For example, the intervention developed by Japanese hospitals includes acute medical care and additional rehabilitation and nursing care to decrease the length of stay in hospitals (LOS) (Aizawa et al., 2015).

The example of Northern Italy that was researched by Avaldi et al. (2015) focuses on skilled nurses’ participation in specific training sessions where they learn how to develop fast diagnostic tests and promote patient self-management. The achievements of American hospitals contribute to the reduction of readmissions among patients through medication reconciliation and the necessity to schedule follow-ups and develop discharge planning before patients leave hospitals (Ziaeian & Fonarow, 2016). Many patients stay unaware of the changes in their medical treatment plans, promoting new errors and inadequate inpatient and outpatient care.

Regarding the importance of controlling patients and their health conditions, special attention should be paid to the chosen drug therapy and nursing skills. Deek et al. (2016) recommend using such medications as ACE inhibitors, beta-blockers, and inotropes during first readmissions. Prediction of readmissions is also a significant intervention that may be introduced by the nursing staff.

The level of glucose and cholesterol in the blood, age, and concomitant diseases determine the number of readmissions among the patients of both genders (Deek et al., 2016). Nurses have to communicate with patients and gather any information that may influence health conditions. For example, the improvement of life-style and optimization of therapy compliance are the main responsibilities of nurses with the help of which they can detect the symptoms of heart failure at its early stage (Avaldi et al., 2015). Bilingual nurses should also focus on discussing such topics as diet, self-management, and regular visits to a family therapist or a local cardiologist (Ziaeian & Fonarow, 2016). The combination of nurse skills, effective training, and patient involvement in self-care should contribute to the reduction of readmissions of people with CFH.

Methodology

This study aims at discussing the necessity to reduce the number of readmissions among patients with CFH. There are three additional objectives based on research questions: to discuss the role of nurses in readmission reduction, to evaluate interventions for eliminating the burning issue, and to analyze transitional care conditions under which it is possible to ensure a high treatment level and patient satisfaction. It is planned to develop a retrospective cohort study of hospitalized and discharged patients with CFH regarding the standards of the International Classification of Disease, 10th Revision (ICD-10).

Several online databases, including PubMed and the Cochrane Library, will be searched from January 1, 2015, to December 31, 2017, for studies where researchers reported the causes and outcomes of readmissions of patients with CFH in South Florida, the United States. The results of the search will be thoroughly studied to identify demographic and clinical characteristics of patients, including gender, age, race, LOS, discharge condition, and CHF readmission. It is necessary to limit readmission time to 30 days and exclude reasons other than CHF.

Approval to conduct this cohort study has to be obtained from the Institutional Review Board. Informal consent will no longer be required because all patients’ data should be used in a de-identified format. A flow map of data inclusion will be used to create a scale of readmissions among patients with heart failures using a purposive sampling design:

Total number of patients with CFH in South Florida ⇒ Time period (patients should be discharged from January 1, 2015, to December 31, 2017) ⇒ A primary diagnosis (patients with CFH meeting the ICD-10 standards); ⇒ Age of patients (40 years and older) ⇒ Length of stay (more than 10 days); ⇒ Readmission (no more than 30 days).

The exclusion of patients CFH with who were readmitted because of other than heart failure causes such as trauma, influenza, or acute pain will be an obligatory condition in this study. The tools that will be necessary for the retrospective analysis are access to the chosen databases and specific search terms for studies. These key-terms will be “heart failure”, “chronic heart failure”, “readmission”, “discharge”, “nursing care”, and “intervention”.

Using this information, it will be possible to compare the incidence of readmissions in CFH patients in hospitals where specific nursing interventions and transitional care conditions are promoted. Within the frames of the chosen design, a multivariate logistic regression model will be used to compare patients with readmissions because of new heart failures with non-readmitted patients and identify the factors that may be associated with readmissions within the next 30 days after discharge.

Statistical analysis of the gathered data will be performed on the basis of Chi-square tests. Nursing interventions will be identified using the chosen cases, regarding the number of follow-ups, the incidence of nurse check-ups, and education courses for nurses to improve their performance and for patients to enlarge their level of knowledge about CFH. In the end, it is expected to report on the interventions with the help of which the number of readmitted patients may be reduced and compare the conditions under which patients receive care. Nursing professionalism, as well as general hospital performance, will be analyzed in terms of the chosen retrospective cohort analysis and comparison of readmitted and non-readmitted patients with CFH.

References

Aizawa, H., Imai, S., & Fushimi, K. (2015). Factors associated with 30-day readmission of patients with heart failure from a Japanese administrative database. BMC Cardiovascular Disorders, 15(1), 134-141.

Avaldi, V. M., Lenzi, J., Castaldini, I., Urbinati, S., di Pasquale, G., Morini, M., … Fantini, M. P. (2015). Hospital readmissions of patients with heart failure: The impact of hospital and primary care organizational factors in Northern Italy. PLoS One, 10(5), 1-15. Web.

Deek, H., Skouri, H., & Noureddine, S. (2016). Readmission rates and related factors in heart failure patients: A study in Lebanon. Collegian, 23(1), 61-68.

Wan, T. T. H., Terry, A., Cobb, E., McKee, B., Tregerman, R., & Barbaro, S. D. S. (2017). Strategies to modify the risk of heart failure readmission: A systematic review and meta-analysis. Health Services Research and Managerial Epidemiology, 4, 1-16. Web.

Ziaeian, B., & Fonarow, G. C. (2016). The prevention of hospital readmissions in heart failure. Progress in Cardiovascular Diseases, 58(4), 379-385.

Cite this paper

Select style

Reference

NursingBird. (2024, February 2). Readmission Rates in Cardiology: Study Design. https://nursingbird.com/readmission-rates-in-cardiology-study-design/

Work Cited

"Readmission Rates in Cardiology: Study Design." NursingBird, 2 Feb. 2024, nursingbird.com/readmission-rates-in-cardiology-study-design/.

References

NursingBird. (2024) 'Readmission Rates in Cardiology: Study Design'. 2 February.

References

NursingBird. 2024. "Readmission Rates in Cardiology: Study Design." February 2, 2024. https://nursingbird.com/readmission-rates-in-cardiology-study-design/.

1. NursingBird. "Readmission Rates in Cardiology: Study Design." February 2, 2024. https://nursingbird.com/readmission-rates-in-cardiology-study-design/.


Bibliography


NursingBird. "Readmission Rates in Cardiology: Study Design." February 2, 2024. https://nursingbird.com/readmission-rates-in-cardiology-study-design/.