Reducing Congestive Heart Failure Readmission Rates

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In a study associated with heart failure and cardiac conditions, in general, it is necessary to account for risks related to one’s lifestyle and medical history. Hence, in the present quantitative study aimed at defining the effect of patient education on readmission, such extraneous variables as age, body mass index, dietary habits, diabetes mellitus, cholesterol, blood pressure, and difference in inpatient units and treatment should be considered. According to Onstott (2021), to eliminate the latter, the process of sampling should be conducted only within a single inpatient unit. In terms of this study, this unit is the Brigham and Women’s Hospital. As far as the other extraneous variables are concerned, the control over them will be performed with the help of administering surveys among potentially eligible study candidates to choose a group of participants within the same range of health and lifestyle characteristics.

Instruments

The two major techniques used in the present research will include survey and experimentation. The first technique will be used to collect preliminary data to adjust the study sample. The surveys will be self-administered and distributed among patients with a history of congestive heart failure at the Brigham and Women’s Hospital. The main instrument of the quantitative study, however, is experimentation. Since the study itself is quasi-experimental, minor manipulation of the independent variables is required to compare and contrast the results. The primary threats to the internal validity caused by such an instrument are “history, maturity… testing, instrument decay, regression toward the mean, selection, and mortality” (Flannelly et al., 2018, p. 127). These threats can be addressed by securing the homogeneity of the sample through preliminary selection, which, for its part, may decrease the generalizability of the findings. In this context, the control over the internal validity of the research will be more relevant.

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The tests for validity and reliability of the study will include criterion-related validity and Cronbach’s alpha reliability test. The former stands for the comparison of the results with the concurrent measurement outcomes through the correlation coefficient, and the latter shows the scope of the relation between the items within the sample (“Reliability and validity,” 2021). In such a way, one could define the extent to which the study outcomes could be extrapolated to the public.

Intervention

The quasi-experimental design of the study will account for the non-random selection of the sample but the random allocation of the subjects between the intervention and control groups. The intervention group for the study will include the subjects undergoing tailored patient education on the matter of prevention readmission and health promotion and post-discharge for congestive heart failure. The intervention per se will include nurses’ guidelines, recommendations, and educational leaflets on health promotion and heart failure management adopted from the data sheets by CDC and American Heart Association. The control group will include subjects who will be discharged upon the procedure standard for the Brigham and Women’s Hospital with no additional interventions required. Both groups will then be observed on the matter of readmission instances in the 30 days after discharge.

Data Collection Procedures

Using SPSS Statistics software, the results of the experiment will be converted into a spreadsheet with four major indicators: three independent and one dependent variable. The first independent variable of the time spent on patient education will be calculated in minutes per patient and collected through self-administered surveys presented by the nurses and the subject to eliminate the risk of biases. The same survey will include information on whether the patients received the education in the first place. The instances of readmission will be collected from the hospital site database and later inserted into the SSPS spreadsheet to conduct an inferential statistical analysis.

References

Flannelly, K. J., Flannelly, L. T., & Jankowski, K. R. (2018). Threats to the internal validity of experimental and quasi-experimental research in healthcare. Journal of Health Care Chaplaincy, 24(3), 107-130. Web.

Onstott, D. (2021). Implementation of an evidence-based practice discharge medication protocol for heart failure patients to reduce 30-day readmissions. [Doctoral project, University of St Augustine for Health Sciences]. Web.

Reliability and validity. (2021). Web.

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NursingBird. (2022, November 5). Reducing Congestive Heart Failure Readmission Rates. Retrieved from https://nursingbird.com/reducing-congestive-heart-failure-readmission-rates/

Reference

NursingBird. (2022, November 5). Reducing Congestive Heart Failure Readmission Rates. https://nursingbird.com/reducing-congestive-heart-failure-readmission-rates/

Work Cited

"Reducing Congestive Heart Failure Readmission Rates." NursingBird, 5 Nov. 2022, nursingbird.com/reducing-congestive-heart-failure-readmission-rates/.

References

NursingBird. (2022) 'Reducing Congestive Heart Failure Readmission Rates'. 5 November.

References

NursingBird. 2022. "Reducing Congestive Heart Failure Readmission Rates." November 5, 2022. https://nursingbird.com/reducing-congestive-heart-failure-readmission-rates/.

1. NursingBird. "Reducing Congestive Heart Failure Readmission Rates." November 5, 2022. https://nursingbird.com/reducing-congestive-heart-failure-readmission-rates/.


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NursingBird. "Reducing Congestive Heart Failure Readmission Rates." November 5, 2022. https://nursingbird.com/reducing-congestive-heart-failure-readmission-rates/.