South University Online
Evidence Table Worksheet
1. PICOT Question:
Does an effective discharge plan (I) compared to routine care (C) influence Readmission rates (O) in patients, 65 years and older, who have been discharged after hospitalization with Congestive heart failure (P) over 30 days after discharge (T)?
Plus
1. Will you have a comparison group, or will subjects be their own controls? Yes, there will be a comparison group. The study population will have personalized post-discharge outpatient follow-up appointments, while the control group will not have the usual care.
2. Is a ‘time’ appropriate with your question—why or why not?
The allocated time is suitable for the study and will provide more time to follow up for patients after discharge.
II. Evidence Synthesis
Database: PubMed (Parrinello et al., 2011) (Ryan et al., 2013) (Shao et al., 2013) (Lee et al., 2016) (Sharma et al., 2010) Synthesis
(p) Population Comprised of 22 discharged CHF patients 398 patients from heart failure discharge The intervention group had 47 heart failure patients actively attending cardiac clinics. 11,985 eligible adults hospitalized for HF 62 746 COPD patients years old. All the studies comprised of a study population that was either hospitalized for HF or heart related conditions such as COPD.
(i) Intervention Early and personalized congestion guided ambulatory program. 7-day follow-up visits. Self-management initiatives centered on the self-efficacy construct, in elderly patients with heart failure. The timing and type of post-discharge follow-up An early follow-up visit with the patient’s pulmonologist or primary care physician. From the studies, there are several intervention methods and approaches that have been studied by scientists capable of decreasing readmissions
(c) Comparison (c) Comparison 21 subjects for the control group No control group The Control group had 46 patients that received the usual care 7,935 eligible controls. Usual care and no follow-up These are primary studies, and it is proper for them to have controls as part of the research design to lower the effects of variables.
(o) Outcome. Improved clinical compensation, enhanced quality of life, and a decrease in readmissions A reduction in 30- day readmission rate. Significantly improved confidence for salt and fluid control, self-management behavior, and reduction in heart failure-related symptoms. Risks of readmission within 30 days after discharge. A reduction in readmissions and emergency department visits. Majority of the intervention measures taken significantly reduce readmission cases and risks for readmission.
(t) time Six months of follow up visits. 30 days follow up visits. 12 weeks follow up visits. 30 days 30 days Each study had a proper time frame that allowed the studies to be completed and answer the clinical question
III. Evaluation Table
Citation Design Sample Major Variables: Independent Dependent Study findings: Strengths and weaknesses Level of Evidence Synthesis
(Parrinello et al., 2011) Case-control study design 43 participants The sample was inadequate Major Variables: Independent: Readmission rates Independent Dependent: Early (Time)and personalized congestion-guided ambulatory initiatives Study findings: Early and personalized ambulatory follow-up among CHF patients can effectively improve the management and maintenance of clinical stability in the post-discharge period. Strengths: No conflict of interest, the results have significant clinical practice implications and essential for future studies.
Weaknesses: Inadequate sample size. No power analysis Level IV Despite a small sample size, the study provides significant evidence to answer the clinical question for this study. It evaluates alternative methods that can be used to lower readmission rates in elderly patients.
(Ryan et al., 2013) Retrospective chart review 398 patients from heart failure discharge. Adequate Major Variables: Independent: Change in readmission rate Independent Dependent: Seven-day follow-up appointment Study findings: Hospital heart failure readmissions reduced within 30 days Strengths: Adequate sample size The result is of clinical significance Charts, graphs, and tables to illustrate the findings Sufficient statistical analysis
Weaknesses: It is a single-center analysis Discrepancies in the number of patients recruited and completed follow-ups Level III The study provides compelling evidence to support the PICOT question. The research design and the time frame match the current research. It ascertains the fact that follow-ups can significantly reduce readmissions.
(Shao et al., 2013) Randomized controlled trial 47 study participants for the intervention group and 36 for the control group The sample size is adequate Major Variables: Independent: Self-efficacy for salt and fluid control, HF related self-management behavior, and heart failure symptom Independent Dependent: self-management initiatives Study findings: self-management initiatives improve patient self-efficacy
Strengths: It is an RCT study Clinical significance Used Bandura’s model for improving self-efficacy Weaknesses: Inconclusive results. Limited time frame. Lack of objective measures. The study cannot be generalized Level II The study provides strong evidence to answer the PICOT question. Furthermore, it looks at a different method for reducing readmission rates as compared to the other earlier studies
(Lee et al., 2016) Nested matched case-control study 11,985 eligible adults for the intervention group the sample size is adequate Major Variables: Independent: Readmission rates Dependent: Timing and type of post-discharge follow-up Study findings: Outpatient follow-up with a care provider within 7 days reduced chances of 30-day readmission
Strengths: clinically significant No conflict of interest large sample size Enough time frame Graphs, charts, and tables to illustrate the outcomes
Weaknesses: Lost follow-ups due to a large number No power analysis Level IV According to the research design and the findings, this study will be crucial in this project. The article provides compelling evidence regarding what kind of intervention can be used to reduce readmissions.
(Sharma et al., 2010) Retrospective e cohort study 62 746 COPD patients years old Adequate sample size Major Variables: Independent: Readmission rates Dependent: Early follow-up visit with care providers Study findings: Follow-ups with care providers can reduce readmissions rate Strengths: Had several inputs from other scholars Had tables and charts to present results.
Weaknesses: Only examined follow-up visits with the patient’s own PCP or pulmonologist Inadequate patient data before first admission Level IV The study demonstrates that follow-ups with PCP or pulmonologist lower patient readmission. Just like the other studies, it shows there are different ways to reduce readmission cases.
References
Lee, K., Yang, J., Hernandez, A., Steimle, A., & Go, A. (2016). Post-discharge Follow-up Characteristics Associated With 30-Day Readmission After Heart Failure Hospitalization. Medical Care, 54(4), 365-372.