Home / Research Paper / How to Cut Down on CHF Readmissions, Research Paper Example

How to Cut Down on CHF Readmissions, Research Paper Example

Pages: 13

Words: 3635

Abstract

The research completed is focusing on recent studies examining the reasons behind CHF readmissions of patients and methods or reducing short term repeated hospitalization. The studies examined focused on identifying risk factors, as well as measuring different intervention methods’ effectiveness to reduce readmission rates.

The main research questions of the literature search were as follows:

A: What are the risk factors that should be assessed when identifying patients who are at risk of being readmitted for the primary reason of CHF within 30 days?

B: How can populations with the highest rate of readmission be identified and educated to avoid readmission?

C: How effective are tools currently utilized in cardiovascular units to determine the probability of readmission short term and long term?

D: What steps can nursing managers take to reduce overall readmission rates among CHF patients?

Methods to Cut Down CHF Readmissions. An Exploratory Study

Part II

Purpose

The purpose of the current research is to retrieve information about effective methods to prevent CHF readmissions of patients. The author would like to draw from existing research literature examining various intervention methods focusing on measurable reduction of patient readmission to hospitals related to CHF. The author of the current research would like to determine the main variables that impact rehospitalization of CHF patients, and the main measures that are related to measuring success. While all the reviewed articles and research studies are using different measurements to evaluate the effectiveness of the intervention, it is important to create an assessment framework in order to compare the results of the studies, and identify the main themes and intervention components.

Methods

The author would like to use a literature search, and a statistical analysis of completed research. The literature search is covering academic journal research articles published between 2010 and 2015, focusing on interventions to prevent readmission. During the literature search, the author will analyze the text of the research studies, and conduct a phrase or theme analysis. By creating a table that compares how many times each of the intervention component, measure, and tool is mentioned in the articles, the prevalence of the method, and the measured effectiveness can be analyzed.

Sample

Using online databases, the author will critically evaluate and examine five large scale research studies, through a qualitative analysis that covers intervention methods, participant characteristics, and correlations between the intervention and readmission reduction. The samples will then be weighted and analyzed to assess how representative the findings of the research study are and how relevant the research is the current research question.

Literature Review

First Article:

Markley, J., Andow, V., Sabharwal, K., Wang, Z., Fennell, E., & Dusek, R. (2013). A project to reengineer discharges reduces 30-day readmission rates. AJN The American Journal of Nursing, 113(7), 55-64. Retrieved from http://njhimss.org/images/documents/whitepapers/Solving-Preventable-Readmissions-White_Paper.pdf

Authors:

The authors are medical practitioners, and their credentials include PhD in health care, MPA, and BHA training. Jennifer Markley currently works as a health care quality improvement director. Karen Sabharwal works as a senior analytic consultant, Vanessa Andow is a readmissions program manager, Ziyin Wang works as a data analyst, Ron Dusek is a specialist in communication, while Emilie Fennell works at the TMF Health Quality Institute in Austin, Texas, as a director of communications.

Title:

The title of this project is A Project to Reengineer Discharges Reduces 30-Day Readmission Rates A Texas hospital achieves improvement in its readmission rate by implementing Project RED. The title reflects the research that is being reported is related to one particular method of intervention to reduce readmission rates: Project RED.

Type:

This research is mixed, including both quantitative and qualitative data. It is a study that measures readmission rates before and after the implementation of the project, and draws conclusions based on the information from the statistical analysis and patient discharge survey results.

Purpose:

The purpose of the research is to evaluate the effectiveness of Project RED to reduce the number of hospital readmissions. The authors created the review to support health care professionals to reduce the number of readmissions in their organization, avoid readmission penalty, and to investigate the root causes of readmission within 30 days for heart attack and heart failure. The project RED is thought to be in line with the government’s Medicare and Medicaid policies and initiatives, in particular the Readmission Reduction Program (Markley et al., 2013).

Methods:

The authors used free-for-service databases from the Centers for Medicare and Medicaid Services (CMS) to analyze the claims related to hospital readmissions. The researchers created a baseline before measuring improvements, based on data between October 1 2007 and March 31 2008. This baseline data created a quantitative foundation for the comparison.

Sample:

The authors worked with the Quality Improvement team to identify the sample population, and selected “heart failure patients who had been admitted to the telemetry floor and were subsequently discharged to home and self-care” (Markley et al., 2013, p. 57).

Results:

Within the examined hospital, Valley Baptist Medical Center–Brownsville, between the baseline readmission rate (previously determined at 23.3 percent) and the time after implementation was 8.3 percentage points, which is an improvement of 36 percent.

Limitations:

The limitations of the study include the small size of the sample, and the fact that the CMS data used did not include Medicare Advantage data.

Conclusions:

Overall, the study revealed that the implementation of Project Red has the potential to positively influence patient outcomes and reduce readmission rates among CHF patients.

Second Article:

Rabbat, J., Bashari, D. R., Khillan, R., Rai, M., Villamil, J., Pearson, J. M., & Saxena, A. (2012). Implementation of a heart failure readmission reduction program: a role for medical residents. Journal of Community Hospital Internal Medicine Perspectives, 2(1).

Authors:

All authors work at the Lutheran Medical Center. Jennifer Rabbat, Rajnish Khillan, Manisha Rai, MD, Jose Villami, and Daniel R. Bashari, work in the Department of Internal Medicine. Julie M. Pearson, MPH holds a position at the Department of Clinical Research, while Archana Saxena, MD,, FACC is a member of the Department of Cardiology.

Title: Implementation of a heart failure readmission reduction program: a role for medical residents

Type:

The research was based on the quantitative analysis of readmission rates in the Lutheran Medical Center before and after the implementation of the Smooth Transitions Equal Less Readmission (STELR) program. The authors used both retrospective and prospective data collection methods: one sample included readmitted patients to identify intervention areas, and the other one involved the tracking of patients who participated in the intervention project.

Purpose:

The purpose of the study was to evaluate the effectiveness of the STELR intervention program in reducing CHF patient readmission rates. Further, the follow-up of patients measured short term outcomes after the implementation of the project.

Methods:

The authors identified patients to be included in the study using a CHF diagnostic tool. The admission index of the hospital was used to identify the sample population.

Sample:

The retrospective sample included 65 patients who were diagnosed with CHF and were readmitted to the hospital within 30 days. The prospective sample included patients who were or were not readmitted within 30 days, and had a size of 69.

Results:

The research results showed that readmission rates reduced by 8 percentage points (32 percent to 24 percent) after the implementation of the STELR intervention program.

Limitations:

This research only focused on a small sample within one community hospital, therefore, the data might not be representative. Further, it is important to note that the population served by the hospital consists of a great proportion of minority patients, which means that the results might be different for a more representative sample.

Conclusions:

Overall, the research has confirmed that following up and educating patients with CHF can reduce readmission rates in community hospitals. Further, it has been found that patient education had a positive effect on patient outcomes, and those who had a follow-up appointment were less likely to be readmitted.

Third Article:

Dungan, K., Osei, K., Nagaraja, H., Schuster, D., & Binkley, P. (2010). Relationship between glycemic control and readmission rates in patients hospitalized with congestive heart failure during implementation of hospital-wide initiatives. Endocrine Practice, 16(6), 945-951.

Authors:

Kathleen M Dungan, Dara Schuster, and Kwame Osei are working in the The Ohio State University Division of Endocrinology, Diabetes & Metabolism. Haikady N Nagaraja is a member of the The Ohio State University Department of Statistics. Philip Binkley works at the Division of Cardiovascular Medicine and the Dorothy M. Davis Heart and Lung Research Institute.

Title:

Relationship between glycemic control and readmission rates in patients hospitalized with congestive heart failure during the implementation of hospital-wide initiatives

Type:

The qualitative data collection and statistical analysis survey was used to determine the time-weighted mean glucose and GLI indexes, to find a correlation between the comorbidity factor among CHF patients and the rate of readmission.

Purpose:

The main purpose of the study was to determine whether or not there is a positive correlation between the glycemic control of the CHF patient and the probability of readmission. The research presented valuable information for practitioners planing to determine related conditions when measuring the risk of readmission to cardiovascular units.

Methods:

The authors used the time weighted mean glucose index, and the glucose liability index of patients to record individual patients’ scores. The scores were later compared with readmission rates, in order to determine whether or not there is a correlation between glucose indexes and readmission risks.

Sample:

The sample population included 748 patients. The authors use electronic computerized data collection from the Ohio State University’s Information Warehouse. Multiple databases were used to collect data about the sample, and the selection criteria included: primary reason for admission being CHF, and at least 2 point-of care glucose values.

Results:

No correlation between TWMG and HbA1c indexes and immediate (within 30 day) readmissions was found. However, after the findings were presented by the analysis, the researchers modified the study, and followed up patients for a longer period of time. The results of the second study showed that elevated TWMG and HbA1c levels were positively correlated with readmission within 30-90 days.

Limitations:

The main limitation of the study is that it measured the entire population with and at least 2 point-of care glucose values, independent on whether or not the patients’ diabetes was controlled or not. It is likely that patients with controlled glucose levels were less likely to be readmitted than those whose condition was recently discovered.

Conclusions:

The main finding of the study is that correlations between CHF co-morbidity conditions should be measured longer term, and patients might need to be followed up for up to 3 months to find a correlation between the condition and readmissions.

Fourth Article:

Wang, H., Robinson, R. D., Johnson, C., Zenarosa, N. R., Jayswal, R. D., Keithley, J., & Delaney, K. A. (2014). Using the LACE index to predict hospital readmissions in congestive heart failure patients. BMC cardiovascular disorders, 14(1), 97.

Authors:

The authors were professional researchers, focusing on data collection, analysis, and research of the methodologies, coordination of the research, methodology selection, and statistical analysis. No professional attributes of the authors are listed in the journal.

Title:

Using the LACE index to predict hospital readmissions in congestive heart failure patients

Type:

The quantitative research study focuses on determining the reliability of the LACE index to predict the risk of unplanned hospital readmissions among CHF patients. The authors used a retrospective study to calculate the score of all patients and compare the scores of those who were readmitted and those who were not readmitted.

Purpose:

The purpose of the study is to measure how reliable the LACE index is to predict unplanned readmissions among CHF patients. The authors attempt to validate the accuracy of the risk assessment tool, in order to provide recommendations for hospital staff and managers whether or not the assessment should be used for predicting unplanned readmissions.

Methods:

The authors used the LACE score calculation in order to determine the initial score of all patients. L stands for the length of time spent in the hospital in days, and is scored 1-7. A stands for the acuity of admission, rated 0 for non-acute cases, and 3 for acute admissions. C- score indicates co-morbidities, ranging from +1 to +6 for each condition. The E-score is indicated by the number of emergency visits sis months prior to the admission.

Sample:

The authors used a sample of patients who were admitted to the hospital mainly for CHF. The selection criteria included that the primary reason for admission was CHF related. Between June 2012 and June 2013, in the urban community hospital 343 patients were admitted for the above stated reasons. The mean age of patients was 57.64, and 59.68 percent were African American. The average initial hospitalization stay was 5.33. 27.42 percent of patients were admitted through a charity program.

Results:

The results of the study showed that there was a weak correlation between the LACE index and readmission risk. The LACE index of those readmitted was an average of 12.17, compared with 11.80 for those who were not readmitted. Therefore, the authors found that the LACE might not be able to accurately predict the risk of unplanned readmissions. However, the study showed that the tool was more effective in predicting ER visits than hospital readmissions.

Limitations:

One of the main limitations of the study was that the sample was limited to one community hospital in an urban area, and was not representative. Further, the study only covered patients who were admitted to the hospital for CHF as a primary reason, from the emergency department, and did not include patients who were referred by primary care services. Finally, the demographics of the sample indicate that patients’ socio-economic status could have affected intervention outcomes.

Conclusions:

Surprisingly, the study covering a relatively large sample did not confirm the reliability and applicability of the LACE index for determining the risk of readmission. This finding might help decision makers and cardiovascular care unit managers to revise their assessment criteria and implement changes in their methods of determining risks.

Fifth Article:

Xexemeku, F., Singh, A., Adjepong, Y. A., & Zarich, S. (2014). Predictors of Early Readmission in Heart Failure Patients in an Inner-City Community Hospital.World Journal of Cardiovascular Diseases, 2014.

Title:

Predictors of Early Readmission in Heart Failure Patients in an Inner-City Community Hospital

Authors:

Fafa Xexemeku is a member of the Division of Cardiology, while Yaw Amoateng Adjepong and Stuart Zarich work at the Department of Medicine, Bridgeport Hospital, Yale University, Bridgeport, USA

Type:

The authors used a quantitative approach to conduct a retrospective cohort study, in a community hospital. Quantitative data was extracted from the electronic database of the inner-city community hospital.

Purpose:

The main purpose of the study is to determine the risk factors of CHF readmissions. In this study, the authors were attempting to create a comprehensive report of risk factors to help medical staff and health care organization managers design more effective interventions and preventive measures to reduce short term readmission of CHF patients, and identify at-risk populations.

Methods:

The authors selected a large urban community teaching hospital with over 400 beds, with a great catchment area, including suburbs. The authors extracted data from the database related to patients admitted between January 1 2008 and December 31 2010, with a primary discharge diagnosis of CHF.

Sample:

A total number of 712 patients were included in the sample. The mean age was 75.4 + 14.3, and over 78 percent were aged 65 or over. The most common reason for hospitalization in the population was CHF exacerbations.

Results:

Readmission rates were higher among Blacks than Non-Blacks (26.1 and 15.6 percent, consequently). Patients who stayed in the hospital for more than 7 days were more likely to be readmitted. Further risk factors identified were being discharged to a nursing facility, and prior history.

Limitations:

The research used only a selection of criteria to assess associated readmission risks. Gender, for example, was not recorded, and race was only measured on a Black/Non-Black basis. This leaves the relatively large Hispanic population out.

Conclusions:

The authors successfully identified some risk factors and the results can help determine at-risk populations. The valuable information provided by the research will be valuable for managers of

Problem Statement

A recent Medscape publication (Hines, Yu, & Randall, 2010, p. 1) states that “27% of patients with HF on Medicare are readmitted within 30 days”. Markley et al. (2013) mentions the Medicare penalty for readmission, which makes it important for health care providers to aim for lower readmission rates. The authors (Markley et al., 2013, p. 55) confirm that “The estimated cost exceeds $2.6 billion every year, or more than $1,000 per readmission”. Apart from the cost of readmission, the high rates also indicate that patient outcomes across the health care system among the CHF population need to be improved. One of the main methods to avoid readmissions identified during the literature search is to educate patients and follow up after discharge. Readmission risk assessment tools can also be potentially utilized in order to implement evidence-based practice and patient-centered care.

Findings

Upon evaluating the results of the research, one tool to identify risks of readmission was assessed. The LACE index, utilized in order to predict readmission risk was examined by Robinson et al. (2014). The index showed a true potential for supporting hospital staff to identify high risk patients, however, the researchers found only weak correlation between elevated LACE score and readmission rates. Therefore, the LACE index was not found to be an effective tool to identify at risk populations.

Another research, completed by Dungan et al. (2010) found correlation between high TWMG and HbA1c indexes and the risk of readmission within 30-90 days. A correlation was not found between higher TWMG and HbA1c indexes and immediate (within 30 day) readmission.

The most comprehensive study to identify risk factors was completed by Xexemeku et al. (2014). The main risk factors identified based on the large scale survey of hospital data were race, longer initial hospital stay, and being released to a nursing facility.

Two studies evaluated the effectiveness of patient-centered prevention and intervention programs to reduce CHF readmission rates. The RED initiative (Markley et al., 2013) was found to be effective to reduce readmission rates, and within the researched hospital, an improvement of 36 percent was achieved. The other research, published by Rabbat et al. (2014) analyzed the effectiveness of Smooth Transitions Equal Less Readmission program. The authors came to the conclusion that a reduction of 8 percentage points was achieved after the implementation of the program. Both intervention frameworks were found to be effective for improving patient outcomes.

Summary

As the above review of literature showed, patient-centered care and education of nurses, as well as patients can improve health outcomes of the entire population. No proven to effective tools were identified to evaluate the risks of readmission, therefore, it is not recommended that cardiovascular units focus on patient groups. Intervention programs implemented, however, showed great results across the patient population, therefore, it is recommended that the nursing manager works on developing a framework focusing on patient-centered care, and the evaluation of risks on an individual basis.

Implementation Steps

The first step of implementation is to carry out a data analysis within the organization and measure readmission rates within 30 and 90 days. The data would be used to create targets for the project team, and develop a related mission for the organization.
The second step is to create a multidisciplinary project team that would work together on selecting the right intervention method. The two methods to choose from are: Red and Smooth Transitions Equal Less Readmission programs. The suitability, cost, and feasibility of the two programs would be assessed in order to make an informed decision. As the results presented in the two studies showed almost equal effectiveness, both programs have the potential of delivering goals.
The next step would be consultation with stakeholders, in particular researchers and patient representative groups, in order to determine the focus areas of the project.
Finally, after choosing an intervention, a mission needs to be created, and a project team would develop related education of the nursing team, and implement changes in the health care delivery.
Results will be measured using the health and discharge database, and discussed monthly by the project team.

Barriers to Implementation

The main barrier of implementation is the lack of commitment from staff. Holding additional meetings with patients, and carrying out further checks would increase nurses’ work-flow. Therefore, commitment towards a shared vision needs to be achieved through facilitating communication and collaboration.

Cost of education and additional tools might also create a barrier. This barrier can be overcome by showing the hospital’s management the financial and performance benefits of reducing readmission rates.

Three Elements of Practice That Should Be Changed Based on the Findings

The first element of practice that needs to be changed is discharge. Patient education needs to be implemented in the procedures, while discharge assessments need to be changed.
The follow-up of patients needs to be changed, as well, according to the project design of the program implemented. Regular checks need to be carried out by nursing staff, to ensure patients have the ability to manage their condition.
Finally, the management of co-morbidity conditions and potential risk factors need to be improved. As a part of patient-centered care, nurses need to focus on the additional health issues, as well as CHF when creating a treatment plan.

References

Hines, P. A., Yu, K., & Randall, M. (2010). Preventing heart failure readmissions: is your organization prepared. Nursing Economics, 28(2), 74-86.

Rabbat, J., Bashari, D. R., Khillan, R., Rai, M., Villamil, J., Pearson, J. M., & Saxena, A. (2012). Implementation of a heart failure readmission reduction program: a role for medical residents.Journal of Community Hospital Internal Medicine Perspectives, 2(1).