NR702: Project and Practicum I
Session,
Readmissions in Home Care
Readmission rates in hospitals and home care environments has become a major problem due to the reduction in reimbursement rates. There are several diagnoses that are shown to have higher readmission rates heart failure, pneumonia, and myocardial infarction. If a hospital performs poorly in preventing 30-day readmission rates for these diagnoses, there will be a financial penalty. This research will review the readmission issues with congestive heart failure (CHF) and delineate the significance of the problem with this specific issue. Further, the paper will outline a PICOT question, synthesize the literature related to CHF readmissions, discuss the theoretical framework, and summarize practice recommendations.
Significance of the Practice Problem
Readmission rates are significant, because there is a marked impact on patient outcomes and the financial outcomes for the provider or facility. The 30-day readmission rate for CHF patients is 24.8 percent nationwide (Rodak, 2013). Heart failure is the most common diagnosis that is associated with readmission. Further, the mean cost per CHF readmission to the hospital facility is $13,000 per readmission (Rizzo, 2013). And this is 118 percent higher than the primary cost of first admission (Rizzo, 2013). Best practices for reducing readmissions should be studied and implemented.
PICOT Question
The PICOT question for this research is: In patients with congestive heart failure does adopting the adopting the restorative model of post-hospital home care in comparison to not implementing any model impact the readmission rate during the first 30-days after hospital discharge?
Population – the population that is studied is those who are admitted to the hospital for a CHF diagnosis.
Intervention – the intervention is the restorative care model which is based on items adapted from behavioral change theory, goal attainment, nursing, rehabilitation, chronic care management, and geriatric medicine (Tinetti, et. al., 2012).
Comparison – the comparison is to not adopt the restorative care model in reducing readmission rates among CHF patients.
Outcome – does the intervention reduced readmissions? This is the primary question that needs to be answered related to the target population.
Timeframe – the timeframe that was selected for study, was 30-days after discharge. This was due to the fact that this is the timeframe that the Centers for Medicare and Medicaid have established for leveling a penalty at hospitals and providers who have rates of readmission prior to 30-days.
Synthesis of the Literature
There are several research studies that discuss readmission rates and CHF. The restorative care model is one suggested intervention that shows promise in effectively reducing readmission rates among CHF patients (Tinetti, et. al., 2012). This model involves reorienting the patient to the home care environment and familiarize clinicians with this home environment (Tinett, et. al., 2012). This is accomplished through Plan-Do-Study-Act cycles (Tinetti, et. al., 2012). McClintock, Mose & Smith (2014) recommend several strategies for reducing CHF patient readmissions including medication reconciliation, patient education for at least one hour, communication between patient, family, and healthcare team, and sufficient discharge planning to the home environment (p. 431). Because geriatric patients are more prone to readmissions, researchers suggest applying transitional care professionals to serve as a point of contact and support (Deniger, Trailer & Kennelty, 2015).
Risk prediction models can also help to determine which patients are more likely to be readmitted (Betihavas, Newton & Davidson, 2012). Risk models should target individuals who are at-risk and what can treatment and management activities should be adopted. Provider communication is another methodology that can be adopted to reduce readmission (Mansukhani, Bridgeman, Candelario, & Eckert, 2015). Direct communication among providers may help assist in ensuring the patient’s needs are met. Research also indicates that giving patient’s written information for their prescribed regiment can reduce the readmission rates as well (Gavgani, et. al., 2015). This reduces the costs of readmission and provides valuable information to patients. Economic, lifestyle, and socioeconomic variables can also have an impact on readmission rates (Bathaei, et. al., 2012).
Understanding the impact of these variables can help nurses to deliver appropriate care that reduces the potential for readmission. Informal and formal service use and joint use of information also helped to reduce patient readmission in patients who had CHF (Li, Morrow-Howell & Proctor, 2004). Specific tasks related to caring for patients helped to foster these reductions. Other recommendations specific to CHF patients was to assess renal function during hospitalization (Whittaker, Soine & Errico, 2015). This can help identify CHF patients who are prone to 30-day readmission risk. The specific statistics related to renal function can help practitioners to determine whether or not to discharge the patient (Whittaker, Soine & Errico, 2015). Following-up with patients, post-discharge can also help practitioners to determine if there are any issues that require additional attention, particularly for those patients who have compromised renal function.
Theoretical Framework
The framework that support this research is the restorative care model. The model is based on “geriatric medicine, nursing, rehabilitation, goal attainment, chronic care management, and behavioral change theory” (Tinetti, et. al., 2012, p. 1522). The model is comprised of several elements, including creating and implementing a cohesive plan of care that is underpinned with goal attainment, forming and agreeing on goals with input from family, the individual and the home care providers, rearranging the home care staff into an interdisciplinary team that is there to help the patient reach their goals, and defining clearly the roles and responsibilities of everyone (Tinetti, et. al., 2012). Further, the model will create a standardized evaluation for patient, including a report on progress, a change of focus to maximize self-care for the patient, and targeted treatment plans that address behavior modification, training, counseling, support, and medication management (Tinetti, et. al., 2012). This model will be applied to underpin the research question.
Practice Recommendations
There are several recommendations that can be integrated into practice based on the research. Practitioners should adopt the restorative care model which produces reduced rates of 30-day readmissions. Initially, patients with CHF can be targeted for the intervention and additional diagnoses can be integrated into the restorative care model approach. Research also supported providing written information about the diagnosis and treatment to the patient, and integrating a risk prediction model, may aid in identifying patients who are in need of these interventions due to their likelihood of a potential 30-day readmission. Finally, following-up with patients, post-discharge can help to determine their potential needs which aids in preventing potential readmission to the hospital facility.
References
Bathaei, A., Ashktorab, T., Anbuhi, S. Z., Ezati, J., & Majd, H. A. (2012). Use of logistic regression in surveying effective causes of readmission in patients with congestive heart failure. Qom University Of Medical Sciences Journal, 6(1), 10-10 1p.
Betihavas, V., Newton, P. J., & Davidson, P. M. (2012). An overview of risk prediction models and the implications for nursing practice. British Journal Of Cardiac Nursing, 7(6), 259-265 7p.
Deniger, A., Trailer, P., & Kennelty, K. A. (2015). Geriatric Transitional Care and Readmissions Review. Journal For Nurse Practitioners, 11(2), 248-252 5p. doi:10.1016/j.nurpra.2014.08.014
Gavgani, V. Z., Majd, F. K., Nosratnejad, S., Golmohammadi, A., & Sadeghi-Bazargani, H. (2015). The Efficacy of Written Information Intervention in Reduction of Hospital Re-admission Cost in Patients With Heart Failure; A Systematic Review and Meta-Analysis. Journal Of Cardiovascular & Thoracic Research, 7(1), 1-5 5p. doi:10.15171/jcvtr.2015.01
Li, H., Morrow-Howell, N., & Proctor, E. (2004). Post-acute home care and hospital readmission of elderly patients with congestive heart failure. Health & Social Work, 29(4), 275-285 11p
Mansukhani, R. P., Bridgeman, M. B., Candelario, D., & Eckert, L. J. (2015). Exploring Transitional Care: Evidence-Based Strategies for Improving Provider Communication and Reducing Readmissions. P&T: A Peer-Reviewed Journal For Managed Care & Formulary Management, 40(10), 690-694 5p.
McClintock, S., Mose, R., & Smith, L. F. (2014). Strategies for Reducing the Hospital Readmission Rates of Heart Failure Patients. Journal For Nurse Practitioners, 10(6), 430-433 4p. doi:10.1016/j.nurpra.2014.04.005
Rizzo, E. (2013, December 12). 6 Stats on the Cost of Readmission for CMS-Tracked Conditions. Retrieved from http://www.beckershospitalreview.com/quality/6-stats-on-the-cost-of-readmission-for-cms-tracked-conditions.html
Rodak, S. (2013, January 23). 20 Statistics on Hospital Readmissions. Retrieved from http://www.beckershospitalreview.com/quality/20-statistics-on-hospital-readmissions.html
Tinetti, M. E., Charpentier, P., Gottschalk, M., & Baker, D. I. (2012). Effect of a Restorative Model of Posthospital Home Care on Hospital Readmissions. Journal Of The American Geriatrics Society, 60(8), 1521-1526 6p. doi:10.1111/j.1532-5415.2012.04060.x
Whittaker, B. D., Soine, L. A., & Errico, K. M. (2015). Patient and process factors associated with all-cause 30-day readmission among patients with heart failure. Journal of The American Association Of Nurse Practitioners, 27(2), 105-113 9p. doi:10.1002/2327-6924.12123
Budget
Figure 1
Appendix A
NOTE: Order these appendices in the order in which they were referred to in the paper.
Summary of Primary Research Evidence (You may use the table from your NR701 course; this table may be single space)
Legend:
Appendix B
Summary of Systematic Reviews (SR) (this table may be single space)
Legend:
Appendix C
Project Schedule
Appendix D
Data Collection Tool for Evaluation (Use the name of the tool here)
