Abstract 23: Reducing Stroke Readmissions Utilizing a Home Care Based Transitions Coaching Program

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Ann M Leonhardt Caprio ◽  
Denise M Burgen ◽  
Curtis G Benesch
Keyword(s):  
Ischemic Stroke ◽  
Home Care ◽  
Hospital Readmissions ◽  
Care Transitions ◽  
Hospital Inpatient ◽  
Pilot Program ◽  
Readmission Rates ◽  
Specific Patient ◽  
Care Agency ◽  
Home Care Agency

Background: The Center for Medicare and Medicaid Services (CMS) has instituted utilization of all-cause, unplanned 30 day hospital readmissions following discharge for ischemic stroke as part of the Hospital Inpatient Quality Reporting Program. While readmission reduction following stroke is a hospital imperative, there is minimal evidence on stroke-specific readmission reduction programs. Purpose: We sought to reduce 30 day readmissions following ischemic stroke through utilization of an established care transitions program in collaboration with our institution’s affiliated home care agency. Methods: Our institution’s home care agency has reduced readmission rates in the general medical population utilizing the Coleman Care Transitions Model © . This model incorporates motivational interviewing in visits prior to hospital discharge, with a home visit 24 to 48 hours after discharge, and by telephone at least weekly by a trained transitions coach. The coach ensures understanding of medications, follow up visits, and recognition of red flag symptoms. A one year pilot program for stroke patients utilizing this established program was initiated in October 2015. Basic stroke training was provided for all coaching staff. Quarterly readmission rates for 1 year prior to the intervention and 6 months following were analyzed. Results: During the first 6 months of the pilot program 18.2% of patients discharged with a diagnosis of ischemic stroke qualified for and completed the coaching program. Of those in the program 3.3% were readmitted. Overall, there were 15 readmissions in 13 patients, 85% of whom did not receive transitions coaching services. The readmission rate in the year prior to intervention was 7.8%, in the 6 months following 4.5%. These findings represent a 42.7% overall reduction in readmissions (p = 0.06) and a treatment effect of 1.7. Conclusions: Utilizing the Coleman Care Transitions Model © led to a meaningful reduction of hospital readmissions for patients with ischemic stroke in this pilot program. In an area in which readmission reduction has proven challenging, expanding the availability of a home care based program for specific patient populations may be an effective strategy.

Abstract TMP77: Development of a Collaborative Transition Coaching Program for Reduction of Post-stroke Hospitalizations

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Ann M Leonhardt ◽  
Denise M Burgen ◽  
Jennifer Wolfe ◽  
Kelly Luther
Keyword(s):  
Ischemic Stroke ◽  
Home Care ◽  
Hospital Readmission ◽  
Fiscal Year ◽  
Pilot Program ◽  
Stroke Patients ◽  
Stroke Population ◽  
Essential Components ◽  
Care Agency ◽  
Home Care Agency

Issue: All-cause 30 day hospital readmission rate following discharge for ischemic stroke has been instituted by CMS as a quality measure. Successful readmission reduction planning is a hospital imperative. Purpose: We set out to establish a stroke-specific transitions coaching program with the intention of decreasing readmissions in our ischemic stroke population. Methods: Fiscal year 2013 stroke readmissions to our hospital were individually reviewed for factors leading to readmission. After determining 62.5% of avoidable readmissions were attributed to outpatient factors, a regional home care agency was contacted for collaboration. The agency has proven readmission reductions utilizing the Coleman Care Transitions Model. This model incorporates visits prior to discharge, by telephone, and at home by a trained transitions coach to ensure understanding of medications, follow up visits, and recognition of concerning symptoms. Cost estimates for expanding the program to stroke patients were made using the prior year’s volume based on primary payer, county, and discharge destination. A business plan was established and training and informational sessions planned. Results: Of the outpatient factors contributing to readmission the most common were medication issues, seeking emergency care prematurely, and need for education or support. Based on the data and prior successes of the home care agency a pilot program was developed. The estimated cost for patients not covered by their primary insurance is $52,000 annually. The estimated cost for one hospital readmission is $11,200. Preventing 5 readmissions per year would save $56,000. A successful collaborative was formed resulting in the ability to enroll a larger number of ischemic stroke patients in the transitions coaching program. Conclusions: Solving the problem of readmissions after ischemic stroke is complex and requires extensive planning and collaboration. Identifying our issues and establishing a pilot program took nearly a year. Key stakeholders and a committed team are essential components of establishing a collaborative process of this magnitude. The pilot program will be evaluated by comparting readmission rates in the ischemic stroke population pre and post initiation.

scholarly journals Facilitating co-production in public services: Empirical evidence from a co-design experience with family caregivers living in a remote and rural area

2020 ◽  
pp. 095148482097145
Author(s):  
Eleonora Gheduzzi ◽  
Niccolò Morelli ◽  
Guendalina Graffigna ◽  
Cristina Masella
Keyword(s):  
Home Care ◽  
Family Caregivers ◽  
Empirical Evidence ◽  
Rural Area ◽  
Public Service ◽  
Rural Areas ◽  
Crucial Role ◽  
Care Agency ◽  
Home Care Agency ◽  
Design Experience

The involvement of vulnerable actors in co-production activities is a debated topic in the current public service literature. While vulnerable actors should have the same opportunities to be involved as other actors, they may not have the needed competences, skills and attitudes to contribute to this process. This paper is part of a broader project on family caregivers’ engagement in remote and rural areas. In particular, it investigates how to facilitate co-production by looking at four co-design workshops with family caregivers, representatives of a local home care agency and researchers. The transcripts of the workshops were coded using NVivo, and the data were analysed based on the existing theory about co-production. Two main findings were identified from the analysis. First, the adoption of co-production by vulnerable actors may occur in conjunction with other forms of engagement. Second, the interactions among facilitators and providers play a crucial role in encouraging the adoption of co-production. We identified at least two strategies that may help facilitators and providers achieve that goal. However, there is a need for an in-depth understanding of how facilitators and providers should interact to enhance implementation of co-production.

Abstract WMP94: Readmission Within 30 days After Acute Ischemic Stroke, United States 2013

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Xin Tong ◽  
Mary G George ◽  
Sallyann M Coleman King ◽  
Cathleen Gillespie ◽  
Robert Merritt
Keyword(s):  
United States ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Readmission Rate ◽  
Hospital Readmissions ◽  
The United States ◽  
Artery Occlusion ◽  
Principal Diagnosis ◽  
Readmission Rates ◽  
The Cost

Introduction: Hospital readmissions contribute significantly to the cost of medical care and reflect the burden of disease. Limited data have been reported on national hospital readmission after acute ischemic stroke. Methods: Among 2013 adult hospitalizations from the National Inpatient Sample of the Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD), we identified acute ischemic stroke (AIS) hospitalizations using principal diagnosis ICD-9-CM codes. We provided national estimates of AIS non-elective readmission rates within 30 days. Results: In 2013, there were a total of 489,813 adult index AIS admissions in the United States. The readmission rate within 30 days for a new AIS as the principal diagnosis was 2.1% of index AIS admissions, and was 10.2% of all readmissions. The readmission rate for all non-elective reasons increased with age, with the lowest readmission rate (8.9%) among ages 18-44, and the highest (11.7%).among ages 85+. The readmission rate was higher among patients with public insurance (11.1%) as compared to private (7.4%) or others (7.9%). Recurrent AIS (20.2%) was the most common reason for readmission, including unspecified cerebral artery occlusion with infarction (ICD9-CM=434.91, 13.0%) and cerebral embolism with infarction (ICD9-CM=434.11, 3.1%). In addition, infections were among the most common causes (Septicemia 5.7%, UTI 2.7%, and pneumonia 2.2%) and TIA (2.4%). Conclusions: The findings have important implications for identifying groups and conditions at high-risk for readmission. The large number of recurrent AIS within 30 days of index AIS highlights the need for improved patient follow-up and secondary prevention treatment.

Right TraC™ Post-Hospitalization Care Transitions Program to Reduce Readmissions for Hemodialysis Patients

2017 ◽  
Vol 45 (6) ◽  
pp. 532-539 ◽  
Author(s):  
Rebecca L. Wingard ◽  
Kathryn McDougall ◽  
Billie Axley ◽  
Andrew Howard ◽  
Cathleen O''Keefe ◽  
...  
Keyword(s):  
Hospital Readmission ◽  
Information Exchange ◽  
Repeated Measures ◽  
Hospital Readmissions ◽  
Care Transitions ◽  
Readmission Rates ◽  
Hospitalization Rates ◽  
Hospital Readmission Rates ◽  
Nonrandomized Trial

Background: Hemodialysis (HD) patients have high hospitalization rates. This nonrandomized trial tested the effect of a bundle of renal-specific “Right TraC™” strategies on 30-day all-cause readmission rates and, secondarily, 90-day readmissions and overall admissions among HD patients. Methods: Twenty-six Fresenius clinics in West Virginia, Ohio, and Kentucky participated in the interventions. Eighteen matched clinics served as controls; intervention clinics also served as their own controls. We deployed the intervention in 3 incremental phases focused on patient information exchange, post-hospital follow-up, and telephonic case management. Thirty-day hospital readmissions per patient year (ppy) were calculated by dividing the total number of readmissions within 30 days of index admission by the total number of patient-years in baseline (2012) and remeasurement (2014) periods. We also compared readmission rates from 2010 to 2015. We used repeated measures Poisson regression to compare outcomes between groups and time periods. Results: From 2012 to 2014, 30-day all-cause readmissions ppy declined for Right TraC clinics (from 0.88 to 0.66 [p < 0.001]; for controls, from 0.73 to 0.61 [p = 0.16]). Difference in change between groups was nonsignificant (p = 0.26). Overall admissions ppy declined: for Right TraC clinics from 2.51 to 1.97 (p < 0.001); for controls from 2.14 to1.92 (p = 0.21); difference in change between groups was significant (p = 0.01). For 2010, 2011, and 2012, Right TraC clinic 30-day readmissions ppy were unchanged: 0.89, 1.00, 0.88 (p = 0.61 and p = 0.49); they declined to 0.66 (p < 0.001) in 2014 (intervention year); rose to 0.70 (p = 0.06) in 2015 (interventions discontinued). Conclusion: We conclude that Right TraC interventions may have been helpful in reducing hospital readmission rates.

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