Abstract 11906: Heart Failure Admissions to General Medicine Services are Associated With Increased 30-day Readmission Rate

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Parag Goyal ◽  
Madeline Sterling ◽  
Ashley N Beecy ◽  
Savira Kochhar ◽  
John T Ruffino ◽  
...  
Keyword(s):  
Heart Failure ◽  
Readmission Rate ◽  
General Medicine ◽  
Structural Heart Disease ◽  
Multivariate Regression Analysis ◽  
Readmission Rates ◽  
Modifiable Factors ◽  
Patients With Heart Failure ◽  
Hospital Patients ◽  
Clinical Indices

Introduction: Hospitalists are increasingly caring for patients with heart failure (HF) at a time when there is need to identify modifiable factors associated with 30-day readmission rates. Hypothesis: Patients admitted to General Medicine services (GM) will have higher 30-day readmission rates than those admitted to Cardiology services. Methods: This retrospective cohort comprised patients with a principal diagnosis of HF discharged from GM or Cardiology services in 2013-2014 at an urban academic hospital. Patients discharged with hospice were excluded. Index hospitalizations and 30-day readmissions were identified via query of the electronic medical records. Demographics, clinical indices, and hospitalization characteristics were collected by chart review. Results: Among 926 patients admitted with HF, 40% were admitted to GM and 60% were admitted to a Cardiology service. Patients on GM were slightly older, more likely female, and more likely to have Medicare (Table). They also had higher LVEF, less RV dysfunction, and less ventricular tachycardia (VT). Rates of non-cardiac comorbidities were comparable between groups. Patients on GM experienced a 1.4-fold increased 30-day readmission rate compared to those on Cardiology services (32% vs. 23%, p=0.023). Multivariate regression analysis showed that admission to GM remained a predictor for 30-day readmission (OR 1.37, [1.01 to 1.87], p=0.048) after controlling for key differences between groups including age, sex, insurance, LVEF, RV dysfunction, VT, and admission blood pressure and hemoglobin. Conclusions: HF patients admitted to General Medicine have less structural heart disease, and yet have a higher rate of 30-day readmission compared to those admitted to Cardiology services. This underscores the importance of ensuring that hospitalists obtain adequate heart failure training (related to both inpatient care and optimization of discharge regimens), so as to avoid un-necessary readmissions.

Impact of a pharmacy team–led intervention program on the readmission rate of elderly patients with heart failure

2018 ◽  
Vol 75 (4) ◽  
pp. 183-190 ◽  
Author(s):  
Pamela M. Moye ◽  
Pui Shan Chu ◽  
Teresa Pounds ◽  
Maria Miller Thurston
Keyword(s):  
Heart Failure ◽  
Older Patients ◽  
Readmission Rate ◽  
Academic Medical Center ◽  
Hospital Readmissions ◽  
Intervention Group ◽  
Historical Control Group ◽  
Historical Control ◽  
Control Group ◽  
Patients With Heart Failure

Purpose The results of a study to determine whether pharmacy team–led postdischarge intervention can reduce the rate of 30-day hospital readmissions in older patients with heart failure (HF) are reported. Methods A retrospective chart review was performed to identify patients 60 years of age or older who were admitted to an academic medical center with a primary diagnosis of HF during the period March 2013–June 2014 and received standard postdischarge follow-up care provided by physicians, nurses, and case managers. The rate of 30-day readmissions in that historical control group was compared with the readmission rate in a group of older patients with HF who were admitted to the hospital during a 15-month intervention period (July 2014–October 2015); in addition to usual postdischarge care, these patients received medication reconciliation and counseling from a team of pharmacists, pharmacy residents, and pharmacy students. Results Twelve of 97 patients in the intervention group (12%) and 20 of 80 patients in the control group (25%) were readmitted to the hospital within 30 days of discharge (p = 0.03); 11 patients in the control group (55%) and 7 patients in the intervention group (58%) had HF-related readmissions (p = 0.85). Conclusion In a population of older patients with HF, the rate of 30-day all-cause readmissions in a group of patients targeted for a pharmacy team–led postdischarge intervention was significantly lower than the all-cause readmission rate in a historical control group.

Abstract P216: Heart Failure Readmission Rates: Experience of St John's Physician Group Practice Demonstration

2011 ◽  
Vol 4 (suppl_2) ◽  
Author(s):  
Joseph P Drozda ◽  
Donna A Smith ◽  
Paul C Freiman ◽  
Jeffrey A VanSlette ◽  
Timothy R Smith
Keyword(s):  
Heart Failure ◽  
Readmission Rate ◽  
Group Practice ◽  
Data Sets ◽  
Disease Registry ◽  
Readmission Rates ◽  
Annual Average ◽  
Physician Group ◽  
Period 2 ◽  
Artery Disease

Objective: The appropriateness of using readmission rates alone as markers of the quality of Heart Failure (HF) care has been questioned. The HF program of St. John's Health System's Physician Group Practice (PGP) Demonstration provided an opportunity to assess a number of outcomes that help to put readmission rates in context. The HF program included disease and case management and a disease registry in the PCP office. Methods: Several data sets were analyzed including the EHR, an inpatient database, the disease registry, and the Social Security Death Master File. Traditional Medicare patients admitted to St. John's Hospital from 2000 to 2010 with a diagnosis of HF, were included resulting in data for 5 years before (Period 1) and 5 years after (Period 2) the 2005 inception of PGP. Results: Total admissions were 3559 in Period 1 and 3514 in Period 2. The prevalence of 3 co-morbid conditions in admitted patients increased during Period 2 [diabetes 35.3% (1256/3559) to 42.7% (1499/3514), p<0.001; hypertension 54.8% (1952/3559) to 70.4% (2475/3514), p<0.0001; and coronary artery disease 62.7% (2253/3559) to 66.4% (2332/3514), p=0.015] indicating that patients were getting more complex. HF admissions trended down significantly from Period 1 (709 annual average) to 2009 (637, p=0.007). The 30 day all cause readmission rate dropped in 2005 [16.9% (137/809)] from Period 1 [annual average 18.8% (671 / 3559), p=0.04] and remained stable thereafter [annual average 16.9% (595/3514)]. The 30 day mortality rate was flat from 2000 to 2009 [2.7(15/550)-5.0% (30/597), p=0.3] and increased in 2010 [8.6% (28/327), p<0.0001]. The use of pacemakers and ICDs was unchanged during Period 2 but ACE inhibitor and beta blocker use increased in PGP practices during 2005 and was constant thereafter. Conclusions: The HF program implemented by this PGP project was associated with decreased HF admissions and with increased clinical complexity of admitted patients. Despite this increasing complexity, the 30 day all cause readmission rate dropped in the first year of the program and remained stable thereafter. Finally, 30 day mortality rates were not adversely affected until the last year of the program. The increased mortality in 2010 may be due to a change in case mix but remains unexplained.

scholarly journals Patient engagement with digital disease management and readmission rates: The case of congestive heart failure

2021 ◽  
Vol 27 (3) ◽  
pp. 146045822110309
Author(s):  
Rudin Gjeka ◽  
Kirit Patel ◽  
Chandra Reddy ◽  
Nora Zetsche
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Disease Management ◽  
Readmission Rate ◽  
Hospital Readmissions ◽  
The Elderly ◽  
Readmission Rates ◽  
Management Platform ◽  
High Readmission Rate ◽  
Remote Patient

Congestive heart failure (CHF) is one of the most common diagnoses in the elderly United States Medicare (⩾ age 65) population. This patient population has a particularly high readmission rate, with one estimate of the 6-month readmission rate topping 40%. The rapid rise of mobile health (mHealth) presents a promising new pathway for reducing hospital readmissions of CHF, and, more generally, the management of chronic conditions. Using a randomized research design and a multivariate regression model, we evaluated the effectiveness of a hybrid mHealth model—the integration of remote patient monitoring with an applied health technology and digital disease management platform—on 45-day hospital readmissions for patients diagnosed with CHF. We find a 78% decrease in the likelihood of CHF hospital readmission for patients who were assigned to the digital disease management platform as compared to patients assigned to control.

Abstract P096: Effectiveness of a Comprehensive Care Delivery System on Readmission Rates and Self-Care in Older Adult Patients with Heart Failure

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Linda L Tavares
Keyword(s):  
Heart Failure ◽  
Older Adult ◽  
Delivery System ◽  
Care Delivery ◽  
Self Care ◽  
Comprehensive Care ◽  
Remote Patient Monitoring ◽  
Readmission Rates ◽  
Patients With Heart Failure ◽  
Remote Patient

Background: Telemedicine interventions to prevent readmissions in patients with heart failure (HF) have shown inconsistent results in their effectiveness on HF-related and all-cause rehospitalization. Team-based interventions geared toward patient-centric care delivery in concert with comprehensive care coordination that enhances patient self-care may help to prevent unplanned hospitalizations in patients with HF. Objective: To evaluate the outcomes of a comprehensive care delivery system using a team-based high-touch coaching and remote patient monitoring intervention designed for older adult patients with heart failure in a community hospital setting. Design: A descriptive cross-sectional observational design was used to measure readmission rates. A one-group pretest-posttest design using the Self-care of Heart Failure Index was used to measure self-care outcomes. Correlation analysis was performed to determine relationships between the coaching and outcomes. Patients: Participants were older adult patient hospitalized with heart failure and followed for 30-days. Patients were excluded if they were unwilling to participate, non- English speaking, had end-stage renal disease, a terminal illness, debilitating neuro-psychological disorder, or lived greater than 30 miles away. Results: The 30-patients were primarily Caucasian, female with a mean age of 77.5 years. The majority of patients had medically optimized NYHA class II or III HF with an ejection fraction ≤ 40%. HF readmission rate was zero, and 6% for all cause. Patient self-care scores improved (p < .0001). Team based coaching was correlated with improvement in self-care maintenance scores (p =.009). Conclusion: A comprehensive care delivery system leveraging remote patient monitoring and health coaching significantly reduced 30-day readmission and enhanced patient self-care management. Implications: Patient centric team based care models leveraging technology should continue to be developed and implemented to transform care delivery for older adults with HF. Table 1. Change in Mean Self-Care of Heart Failure Index Scores p < .0001 p < .0001 p < .0001

Relation between process measures and diagnosis-specific readmission rates in patients with heart failure

Heart ◽  
2015 ◽  
Vol 101 (21) ◽  
pp. 1704-1710 ◽  
Author(s):  
Alex Bottle ◽  
Rosalind Goudie ◽  
Martin R Cowie ◽  
Derek Bell ◽  
Paul Aylin
Keyword(s):  
Heart Failure ◽  
Readmission Rates ◽  
Process Measures ◽  
Patients With Heart Failure

P25 Characteristics of patients with heart failure attended at general medicine departments

2003 ◽  
Vol 14 ◽  
pp. S40
Author(s):  
B. Roca ◽  
J. Forteza-Rey ◽  
J.J. Jusdado ◽  
D. Carnevali ◽  
P. Conthe
Keyword(s):  
Heart Failure ◽  
General Medicine ◽  
Patients With Heart Failure

scholarly journals A Case-Control Study: The Impact of Unintentional Discrepancies and Pharmacist Discharge Prescription Review on 30-Day Hospital Readmission

2020 ◽  
Vol 11 ◽  
pp. 215013272093201
Author(s):  
Ali Elbeddini ◽  
Lucy Yang ◽  
Ahmed Aly
Keyword(s):  
Risk Factors ◽  
Readmission Rate ◽  
Case Control Study ◽  
General Medicine ◽  
Case Control ◽  
Readmission Rates ◽  
Medication Discrepancies ◽  
The Relationship ◽  
Discharge Prescription ◽  
Control Study

Introduction: Medication discrepancies on hospital discharge are common and occur despite the use of technology to generate electronically created discharge (e-discharge) prescriptions, justifying pharmacist involvement. No published studies have focused on medication discrepancies as a risk factor for readmission. The aim was to explore the relationship between medication discrepancies on discharge and readmission rates, and how both are affected by pharmacist intervention. Objectives: The primary objective was to establish the relationship between medication discrepancies on the e-discharge prescription and hospital readmissions within 30 days of discharge. Secondary objectives were to determine the 30-day readmission rate with and without pharmacist involvement, and risk factors for 30-day readmission. Methods: This was a matched case-control study where cases and controls consisted of patients readmitted and not readmitted to hospital within 30 days of discharge from the general medicine service, respectively. Case patients were defined as patients who had been readmitted to the hospital within 30 days of discharge from the general medicine unit. Control patients were defined as patients who had not been readmitted to the hospital within 30 days of discharge. Chi-square statistics was used to analyze the association between the presence of medication discrepancy at discharge and 30-day readmission. Multivariate logistic regression was used to further analyze the associations to determine which risk factors best relate to 30-day readmission. Results: Between January 1, 2017 and December 31, 2017, a total of 401 e-discharge prescriptions were reviewed, and 194 cases were readmitted within 30 days of discharge. Similar proportions of patients were readmitted compared with not readmitted regardless of whether discrepancies were identified on the e-discharge prescriptions, and there was no relationship identified between medication discrepancies and readmission within 30 days (odds ratio [OR] = 1.04; P = .854). The readmission rate with and without pharmacist involvement was similar between the case group (50%) and control group (48.0%). The proportion of discharge prescriptions with discrepancies was 48.8% in the group that had pharmacist involvement and 47.0% in the group that had no pharmacist involvement. Additionally, a LACE score of 12 or greater was identified as a statistically significant risk factor for readmission (OR = 2.13; P < .001). Conclusions: Pharmacist review of the e-discharge prescription did not affect the readmission rate. A LACE score of 12 or greater was associated with a higher risk of readmission. Future studies are needed to identify patient groups at high risk of readmission and to determine pharmacist interventions that could reduce readmission rates.

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