Effectiveness of Motivational Interviewing in Decreasing Hospital Readmission in Adults With Heart Failure and Multimorbidity.
ABSTRACT: Hospitalizations are common in heart failure (HF). Multimorbidity, defined as ?2 comorbid conditions, drives many readmissions. The purpose of this pilot study was to test the effectiveness of motivational interviewing (MI) in decreasing these hospital readmissions. We enrolled 100 hospitalized HF patients into a randomized controlled trial, randomizing in a 2:1 ratio: intervention (n = 70) and control (n = 30). The intervention group received MI tailored to reports of self-care during one home visit and three to four follow-up phone calls. After 3 months, 34 participants had at least one hospital readmission. The proportion of patients readmitted for a condition unrelated to HF was lower in the intervention (7.1%) compared with the control group (30%, p = .003). Significant predictors of a non-HF readmission were intervention group, age, diabetes, and hemoglobin. Together, these variables explained 35% of the variance in multimorbidity readmissions. These preliminary results are promising in suggesting that MI may be an effective method of decreasing multimorbidity hospital readmissions in HF patients.
Project description:OBJECTIVE:To investigate whether hospital readmission after admission for heart failure (HF), myocardial infarction (MI), and pneumonia varies by season. DATA SOURCES:All patients in 2005-2009 Healthcare Cost and Utilization Project State Inpatient Databases for New York and California hospitalized for HF, MI, or pneumonia. STUDY DESIGN:The relationship between discharge season and unplanned readmission within 30 days was evaluated using multivariate modified Poisson regression. PRINCIPAL FINDINGS:Cohorts included 869,512 patients with HF, 448,945 patients with MI, and 813,593 patients with pneumonia. While admissions varied widely by season, readmission rates only ranged from 25.0 percent (spring) to 25.6 percent (winter) for HF (p > .05), 18.9 percent (summer) to 20.0 percent (winter) for MI (p < .001), and 19.4 percent (spring) to 20.3 percent (summer) for pneumonia (p < .001). In adjusted models, in New York, there was lower readmission in spring and fall (RR: 0.98, 95% CI: 0.96-0.99 for both) after admission for HF and higher readmission in spring (RR: 1.04, 95% CI: 1.01-1.07) after MI. In California, there was lower readmission in spring and winter (RR: 0.95, 95% CI: 0.93-0.96 and RR: 0.96, 95% CI: 0.94-0.98, respectively) after pneumonia. CONCLUSIONS:Given marked seasonality in incidence and mortality of HF, MI, and pneumonia, the modest seasonality in readmissions suggests that readmissions may be more related to non-seasonally dependent factors than to the seasonal nature of these diseases.
Project description:To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race.To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia.We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge.We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing.From 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race.Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.
Project description:OBJECTIVES:To (1) compare the 2015 hospital grades reported on Medicare's Hospital Compare website for heart failure (HF) and acute myocardial infarction (AMI) readmissions with the HF- and AMI-specific scores for excess readmissions used to assess Medicare readmission penalties and (2) assess how often hospitals were penalized for excess readmissions in only 1 or 2 conditions, given that hospitals received a penalty impacting all Medicare payments based on an overall readmission score calculated from 5 conditions (HF, AMI, pneumonia, chronic obstructive pulmonary disease, and total hip/knee arthroplasty). STUDY DESIGN:Retrospective secondary data analysis. METHODS:Descriptive analyses of hospital-specific, condition-specific grades and excess readmission scores and hospital-level penalties downloaded from Hospital Compare. RESULTS:Of the 2956 hospitals that had publicly reported HF grades on Hospital Compare, 91.9% (2717) were graded as "no different" than the national rate for HF readmissions, which included 48.6% that were scored as having excessive HF admissions, and 87% received an overall readmission penalty. Of 120 (4.1%) hospitals graded as "better" than the national rate for HF, none were scored as having excessive HF readmissions and 50% were penalized. AMI data yielded similar results. Among 2591 hospitals penalized for overall readmissions, 26.6% had only 1 condition with excess readmissions and 27.5% had 2 conditions. CONCLUSIONS:Many hospitals with an HF and AMI readmission grade of "no different" than the national rate on Hospital Compare received penalties for excessive readmissions under the Hospital Readmissions Reduction Program. The value signal to consumers and hospitals communicated by grades and penalties is therefore weakened because the methods applied to the same hospital data produce conflicting messages of "average grades" yet "bad enough for penalty."
Project description:OBJECTIVE: To test a multidisciplinary approach to reduce heart failure (HF) readmissions that tailors the intensity of care transition intervention to the risk of the patient using a suite of electronic medical record (EMR)-enabled programmes. METHODS: A prospective controlled before and after study of adult inpatients admitted with HF and two concurrent control conditions (acute myocardial infarction (AMI) and pneumonia (PNA)) was performed between 1 December 2008 and 1 December 2010 at a large urban public teaching hospital. An EMR-based software platform stratified all patients admitted with HF on a daily basis by their 30-day readmission risk using a published electronic predictive model. Patients at highest risk received an intensive set of evidence-based interventions designed to reduce readmission using existing resources. The main outcome measure was readmission for any cause and to any hospital within 30 days of discharge. RESULTS: There were 834 HF admissions in the pre-intervention period and 913 in the post-intervention period. The unadjusted readmission rate declined from 26.2% in the pre-intervention period to 21.2% in the post-intervention period (p=0.01), a decline that persisted in adjusted analyses (adjusted OR (AOR)=0.73; 95% CI 0.58 to 0.93, p=0.01). In contrast, there was no significant change in the unadjusted and adjusted readmission rates for PNA and AMI over the same period. There were 45 fewer readmissions with 913 patients enrolled and 228 patients receiving intervention, resulting in a number needed to treat (NNT) ratio of 20. CONCLUSIONS: An EMR-enabled strategy that targeted scarce care transition resources to high-risk HF patients significantly reduced the risk-adjusted odds of readmission.
Project description:The US Centers for Medicare and Medicaid Services Hospital Readmissions Reduction Program penalizes hospitals with higher-than-expected risk-adjusted 30-day readmission rates (excess readmission ratio [ERR]?>?1) after acute myocardial infarction (MI). However, the association of ERR with MI care processes and outcomes are not well established.To evaluate the association between ERR for MI with in-hospital process of care measures and 1-year clinical outcomes.Observational analysis of hospitalized patients with MI from National Cardiovascular Data Registry/Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With the Guidelines centers subject to the first cycle of the Hospital Readmissions Reduction Program between July 1, 2008, and June 30, 2011.The ERR for MI (MI-ERR) in 2011.Adherence to process of care measures during index hospitalization in the overall study population and risk of the composite outcome of mortality or all-cause readmission within 1 year of discharge and its individual components among participants with available Centers for Medicare and Medicaid Services-linked data.The median ages of patients in the MI-ERR greater than 1 and tertiles 1, 2, and 3 of the MI-ERR greater than 1 groups were 64, 63, 64, and 63 years, respectively. Among 380 hospitals that treated a total of 176?644 patients with MI during the study period, 43% had MI-ERR greater than 1. The proportions of patients of black race, those with heart failure signs at admission, and bleeding complications increased with higher MI-ERR. There was no significant association between adherence to MI performance measures and MI-ERR (adjusted odds ratio, 0.94; 95% CI, 0.81-1.08, per 0.1-unit increase in MI-ERR for overall defect-free care). Among the 51?453 patients with 1-year outcomes data available, higher MI-ERR was associated with higher adjusted risk of the composite outcome and all-cause readmission within 1 year of discharge. This association was largely driven by readmissions early after discharge and was not significant in landmark analyses beginning 30 days after discharge. The MI-ERR was not associated with risk for mortality within 1 year of discharge in the overall and 30-day landmark analyses.During the first cycle of the Hospital Readmissions Reduction Program, participating hospitals' risk-adjusted 30-day readmission rates following MI were not associated with in-hospital quality of MI care or clinical outcomes occurring after the first 30 days after discharge.
Project description:AIMS:Heart failure (HF) readmission commonly arises owing to insufficient patient knowledge and failure of recognition of the early stages of recurrent fluid congestion. In previous work, we developed a score to predict short-term hospital readmission and showed that higher-risk patients benefit most from a disease management programme (DMP) that included enhancing knowledge and education by a nurse. We aim to evaluate the effectiveness of a novel, nurse-led HF DMP in selected patients at high risk of short-term hospital readmission, using ultrasound-guided diuretic management and artificial intelligence to enhance HF knowledge in an outpatient setting. METHODS AND RESULTS:Risk-HF is a prospective multisite randomized controlled trial that will allocate 404 patients hospitalized with acute decompensated HF, and ?33% risk of readmission and/or death at 30 days, into risk-guided nurse intervention (DMP-Plus group) compared with usual care. Intervention elements include (i) fluid management with a handheld ultrasound (HHU) device at point of care; (ii) post-discharge follow-up; (iii) optimal programmed drug titration; (iv) better transition of care; (v) intensive self-care education via an avatar-based 'digital health coach'; and (vi) exercise guidance through the digital coach. Usual care involves standard post-discharge hospital care. The primary outcome is reduced death and/or hospital readmissions at 30 days post-discharge, and secondary outcomes include quality of life, fluid management efficacy, and feasibility and patient engagement. Assuming that our intervention will reduce readmissions and/or deaths by 50%, with a 1:1 ratio of intervention vs. usual care, we plan to randomize 404 patients to show a difference at a statistical power of 80%, using a two-sided alpha of 0.05. We anticipate this recruitment will be achieved by screening 2020 hospitalized HF patients for eligibility. An 8 week pilot programme of our digital health coach in 21 HF patients, age > 75 years, showed overall improvements in quality of life (13 of 21), self-care (12 of 21), and HF knowledge (13 of 21). A pilot of the use of HHU by nurses showed that it was feasible and accurate. CONCLUSIONS:The Risk-HF trial will evaluate the effectiveness of a risk-guided intervention to improve HF outcomes and will evaluate the efficacy of trained HF nurses delivering a fluid management protocol that is guided by lung ultrasound with an HHU at point of care.
Project description:Background Readmission after myocardial infarction ( MI ) is a publicly reported quality metric with hospital reimbursement linked to readmission rates. We describe the timing and pattern of readmission by cause within the first year after MI in consecutive patients, regardless of revascularization strategy, payer status, or age. Methods and Results We identified patients discharged after an MI from April 2008 to June 2012. Readmission within 12 months was the primary end point. Readmissions were classified into 4 groups: MI related, other cardiovascular, noncardiovascular, and planned. A total of 3069 patients were discharged after an MI (average age, 65±13 years; and 1941 [63%] men). A total of 655 patients (21.3%) were readmitted at least once (897 total readmissions). A total of 147 patients (4.8%) were readmitted ≥2 times, accounting for 389 readmissions (43%). The instantaneous risk of all-cause readmission was highest (15 readmissions/100 patients per month; 95% confidence interval, 12-19 readmissions/100 patients per month) immediately after discharge, decreased by almost half (8.1 readmissions/100 patients per month; 95% confidence interval, 7.2-9.0 readmissions/100 patients per month) within 15 days, and was substantially lower and relatively constant (1.4 readmissions/100 patients per month; 95% confidence interval, 1.2-1.6 readmissions/100 patients per month) out to 1 year. Cardiovascular causes of readmission were more common early after discharge. Conclusions Most patients with MI are never readmitted, whereas a small minority (≈5%) account for nearly half of 1-year readmissions. The readmission pattern after MI is characterized by an early peak (first 15 days) of cardiovascular readmissions, followed by a middle period (months 1-4) of noncardiovascular readmissions, and ending with a low-risk period (>4 months) during which the risk appears independent of cause.
Project description:BACKGROUND:The Medicare Hospital Readmissions Reduction Program has led to fewer readmissions following hospitalizations with a principal diagnosis of heart failure (HF). Patients with HF are frequently hospitalized for other causes. OBJECTIVES:This study sought to compare trends in Medicare risk-adjusted, 30-day readmissions following principal HF hospitalizations and other hospitalizations with HF. METHODS:This was a retrospective study of 12,973,853 Medicare hospitalizations with a principal or secondary diagnosis of HF between January 2008 and June 2015. Hospitalizations were categorized as follows: principal HF hospitalizations; principal acute myocardial infarction or pneumonia hospitalizations with secondary HF; and other hospitalizations with secondary HF. The study examined trends in risk-adjusted, 30-day, all-cause readmission rates for each cohort and trends in differences in readmission rates among cohorts by using linear spline regression models. RESULTS:Before passage of the Affordable Care Act in March 2010, risk-adjusted, 30-day readmission rates were stable for all 3 cohorts, with mean monthly rates of 26.1%, 24.9%, and 24.4%, respectively. Risk-adjusted readmission rates started declining after passage of the Affordable Care Act by 1.09% (95% confidence interval [CI]: 0.51% to 1.68%), 1.24% (95% CI: 0.92% to 1.57%), and 1.05% (95% CI: 0.52% to 1.58%) per year, respectively, until implementation of the Hospital Readmissions Reduction Program in October 2012 and then stabilized for all 3 cohorts. CONCLUSIONS:Patients with HF are often hospitalized for other causes, and these hospitalizations have high readmission rates. Policy changes led to decreases in readmission rates for both principal and secondary HF hospitalizations. Readmission rates in both groups remain high, suggesting that initiatives targeting all hospitalized patients with HF continue to be warranted.
Project description:Background When patients require readmission after a recent myocardial infarction (MI), returning to the discharging (index) hospital may be associated with better outcomes as a result of greater continuity in care. However, little evidence exists to answer this frequent patient question. Methods and Results Among Medicare patients aged ?65 years discharged home alive post-MI from 491 US hospitals in the ACTION (Acute Coronary Treatment Intervention Outcomes Network) Registry, we compared reason for readmission, duration of rehospitalization, and 30-day mortality between patients readmitted to the index versus nonindex hospital within 30 days of index MI discharge. Among 53 471 MI patients, 7715 (14%) were readmitted within 30 days, and most readmitted patients (73%) returned to the discharging hospital. Reason for readmission was not significantly associated with location of readmission. In multivariable modeling, the strongest factors associated with readmission to a nonindex hospital were distance from the discharging hospital, transfer-in during the index MI hospitalization, and frequency of nonindex hospital admissions in the year preceding to the index MI. Duration of rehospitalization did not differ significantly between patients readmitted to the index versus nonindex hospital (median, 4 versus 3 days; <i>P</i>=0.17). Mortality risk was also not significantly different between patients readmitted to the index versus nonindex hospital overall (7.4 versus 7.7%; adjusted odds ratio, 0.89; 95% CI, 0.73-1.10) and when stratified by reason for readmission (<i>P</i> for interaction=0.61). Conclusions Post-MI readmissions did not differ in reason for readmission, duration of rehospitalization, or associated mortality when compared between patients who returned to the discharging hospital and those who sought care elsewhere.
Project description:OBJECTIVES:Variation in hospital resource allocations across weekdays and weekends have led to studies of the 'weekend effect' for ST elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI), heart failure (HF) and stroke. However, few studies have explored the 'weekend effect' on unplanned readmission. We aimed to investigate 30-day unplanned readmissions and processes of care across weekend and weekday hospitalisations for STEMI, NSTEMI, HF and stroke. DESIGN:We grouped hospitalisations for STEMI, NSTEMI, HF or stroke into weekday or weekend admissions. Multivariable adjusted ORs for binary outcomes across weekend versus weekday (reference) groups were estimated using logistic regression. SETTING:We included all non-elective hospitalisations for STEMI, NSTEMI, HF or stroke, which were recorded in the US Nationwide Readmissions Database between 2010 and 2014. PARTICIPANTS:The analysis sample included 659 906 hospitalisations for STEMI, 1 420 600 hospitalisations for NSTEMI, 3 027 699 hospitalisations for HF, and 2 574 168 hospitalisations for stroke. MAIN OUTCOME MEASURES:The primary outcome was unplanned 30-day readmission. As secondary outcomes, we considered length of stay and the following processes of care: coronary angiography, primary percutaneous coronary intervention, coronary artery bypass graft, thrombolysis, brain scan/imaging, thrombectomy, echocardiography and cardiac resynchronisation therapy/implantable cardioverter-defibrillator. RESULTS:Unplanned 30-day readmission rates were 11.0%, 15.1%, 23.0% and 10.9% for STEMI, NSTEMI, HF and stroke, respectively. Weekend hospitalisations for HF were associated with a statistically significant but modest increase in 30-day readmissions (OR of 1.045, 95% CI 1.033 to 1.058). Weekend hospitalisation for STEMI, NSTEMI or stroke was not associated with increased risk of 30-day readmission. CONCLUSION:There was no clinically meaningful evidence against the supposition that weekend and weekday hospitalisations have the same 30-day unplanned readmissions. Thirty-day readmission rates were high, especially for HF, which has implications for service provision. Strategies to reduce readmission rates should be explored, regardless of day of hospitalisation.