Hospital-Readmission Risk - Isolating Hospital Effects from Patient Effects.

BACKGROUND: To isolate hospital effects on risk-standardized hospital-readmission rates, we examined readmission outcomes among patients who had multiple admissions for a similar diagnosis at more than one hospital within a given year. METHODS: We divided the Centers for Medicare and Medicaid Services hospital-wide readmission measure cohort from July 2014 through June 2015 into two random samples. All the patients in the cohort were Medicare recipients who were at least 65 years of age. We used the first sample to calculate the risk-standardized readmission rate within 30 days for each hospital, and we classified hospitals into performance quartiles, with a lower readmission rate indicating better performance (performance-classification sample). The study sample (identified from the second sample) included patients who had two admissions for similar diagnoses at different hospitals that occurred more than 1 month and less than 1 year apart, and we compared the observed readmission rates among patients who had been admitted to hospitals in different performance quartiles. RESULTS: In the performance-classification sample, the median risk-standardized readmission rate was 15.5% (interquartile range, 15.3 to 15.8). The study sample included 37,508 patients who had two admissions for similar diagnoses at a total of 4272 different hospitals. The observed readmission rate was consistently higher among patients admitted to hospitals in a worse-performing quartile than among those admitted to hospitals in a better-performing quartile, but the only significant difference was observed when the patients were admitted to hospitals in which one was in the best-performing quartile and the other was in the worst-performing quartile (absolute difference in readmission rate, 2.0 percentage points; 95% confidence interval, 0.4 to 3.5; P=0.001). CONCLUSIONS: When the same patients were admitted with similar diagnoses to hospitals in the best-performing quartile as compared with the worst-performing quartile of hospital readmission performance, there was a significant difference in rates of readmission within 30 days. The findings suggest that hospital quality contributes in part to readmission rates independent of factors involving patients. (Funded by Yale-New Haven Hospital Center for Outcomes Research and Evaluation and others.).

Modeling defibrillation benefit for survival among cardiac resynchronization therapy defibrillator recipients.

BACKGROUND: Patients with heart failure having a low expected probability of arrhythmic death may not benefit from implantable cardioverter defibrillators (ICDs). OBJECTIVE: The objective was to validate models to identify cardiac resynchronization therapy (CRT) candidates who may not require CRT devices with ICD functionality. METHODS: Heart failure (HF) patients with CRT-Ds and non-CRT ICDs from the National Cardiovascular Data Registry and others with no device from 3 separate registries and 3 heart failure trials were analyzed using multivariable Cox proportional hazards regression for survival with the Seattle Heart Failure Model (SHFM; estimates overall mortality) and the Seattle Proportional Risk Model (SPRM; estimates proportional risk of arrhythmic death). RESULTS: Among 60,185 patients (age 68.6 ±â€¯11.3 years, 31.9% female) meeting CRT-D criteria, 38,348 had CRT-Ds, 11,389 had non-CRT ICDs, and 10,448 had no device. CRT-D patients had a prominent adjusted survival benefit (HR 0.52, 95% CI 0.50-0.55, P < .0001 versus no device). CRT-D patients with SHFM-predicted 4-year survival ≥81% (median) and a low SPRM-predicted probability of an arrhythmic mode of death ≤42% (median) had an absolute adjusted risk reduction attributable to ICD functionality of just 0.95%/year with the majority of survival benefit (70%) attributable to CRT pacing. In contrast, CRT-D patients with SHFM-predicted survival median had substantially more ICD-attributable benefit (absolute risk reduction of 2.6%/year combined; P < .0001). CONCLUSIONS: The SPRM and SHFM identified a quarter of real-world, primary prevention CRT-D patients with minimal benefit from ICD functionality. Further studies to evaluate CRT pacemakers in these low-risk CRT candidates are indicated.

Admission diagnoses among patients with heart failure: Variation by ACO performance on a measure of risk-standardized acute admission rates.

BACKGROUND: A key quality metric for Accountable Care Organizations (ACOs) is the rate of hospitalization among patients with heart failure (HF). Among this patient population, non-HF-related hospitalizations account for a substantial proportion of admissions. Understanding the types of admissions and the distribution of admission types across ACOs of varying performance may provide important insights for lowering admission rates. METHODS: We examined admission diagnoses among 220 Medicare Shared Savings Program ACOs in 2013. ACOs were stratified into quartiles by their performance on a measure of unplanned risk-standardized acute admission rates (RSAARs) among patients with HF. Using a previously validated algorithm, we categorized admissions by principal discharge diagnosis into: HF, cardiovascular/non-HF, and noncardiovascular. We compared the mean admission rates by admission type as well as the proportion of admission types across RSAAR quartiles (Q1-Q4). RESULTS: Among 220 ACOs caring for 227,356 patients with HF, the median (IQR) RSAARs per 100 person-years ranged from 64.5 (61.7-67.7) in Q1 (best performers) to 94.0 (90.1-99.9) in Q4 (worst performers). The mean admission rates by admission types for ACOs in Q1 compared with Q4 were as follows: HF admissions: 9.8 (2.2) vs 14.6 (2.8) per 100 person years (P < .0001); cardiovascular/non-HF admissions: 11.1 (1.6) vs 15.9 (2.6) per 100 person-years (P < .0001); and noncardiovascular admissions: 42.7 (5.4) vs 69.6 (11.3) per 100 person-years (P < .0001). The proportion of admission due to HF, cardiovascular/non-HF, and noncardiovascular conditions was 15.4%, 17.5%, and 67.1% in Q1 compared with 14.6%, 15.9%, and 69.4% in Q4 (P < .007). CONCLUSIONS: Although ACOs with the best performance on a measure of all-cause admission rates among people with HF tended to have fewer admissions for HF, cardiovascular/non-HF, and noncardiovascular conditions compared with ACOs with the worst performance (highest admission rates), the largest difference in admission rates were for noncardiovascular admission types. Across all ACOs, two-thirds of admissions of patients with HF were for noncardiovascular causes. These findings suggest that comprehensive approaches are needed to reduce the diverse admission types for which HF patients are at risk.

Association of Income Disparities with Patient-Reported Healthcare Experience.

BACKGROUND: Disparities in health outcome exist among patients according to socioeconomic status. However, little is known regarding the differences in healthcare experiences across the various levels of income of patients. In a nationally representative US adult population, we evaluate the differences in healthcare experiences based on patient level of income. OBJECTIVES: To evaluate the differences in patient healthcare experiences based on level of income. PATIENTS AND METHODS: We identified 68,447 individuals (mean age, 48 ± 18 years; 55% female) representing 176.8 million US adults, who had an established healthcare provider in the 2010-2013 Medical Expenditure Panel Survey cohort. This retrospective study examined the differences in all five patient-reported healthcare experience measures (access to care, provider responsiveness, patient-provider communication, shared decision-making, and patient satisfaction) under the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. We examined the relationship between patient income and their healthcare experience. RESULTS: Overall, 32% of the study participants were high-income earners while 23% had very-low income. Lower income was consistently associated with poor patient report on healthcare experience. Compared with those with high income, very-low-income-earning participants had 1.63 times greater odds (OR 1.63, 95% CI 1.45-1.82) of experiencing difficulty accessing care, had 1.34 times higher odds (OR 1.34, 95% CI 1.25-1.45) of experiencing poor communication, had higher odds (OR 1.68, 95% CI 1.46-1.92) of experiencing delays in healthcare delivery, and were more likely to report poor provider satisfaction (OR 1.48, 95% CI 1.37-1.61). CONCLUSION: Lower income-earning patients have poorer healthcare experience in all aspects of access and quality of care. Targeted policies focusing on improving communication, engagement, and satisfaction are needed to enhance patient healthcare experience for this vulnerable population.

Risk Trajectories of Readmission and Death in the First Year after Hospitalization for Chronic Obstructive Pulmonary Disease.

RATIONALE: Characterization of the dynamic nature of posthospital risk in chronic obstructive pulmonary disease (COPD) is needed to provide counseling and plan clinical services. OBJECTIVES: To analyze risk of readmission and death after discharge for COPD among Medicare beneficiaries aged 65 years and older and to determine the association between ventilator support and risk trajectory. METHODS: We computed daily absolute risks of hospital readmission and death for 1 year after discharge for COPD, stratified by ventilator support. We determined the time required for risks to decline by 50% from maximum daily values after discharge and for daily risks to plateau. We compared risks with those found in the general elderly population. MEASUREMENTS AND MAIN RESULTS: Among 2,340,637 hospitalizations, the readmission rate at 1 year was 64.2%, including 63.5%, 66.0%, and 64.1% among those receiving invasive, noninvasive, and no ventilation, respectively. Among 1,283,069 hospitalizations, mortality at 1 year was 26.2%, including 45.7%, 41.8%, and 24.4% among those same respective groups. Daily risk of readmission declined by 50% within 28, 39, and 43 days and plateaued at 46, 54, and 61 days among those receiving invasive, noninvasive, and no ventilation, respectively. Risk of death declined by 50% by 3, 4, and 17 days and plateaued by 21, 18, and 24 days in the same respective groups. Risks of hospitalization and death were significantly higher after discharge for COPD than among the general Medicare population. CONCLUSIONS: Discharge from the hospital is associated with prolonged risks of readmission and death that vary with need for ventilator support. Interventions limited to the first month after discharge may be insufficient to improve longitudinal outcomes.

Sex Differences in 1-Year All-Cause Rehospitalization in Patients After Acute Myocardial Infarction: A Prospective Observational Study.

BACKGROUND: Compared with men, women are at higher risk of rehospitalization in the first month after discharge for acute myocardial infarction (AMI). However, it is unknown whether this risk extends to the full year and varies by age. Explanatory factors potentially mediating the relationship between sex and rehospitalization remain unexplored and are needed to reduce readmissions. The aim of this study was to assess sex differences and factors associated with 1-year rehospitalization rates after AMI. METHODS: We recruited 3536 patients (33% women) ≥18 years of age hospitalized with AMI from 24 US centers into the TRIUMPH study (Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status). Data were obtained by medical record abstraction and patient interviews, and a physician panel adjudicated hospitalizations within the first year after AMI. We compared sex differences in rehospitalization using a Cox proportional hazards model, following sequential adjustment for covariates and testing for an age-sex interaction. RESULTS: One-year crude all-cause rehospitalization rates for women were significantly higher than men after AMI (hazard ratio, 1.29 for women; 95% confidence interval, 1.12-1.48). After adjustment for demographics and clinical factors, women had a persistent 26% higher risk of rehospitalization (hazard ratio, 1.26; 95% confidence interval, 1.08-1.47). However, after adjustment for health status and psychosocial factors (hazard ratio, 1.14; 95% confidence interval, 0.96-1.35), the association was attenuated. No significant age-sex interaction was found for 1-year rehospitalization, suggesting that the increased risk applied to both older and younger women. CONCLUSIONS: Regardless of age, women have a higher risk of rehospitalization compared with men over the first year after AMI. Although the increased risk persisted after adjustment for clinical factors, the poorer health and psychosocial state of women attenuated the difference.

Regional variation in hospitalisation and mortality in heart failure: comparison of England and Lombardy using multistate modelling.

Heart failure (HF) is a common, serious chronic condition with high morbidity, hospitalisation and mortality. The healthcare systems of England and the northern Italian region of Lombardy share important similarities and have comprehensive hospital administrative databases linked to the death register. We used them to compare admission for HF and mortality for patients between 2006 and 2012 (n = 37,185 for Lombardy, 234,719 for England) with multistate models. Despite close similarities in age, sex and common comorbidities of the two sets of patients, in Lombardy, HF admissions were longer and more frequent per patient than in England, but short- and medium-term mortality was much lower. English patients had more very short stays, but their very elderly also had longer stays than their Lombardy counterparts. Using a three-state model, the predicted total time spent in hospital showed large differences between the countries: women in England spent an average of 24 days if aged 65 at first admission and 19 days if aged 85; in Lombardy these figures were 68 and 27 days respectively. Eight-state models suggested disease progression that appeared similar in each country. Differences by region within England were modest, with London patients spending more time in hospital and having lower mortality than the rest of England. Whilst clinical practice differences plausibly explain these patterns, we cannot confidently disentangle the impact of alternatives such as coding, casemix, and the availability and use of non-hospital settings. We need to better understand the links between rehospitalisation frequency and mortality.

Age Differences in Hospital Mortality for Acute Myocardial Infarction: Implications for Hospital Profiling.

BACKGROUND: Publicly reported hospital risk-standardized mortality rates (RSMRs) for acute myocardial infarction (AMI) are calculated for Medicare beneficiaries. Outcomes for older patients with AMI may not reflect general outcomes. OBJECTIVE: To examine the relationship between hospital 30-day RSMRs for older patients (aged ≥65 years) and those for younger patients (aged 18 to 64 years) and all patients (aged ≥18 years) with AMI. DESIGN: Retrospective cohort study. SETTING: 986 hospitals in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry-Get With the Guidelines. PARTICIPANTS: Adults hospitalized for AMI from 1 October 2010 to 30 September 2014. MEASUREMENTS: Hospital 30-day RSMRs were calculated for older, younger, and all patients using an electronic health record measure of AMI mortality endorsed by the National Quality Forum. Hospitals were ranked by their 30-day RSMRs for these 3 age groups, and agreement in rankings was plotted. The correlation in hospital AMI achievement scores for each age group was also calculated using the Hospital Value-Based Purchasing (HVBP) Program method computed with the electronic health record measure. RESULTS: 267 763 and 276 031 AMI hospitalizations among older and younger patients, respectively, were identified. Median hospital 30-day RSMRs were 9.4%, 3.0%, and 6.2% for older, younger, and all patients, respectively. Most top- and bottom-performing hospitals for older patients were neither top nor bottom performers for younger patients. In contrast, most top and bottom performers for older patients were also top and bottom performers for all patients. Similarly, HVBP achievement scores for older patients correlated weakly with those for younger patients (R = 0.30) and strongly with those for all patients (R = 0.92). LIMITATION: Minority of U.S. hospitals. CONCLUSION: Hospital mortality rankings for older patients with AMI inconsistently reflect rankings for younger patients. Incorporation of younger patients into assessment of hospital outcomes would permit further examination of the presence and effect of age-related quality differences. PRIMARY FUNDING SOURCE: American College of Cardiology.

Length of Stay From the Hospital Perspective: Practice of Early Discharge Is Not Associated With Increased Readmission Risk After Lung Cancer Surgery.

OBJECTIVE: To determine if hospitals that routinely discharge patients early after lobectomy have increased readmissions. BACKGROUND: Hospitals are increasingly motivated to reduce length of stay (LOS) after lung cancer surgery, yet it is unclear if a routine of early discharge is associated with increased readmissions. The relationship between hospital discharge practices and readmission rates is therefore of tremendous clinical and financial importance. METHODS: The National Cancer Database was queried for patients undergoing lobectomy for lung cancer from 2004 to 2013 at Commission on Cancer-accredited hospitals, which performed at least 25 lobectomies in a 2-year period. Facility discharge practices were characterized by a facility's median LOS relative to the median LOS for all patients in that same time period. RESULTS: In all, 59,734 patients met inclusion criteria; 2687 (4.5%) experienced an unplanned readmission. In a hierarchical logistic regression model, a routine of early discharge (defined as a facility's tendency to discharge patients faster than the population median in the same time period) was not associated with increased risk of readmission (odds ratio 1.12, 95% confidence interval 0.97-1.28, P = 0.12). In a risk-adjusted hospital readmission rate analysis, hospitals that discharged patients early did not experience more readmissions (P = 0.39). The lack of effect of early discharge practices on readmission rates was observed for both minimally invasive and thoracotomy approaches. CONCLUSIONS: It is possible for hospitals to develop early discharge practices without increasing readmissions. Further study is needed to identify the critical practice elements that have enabled hospitals to aggressively discharge patients without increasing readmission risk.

Reductions in Readmission Rates Are Associated With Modest Improvements in Patient-reported Health Gains Following Hip and Knee Replacement in England.

BACKGROUND: Although many hospital readmission reduction initiatives have been introduced globally, health care systems ultimately aim to improve patients' health and well-being. We examined whether the hospitals that report greater success in reducing readmissions also see greater improvements in patient-reported outcomes. RESEARCH DESIGN: We examined hospital groups (Trusts) that provided hip replacement or knee replacement surgery in England between April 2010 and February 2013. For each Trust, we calculated risk-adjusted 30-day readmission rates from administrative datasets. We also obtained changes in patient-reported health between presurgical assessment and 6-month follow-up, using general health EuroQuol five dimensions questionaire (EQ-5D) and EuroQuol visual analogue scales (EQ-VAS) and procedure-specific (Oxford Hip and Knee Scores) measures. Panel models were used to assess whether changes over time in risk-adjusted readmission rates were associated with changes over time in risk-adjusted health gains. RESULTS: Each percentage point reduction in the risk-adjusted readmission rate for hip replacement was associated with an additional health gain of 0.004 for EQ-5D [95% confidence interval (CI), 0.002-0.006], 0.39 for EQ-VAS (95% CI, 0.26-0.52), and 0.32 for Oxford Hip Score (95% CI, 0.15-0.27). Corresponding figures for knee replacement were 0.003 for EQ-5D (95% CI, 0.001-0.004), 0.21 for EQ-VAS (95% CI, 0.12-0.30), and 0.14 in the Oxford Knee Score (95% CI, 0.09-0.20). CONCLUSIONS: Reductions in readmission rates were associated with modest improvements in patients' sense of their health and well-being at the hospital group level. In particular, fears that efforts to reduce readmission rates have had unintended consequences for patients appear to be unfounded.

Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge.

IMPORTANCE: The Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown. OBJECTIVE: To examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge. DESIGN, SETTING, AND PARTICIPANTS: Retrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014. EXPOSURE: Thirty-day risk-adjusted readmission rate (RARR). MAIN OUTCOMES AND MEASURES: Thirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition. RESULTS: In 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality. CONCLUSIONS AND RELEVANCE: Among Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.

Epidemiology, Pathophysiology, and Prognosis of Heart Failure in Older Adults.

Heart failure is the quintessential cardiovascular syndrome of aging that results from common cardiovascular conditions in older adults in conjunction with age-associated changes in cardiovascular structure and function. To a large extent, heart failure is a geriatric syndrome in much the same way that dementia, falls, and frailty are geriatric syndromes. The incidence and prevalence of heart failure increase strikingly with age and make heart failure the most common reason for hospitalization among older adults. Although outcomes for older adults with heart failure have improved over time, mortality, hospitalization, and rehospitalization rates remain high.

Sex Differences in the Rate, Timing, and Principal Diagnoses of 30-Day Readmissions in Younger Patients with Acute Myocardial Infarction.

BACKGROUND: Young women (<65 years) experience a 2- to 3-fold greater mortality risk than younger men after an acute myocardial infarction. However, it is unknown whether they are at higher risk for 30-day readmission, and if this association varies by age. We examined sex differences in the rate, timing, and principal diagnoses of 30-day readmissions, including the independent effect of sex following adjustment for confounders. METHODS AND RESULTS: We included patients aged 18 to 64 years with a principal diagnosis of acute myocardial infarction. Data were used from the Healthcare Cost and Utilization Project-State Inpatient Database for California (07-09). Readmission diagnoses were categorized by using an aggregated version of the Centers for Medicare and Medicaid Services' Condition Categories, and readmission timing was determined from the day after discharge. Of 42,518 younger patients with acute myocardial infarction (26.4% female), 4775 (11.2%) had at least 1 readmission. The 30-day all-cause readmission rate was higher for women (15.5% versus 9.7%, P<0.0001). For both sexes, readmission risk was highest on days 2 to 4 after discharge and declined thereafter, and women were more likely to present with noncardiac diagnoses (44.4% versus 40.6%, P=0.01). Female sex was associated with a higher rate of 30-day readmission, which persisted after adjustment (hazard ratio, 1.22; 95% confidence interval, 1.15-1.30). There was no significant interaction between age and sex on readmission. CONCLUSIONS: In comparison with men, younger women have a higher risk for readmission, even after the adjustment for confounders. The timing of 30-day readmission was similar in women and men, and both sexes were susceptible to a wide range of causes for readmission.

Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions.

Importance: Readmission rates declined after announcement of the Hospital Readmission Reduction Program (HRRP), which penalizes hospitals for excess readmissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Objective: To compare trends in readmission rates for target and nontarget conditions, stratified by hospital penalty status. Design, Setting, and Participants: Retrospective cohort study of Medicare fee-for-service beneficiaries older than 64 years discharged between January 1, 2008, and June 30, 2015, from 2214 penalty hospitals and 1283 nonpenalty hospitals. Difference-interrupted time-series models were used to compare trends in readmission rates by condition and penalty status. Exposure: Hospital penalty status or target condition under the HRRP. Main Outcomes and Measures: Thirty-day risk adjusted, all-cause unplanned readmission rates for target and nontarget conditions. Results: The study included 48 137 102 hospitalizations of 20 351 161 Medicare beneficiaries. In January 2008, the mean readmission rates for AMI, HF, pneumonia, and nontarget conditions were 21.9%, 27.5%, 20.1%, and 18.4%, respectively, at hospitals later subject to financial penalties and 18.7%, 24.2%, 17.4%, and 15.7% at hospitals not subject to penalties. Between January 2008 and March 2010, prior to HRRP announcement, readmission rates were stable across hospitals (except AMI at nonpenalty hospitals). Following announcement of HRRP (March 2010), readmission rates for both target and nontarget conditions declined significantly faster for patients at hospitals later subject to financial penalties compared with those at nonpenalized hospitals (for AMI, additional decrease of -1.24 [95% CI, -1.84 to -0.65] percentage points per year relative to nonpenalty discharges; for HF, -1.25 [95% CI, -1.64 to -0.86]; for pneumonia, -1.37 [95% CI, -1.80 to -0.95]; and for nontarget conditions, -0.27 [95% CI, -0.38 to -0.17]; P < .001 for all). For penalty hospitals, readmission rates for target conditions declined significantly faster compared with nontarget conditions (for AMI, additional decline of -0.49 [95% CI, -0.81 to -0.16] percentage points per year relative to nontarget conditions [P = .004]; for HF, -0.90 [95% CI, -1.18 to -0.62; P < .001]; and for pneumonia, -0.57 [95% CI, -0.92 to -0.23; P < .001]). In contrast, among nonpenalty hospitals, readmissions for target conditions declined similarly or more slowly compared with nontarget conditions (for AMI, additional increase of 0.48 [95% CI, 0.01-0.95] percentage points per year [P = .05]; for HF, 0.08 [95% CI, -0.30 to 0.46; P = .67]; for pneumonia, 0.53 [95% CI, 0.13-0.93; P = .01]). After HRRP implementation in October 2012, the rate of change for readmission rates plateaued (P < .05 for all except pneumonia at nonpenalty hospitals), with the greatest relative change observed among hospitals subject to financial penalty. Conclusions and Relevance: Medicare fee-for-service patients at hospitals subject to penalties under the HRRP had greater reductions in readmission rates compared with those at nonpenalized hospitals. Changes were greater for target vs nontarget conditions for patients at the penalized hospitals but not at the other hospitals.

Hospital variation in admission to intensive care units for patients with acute myocardial infarction.

BACKGROUND: The treatment for patients with acute myocardial infarction (AMI) was transformed by the introduction of intensive care units (ICUs), yet we know little about how contemporary hospitals use this resource-intensive setting and whether higher use is associated with better outcomes. METHODS: We identified 114,136 adult hospitalizations for AMI from 307 hospitals in the 2009 to 2010 Premier database using codes from the International Classification of Diseases, Ninth Revision, Clinical Modification. Hospitals were stratified into quartiles by rates of ICU admission for AMI patients. Across quartiles, we examined in-hospital risk-standardized mortality rates and usage rates of critical care therapies for these patients. RESULTS: Rates of ICU admission for AMI patients varied markedly among hospitals (median 48%, Q1-Q4 20%-71%, range 0%-98%), and there was no association with in-hospital risk-standardized mortality rates (6% all quartiles, P = .7). However, hospitals admitting more AMI patients to the ICU were more likely to use critical care therapies overall (mechanical ventilation [from Q1 with lowest rate of ICU use to Q4 with highest rate 13%-16%], vasopressors/inotropes [17%-21%], intra-aortic balloon pumps [4%-7%], and pulmonary artery catheters [4%-5%]; P for trend < .05 in all comparisons). CONCLUSIONS: Rates of ICU admission for patients with AMI vary substantially across hospitals and were not associated with differences in mortality, but were associated with greater use of critical care therapies. These findings suggest uncertainty about the appropriate use of this resource-intensive setting and a need to optimize ICU triage for patients who will truly benefit.

National trends in stroke after acute myocardial infarction among Medicare patients in the United States: 1999 to 2010.

BACKGROUND: Stroke is a common and important adverse event after acute myocardial infarction (AMI) in the elderly. It is unclear whether the risk of stroke after AMI has changed with improvements in treatments and outcomes for AMI in the last decade. METHODS: To assess trends in risk of stroke after AMI, we used a national sample of Medicare data to identify Fee-for-Service patients (n = 2,305,441) aged ≥65 years who were discharged alive after hospitalization for AMI from 1999 to 2010. RESULTS: We identified 57,848 subsequent hospitalizations for ischemic stroke and 4,412 hospitalizations for hemorrhagic stroke within 1 year after AMI. The 1-year rate of ischemic stroke decreased from 3.4% (95% CI 3.3%-3.4%) to 2.6% (2.5%-2.7%; P < .001). The risk-adjusted annual decline was 3% (hazard ratio, 0.97; [0.97-0.98]) and was similar across all age and sex-race groups. The rate of hemorrhagic stroke remained stable at 0.2% and did not differ by subgroups. The 30-day mortality for patients admitted with ischemic stroke after AMI decreased from 19.9% (18.8%-20.9%) to 18.3% (17.1%-19.6%) and from 48.3% (43.0%-53.6%) to 45.7% (40.3%-51.2%) for those admitted with hemorrhagic stroke. We observed a decrease in 1-year mortality from 37.8% (36.5%-39.1%) to 35.3% (33.8%-36.8%) for ischemic stroke and from 66.6% (61.4%-71.5%) to 60.6% (55.1%-65.9%) for hemorrhagic stroke. CONCLUSIONS: From 1999 to 2010, the 1-year risk for ischemic stroke after AMI declined, whereas the risk of hemorrhagic stroke remained unchanged. However, 30-day and 1-year mortality continued to be high.

National trends in heart failure hospitalization after acute myocardial infarction for Medicare beneficiaries: 1998-2010.

BACKGROUND: Previous studies have reported conflicting findings regarding how the incidence of heart failure (HF) after acute myocardial infarction (AMI) has changed over time, and data on contemporary national trends are sparse. METHODS AND RESULTS: Using a complete national sample of 2 789 943 AMI hospitalizations of Medicare fee-for-service beneficiaries from 1998 through 2010, we evaluated annual changes in the incidence of subsequent HF hospitalization and mortality using Poisson and survival analysis models. The number of patients hospitalized for HF within 1 year after AMI declined modestly from 16.1 per 100 person-years in 1998 to 14.2 per 100 person years in 2010 (P<0.001). After adjusting for demographic factors, a relative 14.6% decline for HF hospitalizations after AMI was observed over the study period (incidence risk ratio, 0.854; 95% confidence interval, 0.809-0.901). Unadjusted 1-year mortality following HF hospitalization after AMI was 44.4% in 1998, which decreased to 43.2% in 2004 to 2005, but then increased to 45.5% by 2010. After adjusting for demographic factors and clinical comorbidities, this represented a 2.4% relative annual decline (hazard ratio, 0.976; 95% confidence interval, 0.974-0.978) from 1998 to 2007, but a 5.1% relative annual increase from 2007 to 2010 (hazard ratio, 1.051; 95% confidence interval, 1.039-1.064). CONCLUSIONS: In a national sample of Medicare beneficiaries, HF hospitalization after AMI decreased from 1998 to 2010, which may indicate improvements in the management of AMI. In contrast, survival after HF following AMI remains poor, and has worsened from 2007 to 2010, demonstrating that challenges still remain for the treatment of this high-risk condition after AMI.

Variation exists in rates of admission to intensive care units for heart failure patients across hospitals in the United States.

BACKGROUND: Despite increasing attention on reducing relatively costly hospital practices while maintaining the quality of care, few studies have examined how hospitals use the intensive care unit (ICU), a high-cost setting, for patients admitted with heart failure (HF). We characterized hospital patterns of ICU admission for patients with HF and determined their association with the use of ICU-level therapies and patient outcomes. METHODS AND RESULTS: We identified 166 224 HF discharges from 341 hospitals in the 2009-2010 Premier Perspective database. We excluded hospitals with <25 HF admissions, patients <18 years old, and transfers. We defined ICU as including medical ICU, coronary ICU, and surgical ICU. We calculated the percent of patients admitted directly to an ICU. We compared hospitals in the top quartile (high ICU admission) with the remaining quartiles. The median percentage of ICU admission was 10% (interquartile range, 6%-16%; range, 0%-88%). In top-quartile hospitals, treatments requiring an ICU were used less often; the percentage of ICU days receiving mechanical ventilation was 6% for the top quartile versus 15% for the others; noninvasive positive pressure ventilation, 8% versus 19%; vasopressors and/or inotropes, 9% versus 16%; vasodilators, 6% versus 12%; and any of these interventions, 26% versus 51%. Overall HF in-hospital risk-standardized mortality was similar (3.4% versus 3.5%; P=0.2). CONCLUSIONS: ICU admission rates for HF varied markedly across hospitals and lacked association with in-hospital risk-standardized mortality. Greater ICU use correlated with fewer patients receiving ICU interventions. Judicious ICU use could reduce resource consumption without diminishing patient outcomes.

Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.

BACKGROUND: Patients aged ≥ 65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18-64 years with patients aged ≥ 65 years. METHODS AND FINDINGS: We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n=206,141), AMI (n=107,256), and pneumonia (n=199,620) from 2007-2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18-64 years exceeded the readmission rate in patients aged ≥ 65 years in the HF cohort (23.4% vs. 22.0%, p<0.001), but was lower in the AMI (11.2% vs. 17.5%, p<0.001) and pneumonia (14.4% vs. 17.3%, p<0.001) cohorts. When adjusted for sex, race, comorbidities, and payer status, the 30-day readmission risk in patients aged 18-64 years was similar to patients ≥ 65 years in the HF (HR 0.99; 95%CI 0.97-1.02) and pneumonia (HR 0.97; 95%CI 0.94-1.01) cohorts and was marginally lower in the AMI cohort (HR 0.92; 95%CI 0.87-0.96). For all cohorts, the timing of readmission was similar; readmission risks were highest between days 2 and 5 and declined thereafter across all age groups. Diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions among age groups <65 years; a non-cardiac diagnosis represented 39-44% of readmissions in the HF cohort and 37-45% of readmissions in the AMI cohort, while a non-pulmonary diagnosis represented 61-64% of patients in the pneumonia cohort. CONCLUSION: When adjusted for differences in patient characteristics, young and middle-aged adults have 30-day readmission rates that are similar to elderly patients for HF, AMI, and pneumonia. A generalized risk after hospitalization is present regardless of age. Please see later in the article for the Editors' Summary.