Publications by Year: 2018

IMPORTANCE: Patients who survive acute myocardial infarction (AMI) have a high risk of subsequent major cardiovascular events. Efforts to identify risk factors for recurrence have primarily focused on the period immediately following AMI admission.

OBJECTIVES: To identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.

DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study. Patients with AMI (n = 4227), aged 18 years or older, discharged alive from 53 acute-care hospitals across China from January 1, 2013, to July 17, 2014. Patients were randomly divided into samples: training (50% [2113 patients]), test (25% [1057 patients]), and validation (25% [1057 patients]). Risk factors were identified by a Cox model with Markov chain Monte Carlo simulation and further evaluated by latent class analysis. Analyses were conducted from May 1, 2017, to January 21, 2018.

MAIN OUTCOMES AND MEASURES: Major cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.

RESULTS: The mean (SD) age of the cohort was 60.8 (11.8) years and 994 of 4227 patients (23.5%) were female. Common comorbidities included hypertension (2358 patients [55.8%]), coronary heart disease (1798 patients [42.5%]), and dyslipidemia (1290 patients [30.5%]). One-year event rates were 8.1% (95% CI, 6.91%-9.24%), 9.0% (95% CI, 7.22%-10.70%), and 6.4% (95% CI, 4.89%-7.85%) for the training, test, and validation samples, respectively. Nineteen risk factors comprising 15 unique variables (age, education, prior AMI, prior ventricular tachycardia or fibrillation, hypertension, angina, prearrival medical assistance, >4 hours from onset of symptoms to admission, ejection fraction, renal dysfunction, heart rate, systolic blood pressure, white blood cell count, blood glucose, and in-hospital complications) were identified. In the training, test, and validation samples, respectively, the risk model had C statistics of 0.79 (95% CI, 0.75-0.83), 0.73 (95% CI, 0.68-0.78), and 0.77 (95% CI, 0.70-0.83) and a predictive range of 1.2% to 33.9%, 1.2% to 37.9%, and 1.3% to 34.3%. The C statistic was 0.69 (95% CI, 0.65-0.74) for the latent class model in the training data. The risk model stratified 11.3%, 81.0%, and 7.7% of patients to high-, average-, and low-risk groups, with respective probabilities of 0.32, 0.06, and 0.01 for 1-year events.

CONCLUSIONS AND RELEVANCE: Nineteen risk factors were identified, and a model was developed and evaluated to predict risk of 1-year cardiovascular events after AMI. This may aid clinicians in identifying high-risk patients who would benefit most from intensive follow-up and aggressive risk factor reduction.

IMPORTANCE: The Hospital Readmissions Reduction Program (HRRP) has been associated with a reduction in readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. It is unclear whether the HRRP has been associated with change in patient mortality.

OBJECTIVE: To determine whether the HRRP was associated with a change in patient mortality.

DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study of hospitalizations for HF, AMI, and pneumonia among Medicare fee-for-service beneficiaries aged at least 65 years across 4 periods from April 1, 2005, to March 31, 2015. Period 1 and period 2 occurred before the HRRP to establish baseline trends (April 2005-September 2007 and October 2007-March 2010). Period 3 and period 4 were after HRRP announcement (April 2010 to September 2012) and HRRP implementation (October 2012 to March 2015).

EXPOSURES: Announcement and implementation of the HRRP.

MAIN OUTCOMES AND MEASURES: Inverse probability-weighted mortality within 30 days of discharge following hospitalization for HF, AMI, and pneumonia, and stratified by whether there was an associated readmission. An additional end point was mortality within 45 days of initial hospital admission for target conditions.

RESULTS: The study cohort included 8.3 million hospitalizations for HF, AMI, and pneumonia, among which 7.9 million (mean age, 79.6 [8.7] years; 53.4% women) were alive at discharge. There were 3.2 million hospitalizations for HF, 1.8 million for AMI, and 3.0 million for pneumonia. There were 270 517 deaths within 30 days of discharge for HF, 128 088 for AMI, and 246 154 for pneumonia. Among patients with HF, 30-day postdischarge mortality increased before the announcement of the HRRP (0.27% increase from period 1 to period 2). Compared with this baseline trend, HRRP announcement (0.49% increase from period 2 to period 3; difference in change, 0.22%, P = .01) and implementation (0.52% increase from period 3 to period 4; difference in change, 0.25%, P = .001) were significantly associated with an increase in postdischarge mortality. Among patients with AMI, HRRP announcement was associated with a decline in postdischarge mortality (0.18% pre-HRRP increase vs 0.08% post-HRRP announcement decrease; difference in change, -0.26%; P = .01) and did not significantly change after HRRP implementation. Among patients with pneumonia, postdischarge mortality was stable before HRRP (0.04% increase from period 1 to period 2), but significantly increased after HRRP announcement (0.26% post-HRRP announcement increase; difference in change, 0.22%, P = .01) and implementation (0.44% post-HPPR implementation increase; difference in change, 0.40%, P < .001). The overall increase in mortality among patients with HF and pneumonia was mainly related to outcomes among patients who were not readmitted but died within 30 days of discharge. For all 3 conditions, HRRP implementation was not significantly associated with an increase in mortality within 45 days of admission, relative to pre-HRRP trends.

CONCLUSIONS AND RELEVANCE: Among Medicare beneficiaries, the HRRP was significantly associated with an increase in 30-day postdischarge mortality after hospitalization for HF and pneumonia, but not for AMI. Given the study design and the lack of significant association of the HRRP with mortality within 45 days of admission, further research is needed to understand whether the increase in 30-day postdischarge mortality is a result of the policy.

IMPORTANCE: The US News & World Report (USNWR) identifies the "Best Hospitals" for "Cardiology and Heart Surgery." These rankings may have significant influence on patients and hospitals.

OBJECTIVE: To determine whether USNWR top-ranked hospitals perform better than nonranked hospitals on mortality rates and readmission measures as well as patient satisfaction.

DESIGN, SETTING, AND PARTICIPANTS: This national retrospective study evaluated outcomes at 3552 US hospitals from 2014 to 2017.

EXPOSURES: US News & World Report 2018 to 2019 Cardiology and Heart Surgery rankings (top-ranked vs nonranked hospitals).

MAIN OUTCOMES AND MEASURES: Hospital-level 30-day risk-standardized mortality and readmission rates for Medicare fee-for-service beneficiaries age 65 years or older hospitalized for 3 cardiovascular conditions: acute myocardial infarction (AMI), heart failure (HF), and coronary artery bypass grafting (CABG) as well as Hospital Consumer Assessment of Healthcare Providers and Systems patient satisfaction star ratings obtained from publicly available Centers for Medicaid and Medicare Services data.

RESULTS: Thirty-day mortality rates at top-ranked hospitals (n = 50), compared with nonranked hospitals (n = 3502), were lower for AMI (11.9% vs 13.2%, P < .001), HF (9.5% vs 11.9%; P < .001), and CABG (2.3%vs 3.3%; P < .001). Thirty-day readmission rates at the top-ranked hospitals (n = 50) when compared with nonranked hospitals (n = 2841) were similar for AMI (16.7% vs 16.5%; P = .64) and CABG (14.1% vs 13.7%; P = .15) but higher for HF (21.0% vs 19.2%; P < .001), Finally, patient satisfaction was higher at top-ranked hospitals (n = 50) compared with nonranked hospitals (n = 3412) (3.9 vs 3.3; P < .001).

CONCLUSIONS AND RELEVANCE: We found that USNWR top-ranked hospitals for cardiovascular care had lower 30-day mortality rates for AMI, HF, and CABG and higher patient satisfaction ratings compared with nonranked hospitals. However, 30-day readmission rates were either similar (for AMI and CABG) or higher (for HF) at top-ranked compared with nonranked hospitals. This discrepancy between readmissions and other performance measures raises concern that readmissions may not be an adequate metric of hospital care quality.

BACKGROUND: Heart failure (HF) is the leading cause of morbidity and mortality in the United States. Despite advancement in the management of HF, outcomes remain suboptimal, particularly among the uninsured. In 2014, the Affordable Care Act expanded Medicaid eligibility, and millions of low-income adults gained insurance. Little is known about Medicaid expansion's effect on inpatient HF care.

METHODS AND RESULTS: We used the American Heart Association's Get With The Guidelines-Heart Failure registry to assess changes in inpatient care quality and outcomes among low-income patients (<65 years old) hospitalized for HF after Medicaid expansion, in expansion, and nonexpansion states. Patients were classified as low-income if covered by Medicaid, uninsured, or missing insurance. Expansion states were those that implemented expansion in 2014. Piecewise logistic multivariable regression models were constructed to track quarterly trends of quality and outcome measures in the pre (January 1, 2010-December 31, 2013) and postexpansion (January 1, 2014-June 30, 2017) periods. These measures were compared between expansion versus nonexpansion states during the postexpansion period. The cohort included 58 804 patients hospitalized across 391 sites. In states that expanded Medicaid, uninsured HF hospitalizations declined from 7.9% to 4.4%, and Medicaid HF hospitalizations increased from 18.3% to 34.6%. Defect-free HF care was increasing during the preexpansion period (adjusted odds ratio/quarter, 1.06; 95% confidence interval, 1.03-1.08) but did not change after expansion (adjusted odds ratio, 0.99; 95% confidence interval, 0.97-1.02). Patterns were similar for other quality measures. There were no quality measures for which the rate of improvement sped up after expansion. In-hospital mortality rates remained similar during the preexpansion (adjusted odds ratio, 0.99; 95% confidence interval, 0.96-1.02) and postexpansion periods (adjusted odds ratio, 1.00; 95% confidence interval, 0.97-1.03). Among nonexpansion states, uninsured HF hospitalizations increased (11.6% to 16.7%) as did Medicaid HF hospitalizations (17.9% to 26.6%), and no quarterly improvement was observed for most quality measures in the post compared with preexpansion period. During the postexpansion period, defect-free care and mortality did not differ between expansion and nonexpansion states.

CONCLUSIONS: Medicaid expansion was associated with a significant decline in uninsured HF hospitalizations but not improvements in quality of care or in-hospital mortality among sites participating in a national quality improvement initiative. Efforts beyond insurance expansion are needed to improve in-hospital outcomes for low-income patients with HF.