Hospital Characteristics and Early Enrollment Trends in the American College of Cardiology Voluntary Public Reporting Program.

Importance: Limited data exist regarding the characteristics of hospitals that do and do not participate in voluntary public reporting programs. Objective: To describe hospital characteristics and trends associated with early participation in the American College of Cardiology (ACC) voluntary reporting program for cardiac catheterization-percutaneous coronary intervention (CathPCI) and implantable cardioverter-defibrillator (ICD) registries. Design, Setting, and Participants: This cross-sectional study analyzed enrollment trends and characteristics of hospitals that did and did not participate in the ACC voluntary public reporting program. All hospitals reporting procedure data to the National Cardiovascular Data Registry (NCDR) CathPCI or ICD registries that were eligible for the public reporting program from July 2014 (ie, program launch date) to May 2017 were included. Stepwise logistic regression was used to identify hospital characteristics associated with voluntary participation. Enrollment trends were evaluated considering the date US News & World Report (USNWR) announced that it would credit participating hospitals. Data analysis was performed from March 2017 to January 2018. Main Outcomes and Measures: Hospital characteristics and participation in the public reporting program. Results: By May 2017, 561 of 1747 eligible hospitals (32.1%) had opted to participate in the program. Enrollment increased from 240 to 376 hospitals (56.7%) 1 month after the USNWR announcement that program participation would be considered as a component of national hospital rankings. Compared with hospitals that did not enroll, program participants had increased median (IQR) procedural volumes for PCI (481 [280-764] procedures vs 332 [186-569] procedures; P < .001) and ICD (114 [56-220] procedures vs 62 [25-124] procedures; P < .001). Compared with nonparticipating hospitals, an increased mean (SD) proportion of participating hospitals adhered to composite discharge medications after PCI (0.96 [0.03] vs 0.92 [0.07]; P < .001) and ICD (0.88 [0.10] vs 0.81 [0.12]; P < .001). Hospital factors associated with enrollment included participation in 5 or more NCDR registries (odds ratio [OR],1.98; 95% CI, 1.24-3.19; P = .005), membership in a larger hospital system (ie, 3-20 hospitals vs ≤2 hospitals in the system: OR, 2.29; 95% CI, 1.65-3.17; P = .001), participation in an NCDR pilot public reporting program of PCI 30-day readmissions (OR, 2.93; 95% CI, 2.19-3.91; P < .001), university affiliation (vs government affiliation: OR, 3.85, 95% CI, 1.03-14.29; P = .045; vs private affiliation: OR, 2.22; 95% CI, 1.35-3.57; P < .001), Midwest location (vs South: OR, 1.47; 95% CI, 1.06-2.08; P = .02), and increased comprehensive quality ranking (4 vs 1-2 performance stars in CathPCI: OR, 8.08; 95% CI, 5.07-12.87; P < .001; 4 vs 1 performance star in ICD: OR, 2.26; 95% CI, 1.48-3.44; P < .001) (C statistic = 0.829). Conclusions and Relevance: This study found that one-third of eligible hospitals participated in the ACC voluntary public reporting program and that enrollment increased after the announcement that program participation would be considered by USNWR for hospital rankings. Several hospital characteristics, experience with public reporting, and quality of care were associated with increased odds of participation.

Predicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Standardization of risk is critical in benchmarking and quality improvement efforts for percutaneous coronary interventions (PCIs). In 2018, the CathPCI Registry was updated to include additional variables to better classify higher-risk patients. OBJECTIVES: This study sought to develop a model for predicting in-hospital mortality risk following PCI incorporating these additional variables. METHODS: Data from 706,263 PCIs performed between July 2018 and June 2019 at 1,608 sites were used to develop and validate a new full and pre-catheterization model to predict in-hospital mortality, and a simplified bedside risk score. The sample was randomly split into a development cohort (70%, n = 495,005) and a validation cohort (30%, n = 211,258). The authors created 1,000 bootstrapped samples of the development cohort and used stepwise selection logistic regression on each sample. The final model included variables that were selected in at least 70% of the bootstrapped samples and those identified a priori due to clinical relevance. RESULTS: In-hospital mortality following PCI varied based on clinical presentation. Procedural urgency, cardiovascular instability, and level of consciousness after cardiac arrest were most predictive of in-hospital mortality. The full model performed well, with excellent discrimination (C-index: 0.943) in the validation cohort and good calibration across different clinical and procedural risk cohorts. The median hospital risk-standardized mortality rate was 1.9% and ranged from 1.1% to 3.3% (interquartile range: 1.7% to 2.1%). CONCLUSIONS: The risk of mortality following PCI can be predicted in contemporary practice by incorporating variables that reflect clinical acuity. This model, which includes data previously not captured, is a valid instrument for risk stratification and for quality improvement efforts.

Predictors of Underutilization of Medical Therapy in Patients Undergoing Endovascular Revascularization for Peripheral Artery Disease.

OBJECTIVES: The aim of this study was to explore discharge prescription rates of guideline-directed medical therapy (GDMT), defined as aggregate antiplatelet agent, statin, and ACE inhibitor or angiotensin receptor blocker use after endovascular lower extremity (LE) peripheral vascular intervention. BACKGROUND: Little is known about contemporary GDMT prescription following LE PVI. METHODS: Sex, age, and comorbid conditions were related to discharge GDMT prescription among patients undergoing LE PVI for symptomatic peripheral artery disease in the 2014-2018 Vascular Study Group of New England Vascular Quality Initiative. Multivariate logistic regression was used to identify independent predictors of discharge GDMT prescription. RESULTS: Among 12,316 patients, only 47.4% (n = 5,844) were discharged on GDMT after LE PVI. Most patients were discharged on antiplatelet agents (95.2%), with statins (83.5%) and angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (55.8%) prescribed less often. A higher proportion of patients were on Class 1 guideline-recommended therapy with antiplatelet agents and statins (80.5%). In multivariate analysis, female sex, older age, end-stage renal disease, chronic limb-threatening ischemia, and congestive heart failure were negative predictors of discharge GDMT prescription, while hypertension, diabetes, coronary artery disease, and prior LE PVI or bypass were positive predictors. CONCLUSIONS: Fewer than one-half of patients undergoing LE PVI are discharged on appropriate GDMT. As expected, traditional atherosclerotic risk factors and measures of greater atherosclerotic disease burden were associated with a greater likelihood of GDMT prescription. However, women and patients with the highest risk for atherothrombosis and limb loss were least likely to be prescribed these agents. Provider- and patient-directed educational efforts are needed to close these treatment gaps.