Data Registry Practice Innovation Research Articles

Association Between Poverty and Appropriate Statin Prescription for the Treatment of Hyperlipidemia in the United States: An Analysis From the ACC NCDR PINNACLE Registry

BackgroundPoverty is associated with a higher risk of myocardial infarction and cardiac death, both of which are decreased by treatment of hyperlipidemia. There may be differences in the appropriate treatment of hyperlipidemia between richer and poorer Americans. In this study, we aimed to evaluate the association between income level and appropriate lipid-lowering therapy. MethodsWe identified outpatient visits in the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence (PINNACLE) Registry and determined appropriateness of lipid-lowering therapy among patients in different income quintiles (Quintile 5 being the highest income quintile). Logistic regression at the patient level was performed to evaluate the independent association of income and the primary outcome of appropriate statin therapy. The analysis was repeated before and after November 2013 given a change in guideline definitions. ResultsThe study included 1,655,723 patients. Overall, 68–73% of patients were treated appropriately under the ATP III Guidelines and 57–62% of patients were treated appropriately under the ACC/AHA Guidelines. Patients in the wealthiest quintile had higher odds of appropriate statin therapy under both guidelines relative to patients in the poorest quintile (OR 1.06 [1.05–1.07] for ATP III and OR 1.03 [1.01–1.04] for ACC/AHA). In the whole sample, patients with higher estimated income had a small but significant increased likelihood of appropriate statin therapy (point-biserial correlation 0.035 [p < 0.001] for ATP III and 0.026 [p < 0.001] for ACC/AHA). ConclusionsHere we describe a small association between appropriate statin use and income. Further investigation into barriers in the use of evidence-based therapies in poorer populations is needed.

Factors associated with rhythm control treatment decisions in patients with atrial fibrillation—Insights from the NCDR PINNACLE registry

Decisions to use rhythm control in atrial fibrillation (AF) should generally be dictated by patient factors, such as quality of life, heart failure, and other comorbidities. Whether or not other factors affect decisions about the use of rhythm control, and catheter ablation in particular, is unknown. A cohort of all patients diagnosed with nonvalvular AF were identified from the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence (PINNACLE) AF registry of US outpatient cardiology practices during the study period from May 1, 2008, to December 31, 2014. Overall and practice-specific rates of rhythm control (cardioversion, antiarrhythmic drug therapy, or catheter ablation) were assessed. We assessed patient and practice factors associated with rhythm control and determined the relative contribution of patient, practice, and unmeasured practice factors with its use. Among 511,958 PINNACLE AF patients, 22.3% were treated with rhythm control and 2.9% underwent catheter ablation. Significant practice variation in rhythm control was present (median rate of rhythm control across practices 22.8%, range 0.2%-62.9%). Significant patient factors associated with rhythm control therapy included white (vs nonwhite) race (odds ratio [OR] 2.43, P<.001), private (vs nonprivate) insurance (OR 1.04, P<.001), and whether a patient was seen by an electrophysiologist (OR 1.77, P<.001). In an analysis of the relative contribution of patient, practice, and unmeasured practice factors with rhythm control, the contribution of unmeasured practice factors (95% range OR 0.29-3.44) exceeded that of either patient (95% range OR 0.46-2.30) or practice (95% range OR 0.15-2.77) factors. One in 5 AF patients in the PINNACLE registry received rhythm control, and 1 in 50 received catheter ablation, suggesting that rhythm control may be underused. A variety of measured and unmeasured practice factors unrelated to patient characteristics play a disproportionate role in the use of rhythm control treatment decisions. Understanding the drivers of these decisions may identify inappropriate treatment variation and better inform optimal use of these therapies.

Variation in performance measure criteria significantly affects cardiology practice rankings: Insights from the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence Registry

Million Hearts is a national initiative to prevent 1 million heart attacks and strokes over 5 years by improving cardiovascular prevention. An important tool in the success of programs like Million Hearts is public ranking on the quality of practices, yet different measures may provide different rankings, so the true quality of practices is difficult to discern. We evaluated the quality of ambulatory cardiology care using performance measure metrics. We compared rankings of practices participating in the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence Registry using measures from (1) the physician quality reporting system and (2) the American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement. We compared achievement rates for measures between the 2 frameworks and determined correlations in rankings using Spearman correlation coefficients. From January 1, 2008 to December 31, 2012, there were 1,711,326 patients enrolled from 111 US practices. Among eligible patients, the physician quality reporting system and American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement measures were achieved in 76.1% versus 77.4% for antiplatelet prescription (P < .001), 68.3% versus 90.8% for blood pressure control (P < .001), 26.9% versus 43.4% for cholesterol control (P < .001), and 37.4% versus 40.6% for smoking cessation (P = .383). Practice rankings were strongly correlated for antiplatelet prescription (correlation coefficient 0.98) and cholesterol control (0.92) but poorly correlated for blood pressure control (0.39) and smoking cessation (0.22). Evaluation of preventive care and individual practice rankings vary significantly depending on how measures are defined. Publicly reported measures need to be validly associated with outcomes to avoid incorrectly evaluating practice performance and failing to achieve public health goals.