Practice Innovation And Clinical Excellence Research Articles

Sociodemographic determinants of oral anticoagulant prescription in patients with atrial fibrillations: findings from the PINNACLE registry using machine learning.

Current risk scores that are solely based on clinical factors have shown modest predictive ability for understanding of factors associated with gaps in real-world prescription of oral anticoagulation (OAC) in patients with atrial fibrillation (AF). In this study, we sought to identify the role of social and geographic determinants, beyond clinical factors associated with variation in OAC prescriptions using a large national registry of ambulatory patients with AF. Between January 2017 and June 2018, we identified patients with AF from the American College of Cardiology PINNACLE (Practice Innovation and Clinical Excellence) Registry. We examined associations between patient and site-of-care factors and prescription of OAC across U.S. counties. Several machine learning (ML) methods were used to identify factors associated with OAC prescription. Among 864,339 patients with AF, 586,560 (68%) were prescribed OAC. County OAC prescription rates ranged from 26.8% to 93%, with higher OAC use in the Western United States. Supervised ML analysis in predicting likelihood of OAC prescriptions and identified a rank order of patient features associated with OAC prescription. In the ML models, in addition to clinical factors, medication use (aspirin, antihypertensives, antiarrhythmic agents, lipid modifying agents), and age, household income, clinic size, and U.S. region were among the most important predictors of an OAC prescription. In a contemporary, national cohort of patients with AF underuse of OAC remains high, with notable geographic variation. Our results demonstrated the role of several important demographic and socioeconomic factors in underutilization of OAC in patients with AF.

Abstract 11610: Obesity and Metabolic Syndrome Among Heart Failure With Preserved Ejection Fraction Patients

Introduction: Recent data show a relative increase of HFpEF in heart failure. Additionally, an increase in prevalence of obesity and metabolic syndrome (MetS) in the population have been reported. Obesity and MetS differ across race, ethnicity, and sex. We sought to examine characteristics of patients with HFpEF by both obesity and MetS status to characterize differences in patient profiles for HFpEF. Methods: We examined data from the Practice Innovation and Clinical Excellence (PINNACLE) Registry® (American College of Cardiology and Veradigm) for HFpEF patients (LVEF ≥ 50%) and receiving care in a cardiologist clinic from 2016 thru 2019. Obesity is defined as BMI ≥ 30 kg/m 2 and MetS is approximated among patients with no history of myocardial infarction by presence of three of the four conditions (dyslipidemia, hypertension, obesity, and diabetes) at baseline. Results: Among 218,843 HFpEF patients, 56.7% had obesity, 50.4% had MetS, 34.8% had neither, and 41.8% had both. Obese patients were younger than non-obese (69.9 vs 74.9 years) and MetS patients were somewhat younger than non-MetS (71.7 vs 72.5 years). Over half of non-obese (62.7%) and non-MetS (53.8%) patients were 80+ years old. A higher proportion of women were obese than non-obese (57.8 vs 47.3%), while the proportion of women with and without MetS was similar (54.7 and 54.1%). Blacks have higher proportions of both obese and MetS than without (9.8 vs 5.2% and 9.6 vs 6.5%). Hispanics also have a higher proportion of MetS than without (4.9 vs 3.9%). MetS group exhibited a higher rate of all other cardiovascular comorbidities than the obesity group except for atrial fibrilation. Conclusions: In this large cohort of HFpEF patients in the ambulatory specialist care setting, nearly 2/3 of the HFpEF patients had obesity or MetS. MetS patients reflect an older more minority population with a higher proportion of comorbidities than obese patients.

Potential Impact of 2017 American College of Cardiology/American Heart Association Hypertension Guideline on Contemporary Practice: A Cross-Sectional Analysis From NCDR PINNACLE Registry.

BackgroundClinical implications of change in the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guideline on the diagnosis and management of hypertension, compared with recommendations by 2014 expert panel and Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7), are not known.Methods and ResultsUsing data from the NCDR (National Cardiovascular Data Registry) PINNACLE (Practice Innovation and Clinical Excellence) Registry (January 2013‐Decemver 2016), we compared the proportion and clinical characteristics of patients seen in cardiology practices diagnosed with hypertension, recommended antihypertensive treatment, and achieving blood pressure (BP) goals per each guideline document. In addition, we evaluated the proportion of patients at the level of practices meeting BP targets defined by each guideline. Of 6 042 630 patients evaluated, 5 027 961 (83.2%) were diagnosed with hypertension per the 2017 ACC/AHA guideline, compared with 4 521 272 (74.8%) per the 2014 panel and 4 545 976 (75.2%) per JNC7. The largest increase in hypertension prevalence was seen in younger ages, women, and those with lower cardiovascular risk. Antihypertensive medication was recommended to 70.6% of patients per the ACC/AHA guideline compared with 61.8% and 65.9% per the 2014 panel and JNC7, respectively. Among those on antihypertensive agents, 41.2% achieved BP targets per the ACC/AHA guideline, compared with 79.4% per the 2014 panel and 64.3% per JNC7. Lower proportions of women, non‐White (Black and "other") races, and those at higher cardiovascular risk achieved BP goals. Median practice‐level proportion of patients meeting BP targets per the 2014 panel but not the ACC/AHA guideline was 37.8% (interquartile range, 34.8%–40.7%) and per JNC7 but not the ACC/AHA guideline was 22.9% (interquartile range, 19.8%–25.9%).ConclusionsFollowing publication of the 2017 guideline, significantly more people, particularly younger people and those with lower cardiovascular risk, will be diagnosed with hypertension and need antihypertensive treatment compared with previous recommendations. Significant practice‐level variation in BP control also exists. Efforts are needed to improve guideline‐concordant hypertension management in an effort to improve outcomes.

Abstract 14274: Machine Learning-Enhanced Determinants of Oral Anticoagulation in Atrial Fibrillation: Findings From the PINNACLE Registry

Introduction: Current atrial fibrillation (AF) guidelines recommend use of oral anticoagulation (OAC) to reduce the risk of stroke and systemic embolism. Machine learning (ML) techniques may enhance our understanding of factors associated with gaps in real-world prescription of OAC. Hypothesis: There will be large variation in county-level OAC prescription rates among ambulatory patients with AF, and geographic and medication factors will be stronger predictors than clinical comorbidities of lack of OAC prescriptions. Methods: Between January 2017 and June 2018, we identified patients with AF from the American College of Cardiology’s (ACC) Practice Innovation and Clinical Excellence (PINNACLE) Registry. We examined associations between patient and site-of-care factors and prescription of OAC across U.S. counties. Several ML methods were used to identify factors associated with lack of OAC prescription. Results: Among 864,339 patients with AF, 586,560 (68%) were prescribed OAC. County OAC prescription rates ranged from 26.8% (15/56) to 93% (41/44), with higher OAC use in the Western US. Supervised ML analysis (extreme gradient boosting: area under the receiver operating characteristic curve [AUC]: 0.811, 95% confidence interval [CI]: 0.809-0.813) outperformed the CHA2DS2-VASc score (AUC: 0.571, 95% CI: 0.569-0.574) in predicting likelihood of OAC prescriptions and identified a rank order of patient features associated with OAC prescription. In the ML models, use of aspirin, antihypertensives, lipid modifying agents, antiarrhythmic agents, age, inter-normalized ratio, median household income, and clinic size were the most important predictors of OAC prescription. Conclusions: In a national cohort of patients with AF underuse of OAC remains high, with notable geographic variation. ML algorithms can identify factors associated with use of OAC.

Outpatient Prescription Practices in Patients with Atrial Fibrillation (From the NCDR PINNACLE Registry)

This study sought to evaluate inappropriate prescribing practices in an atrial fibrillation (AF) population, as outlined by the 2016 ACC/AHA Clinical Performance and Quality Measures for Adults with Atrial Fibrillation or Atrial Flutter document. The 2016 AF quality measures document specified medications to avoid in certain AF populations, including aspirin and anticoagulant combination therapy in patients without cardiovascular disease, and non-dihydropyridine calcium channel blockers in patients with reduced ejection fraction. Using data from the NCDR PINNACLE registry, a national outpatient cardiology practice registry, we assessed rates of inappropriate prescription of two types of medications among AF outpatients from 5/1/2008-5/1/2016. Overall rates of inappropriate prescription and variation by practice were calculated. Patient and practice factors associated with inappropriate prescription were assessed in adjusted analyses. A total of 107,759 of 658,250 (16.4%) patients without cardiovascular disease were inappropriately prescribed an antiplatelet and anticoagulant together, and 5,731 of 150,079 (3.8%) patients with reduced ejection fraction were inappropriately prescribed a non-dihydropyridine calcium channel blocker. Overall, 14.8% of AF patients were prescribed medications that were not recommended. Both patient and practice factors were associated with inappropriate prescribing, and the adjusted practice-level median odds ratio for inappropriate prescription was 1.70 (95% CI: 1.61-1.82), indicating a 70% likelihood that 2 random practices would treat identical AF patients differently. In a large registry of AF patients treated in cardiology practices, overall rates of inappropriate prescription practices, as defined by the 2016 AF quality measures, were relatively low, but significant practice variation was present.

Representativeness of the VICTORIA Trial Population in Clinical Practice: Analysis of the PINNACLE Registry

In the VerICiguaT Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial, vericiguat reduced the risk of mortality due to cardiovascular problems and of hospitalization due to heart failure (HF) among patients with HF with reduced ejection fraction (HFrEF) and recent worsening HF events (WHFEs). The representativeness of the VICTORIA population of patients with WHFE in clinical practice is unknown. Patients with HF and ejection fraction <45% were identified in the Practice Innovation And Clinical Excellence (PINNACLE) registry and were stratified by the occurrence of WHFEs. Characteristics and outcomes of patients in the PINNACLE registry with and without WHFEs were compared to the VICTORIA population. Of the 14,180 PINNACLE patients identified with HFrEF, 26.5% had had a WHFE. The VICTORIA population was similar to PINNACLE patients with WHFEs in mean age (67.3 vs 66.7), ejection fraction (28.9% vs 28.3%), body mass index (26.8 vs 27.6), and comorbidity burden. The rate of hospitalization because of HF at 1 year was 29.6% in the placebo group of VICTORIA, compared to 35.8% in PINNACLE patients with WHFEs and 13.3% in patients without WHFEs. The PINNACLE patients with WHFEs meeting the VICTORIA definition resembled the VICTORIA population in characteristics and outcomes, suggesting that VICTORIA's population may be generalizable to patients with WHFEs in clinical practice.

Racial disparities among Asian Americans with atrial fibrillation: An analysis from the NCDR® PINNACLE Registry

BackgroundThere is paucity of data on Atrial Fibrillation (AF) management and associated clinical outcomes among Asian Americans. This study sought to investigate baseline risk factor profiles, racial disparities in clinical management and adverse clinical outcomes among White and Asian Americans. MethodsWe used National Cardiovascular Data Registry (NCDR®) Practice Innovation and Clinical Excellence (PINNACLE) registry and linked Centers of Medicare and Medicaid Services data to identify Asian and White patients with AF between January 1, 2013–June 30, 2018. We compared rates of baseline risk factors, management strategies (rate versus rhythm control), anticoagulation use and rates of adverse events between racial groups. The two race groups were compared using hierarchical multivariable adjusted regression models to account for site and confounders. ResultsIn total, 1,359,827 patients (18,793 Asians and 1,341,034 Whites) were included in our analysis. Compared to White Americans, Asian Americans were more likely to use a rate control strategy (Odds Ratio [OR]: 1.20, 95% Confidence Interval [CI]: 1.15–1.25) and lower odds of rhythm control strategy (atrial ablations, cardioversions, or use of antiarrhythmic drugs) (OR: 0.83, 95% CI: 0.80–0.87) in adjusted analysis. Use of oral anticoagulants and direct oral anticoagulants were similar. There were no significant race-based differences in likelihood of all-cause mortality, stroke, and bleeding requiring hospitalization. Analyses performed using propensity score matching were consistent with the main results. ConclusionsAsian Americans with AF have a lower likelihood of being managed with rhythm control strategies. Overall use of OAC and AF related adverse events remain similar between the two racial groups.

Abstract 16634: Treatment Patterns &amp; Clinical Outcomes Among Asian Americans With Atrial Fibrillation: An Analysis From the NCRD® PINNACLE Registry

Introduction: Although treatment modalities for Atrial Fibrillation (AF) continue to evolve, there is paucity of data on AF management and associated clinical outcomes among Asian Americans (AA). We investigated risk factor profiles, racial disparities in clinical management and associated adverse clinical outcomes among AA compared to Whites. Hypothesis: Racial disparities exist between White and AA with regards to AF management and related adverse clinical outcomes. Methods: Using the National Cardiovascular Data Registry (NCDR®) Practice Innovation and Clinical Excellence (PINNACLE) registry and linked Centers of Medicare and Medicaid Services data to identify AA and White patients with AF between 1/1/13-6/30/18, we characterized risk factors, management strategies (rate vs. rhythm control), anticoagulation use and rates of adverse events across racial groups. The two race groups were compared using hierarchical multivariable adjusted regression models to account for site and potential confounders. Results: Our analysis included 1359827 patients with AF (18793 AA; 1341034 Whites). Compared to Whites, AA were more likely to be treated with rate control strategy (OR:1.20, 95% CI:1.15-1.25) in adjusted analyses. AA had lower odds of use of rhythm control strategy (atrial ablations, cardioversions, or use of antiarrhythmic drugs) (OR:0.83, 95% CI:0.80-0.87). Overall use of oral anticoagulants (OAC) and direct oral anticoagulants were similar across both racial groups. There were no significant race-based differences in likelihood of adverse clinical events including all-cause mortality, strokes, and bleeding. Analyses performed using propensity score matching were consistent with the main results. Conclusions: AA with AF have a lower likelihood of being managed with rhythm control strategies. Overall use of OAC and AF related adverse events remain similar between the two racial groups.

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.

Prescription Patterns of Clopidogrel, Prasugrel, and Ticagrelor After Percutaneous Coronary Intervention With Stent Implantation (from the NCDR PINNACLE Registry)

The use of prasugrel and ticagrelor as part of dual antiplatelet therapy is increasing in patients after percutaneous coronary intervention (PCI). Accordingly, we aimed to evaluate their prescription patterns in the National Cardiovascular Data Registry (NCDR) Practice Innovation and Clinical Excellence (PINNACLE) registry. We analyzed patients enrolled in NCDR PINNACLE registry from January 2013 to March 2015 who underwent PCI with drug-eluting stent and were prescribed dual antiplatelet therapy. All patients received aspirin. The primary study outcome was a 3-level variable denoting the second antiplatelet agent prescribed: (1) clopidogrel, (2) prasugrel, or (3) ticagrelor. Baseline characteristics were compared among the 3 groups. Odds ratios and 95% credible intervals were calculated from a nested hierarchical Bayesian logistic regression models to identify independent predictors of prescription of antiplatelet medications, incorporating practice and provider as random effects. Our study cohort consisted of 26,710 patients during our study period January 2013 to March 2015. Seventy nine percent of patients were prescribed clopidogrel, 12% prasugrel, and 11% ticagrelor. Patients aged ≥75 years, women, history of tobacco use, Peripheral Arterial Disease (PAD), hypertension, diabetes, previous vascular complication, heart failure, and stroke/transient ischemic attack were more likely to be on clopidogrel than prasugrel or ticagrelor. The relative percentages of ticagrelor and prasugrel were higher in patients with history of myocardial infarction, compared with those without myocardial infarction. In summary, our study highlights the prescription patterns associated with prescription of antiplatelet agents after PCI. We found that both ticagrelor and prasugrel were mostly prescribed per the current practice guidelines, thus reflecting appropriate guideline adherence by practices in NCDR PINNACLE registry.

Heart failure with mid-range ejection fraction: characterization of patients from the PINNACLE Registry®.

AimsGuidelines for management of patients with heart failure with mid‐range ejection fraction [HFmrEF; left ventricular EF (LVEF) 41–49%] do not exist. Disagreement exists whether HFmrEF should be considered a distinct group. The aim of this study is to examine characteristics of patients with HFmrEF with HF with reduced EF (HFrEF; LVEF ≤ 40%) or preserved EF (HFpEF; LVEF ≥ 50%).Methods and resultsWe examined data collected in the American College of Cardiology's National Cardiovascular Data Registry (NCDR) Practice Innovation and Clinical Excellence (PINNACLE) Registry® for first HF patient visits between 1 May 2008 and 30 June 2016. Analysis was performed using ANOVA F‐tests (or Kruskal–Wallis tests for non‐normally distributed variables) for continuous parameters and χ 2 tests for nominal covariates at the first diagnosed HF visit. Given the NCDR PINNACLE Registry® is a US‐based registry, we opted to define HFmrEF as per the US guidelines, which define HFmrEF as LVEF 41–49% in contrast to European guidelines, which define HFmrEF as LVEF 40–49%. Among 1 103 386 patients with available data, 36.1% (N = 398 228) had HFrEF, 7.5% (N = 82 292) had HFmrEF, and 56.5% (N = 622 866) had HFpEF. Compared with patients with HFrEF or HFpEF, patients with HFmrEF had more prevalent coronary and peripheral artery disease and more history of myocardial infarction, percutaneous coronary intervention, or coronary artery bypass surgery (all P < 0.001). Patients with HFmrEF were also more likely to have atrial fibrillation/flutter, diabetes, and chronic kidney disease and to have a history of tobacco use (both P < 0.001). Among those with EF assessment prior to this analysis, only 4.8% (N = 1032) previously had HFrEF that improved to HFmrEF; 32.9% (N = 7072) had HFpEF previously and progressed to HFmrEF. Those patients who transitioned from HFpEF to HFmrEF had considerably more complex profiles and were less aggressively managed compared with those who remained with HFmrEF (all P < 0.001).ConclusionsIn this large descriptive analysis, patients with HFmrEF had an atherothrombotic phenotype distinct from other forms of HF. Interventions aimed at treating coronary ischaemia and addressing prevalent risk factors may play a particularly important role in the management of patients with HFmrEF.

Provider-Level Variation in Smoking Cessation Assistance Provided in the Cardiology Clinics: Insights From the NCDR PINNACLE Registry.

BackgroundStudies show suboptimal provision of smoking cessation assistance (counseling or pharmacotherapy) for current smokers attempting to quit. We aimed to identify smoking cessation assistance patterns in US cardiology practices.Methods and ResultsAmong 328 749 current smokers seen between January 1, 2013, and March 31, 2016, in 348 NCDR (National Cardiovascular Data Registry) PINNACLE (Practice Innovation and Clinical Excellence)‐affiliated cardiology practices, we measured the rates of cessation assistance. We used multivariable hierarchical logistic regression models to determine provider‐, practice‐, and patient‐level predictors of cessation assistance. We measured provider variation in cessation assistance using median rate ratio (the likelihood that the same patient would receive the same assistance at by any given provider; >1.2 suggests significant variation). Smoking cessation assistance was documented in only 34% of encounters. Despite adjustment of provider, practice, and patient characteristics, there was large provider‐level variation in cessation assistance (median rate ratio, 6 [95% CI, 5.76–6.32]). Practice location in the South region (odds ratio [OR], 0.48 [0.37–0.63] versus West region) and rural or suburban location (OR, 0.92 [0.88–0.95] for rural; OR, 0.94 [0.91–0.97] for suburban versus urban) were associated with lower rates of cessation assistance. Similarly, older age (OR, 0.88 [0.88–0.89] per 10‐year increase), diabetes mellitus (OR, 0.84 [0.82–0.87]), and atrial fibrillation (OR, 0.93 [0.91–0.96]) were associated with lower odds of receiving cessation assistance.ConclusionsIn a large contemporary US registry, only 1 in 3 smokers presenting for a cardiology visit received smoking cessation assistance. Our findings suggest the presence of a large deficit and largely idiosyncratic provider‐level variation in the provision of smoking cessation assistance.

Differences in Management of Coronary Artery Disease in Patients With Medicare Advantage vs Traditional Fee-for-Service Medicare Among Cardiology Practices

One-third of Medicare beneficiaries are enrolled in Medicare Advantage (MA), Medicare's private plan option. Medicare Advantage incentivizes performance on evidence-based care, but limited information exists using reliable clinical data to determine whether this translates into better quality for patients with coronary artery disease (CAD) enrolled in MA compared with those enrolled in traditional fee-for-service (FFS) Medicare. To determine differences in evidence-based secondary prevention treatments and intermediate outcomes among patients with CAD enrolled in MA vs FFS Medicare. In this observational, retrospective, cohort study, deidentified data from patients 18 years or older diagnosed as having CAD between January 1, 2013, and May 1, 2014, at cardiology practices participating in the Practice Innovation and Clinical Excellence (PINNACLE) registry were studied, including 35 563 patients enrolled in MA and 172 732 enrolled in FFS Medicare. Data were analyzed from March to July 2018. Medicare Advantage enrollment. Medication prescription patterns among eligible patients and intermediate outcomes, including blood pressure and low-density lipoprotein cholesterol. Of the 35 563 patients with CAD enrolled in MA, 20 193 (56.8%) were male, and the mean (SD) age was 76.7 (7.6) years; of the 172 732 patients with CAD enrolled in FFS Medicare, 100 025 (57.9%) were male, and the mean (SD) age was 77.5 (8.0) years. Patients enrolled in MA were younger, less likely to be white, and more likely to be female and to have heart failure, diabetes, and chronic kidney disease compared with those enrolled in FFS Medicare. Compared with FFS Medicare beneficiaries, MA beneficiaries were more likely to receive secondary prevention treatments, including β-blockers (80.6% vs 78.8%; P < .001), angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (70.7% vs 65.1%; P < .001), and statins (68.4% vs 64.5%; P < .001). Patients enrolled in MA were also more likely to receive all 3 medications when eligible (48.9% vs 40.4%; P < .001). After adjustment, MA beneficiaries had higher odds of receiving guideline-recommended therapy compared with FFS Medicare beneficiaries for β-blockers (odds ratio, 1.10; 95% CI, 1.04-1.17; P = .002), angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (odds ratio, 1.13; 95% CI, 1.08-1.19; P < .001), and all 3 medications (odds ratio, 1.23; 95% CI, 1.001-1.50; P = .047). There were no significant differences in intermediate outcomes between those enrolled in MA and FFS Medicare, including systolic and diastolic blood pressure and low-density lipoprotein cholesterol levels. Among patients with CAD in the PINNACLE registry, MA beneficiaries had more comorbidities than FFS Medicare beneficiaries and were more likely to receive secondary prevention treatments. However, this did not translate into differences in intermediate outcomes. These findings suggest that MA plans may drive improvements in process-based quality measures for Medicare beneficiaries, although this may have a limited effect on improving patient outcomes over FFS Medicare.

Signs, symptoms, and treatment patterns across serial ambulatory cardiology visits in patients with heart failure: insights from the NCDR PINNACLE\xae registry

BackgroundDue to a relative lack of outpatient heart failure (HF) clinical registries, we aimed to describe symptoms, signs, and medication treatment among ambulatory patients with heart failure (HF) over time.MethodsUsing health records from 234 PINNACLE (Practice Innovation and Clinical Excellence) U.S. cardiology practices (2008–2014), serial visits for patients with HF were characterized. Symptoms, signs, and HF medications (angiotensin-converting enzyme inhibitors [ACEI], angiotensin receptor blockers [ARB], beta blockers [BB], and diuretics) were compared between visits.ResultsAmong 763,331 patients with HF, 550,581 had ≥2 clinic visits < 1 year apart, with 2,998,444 visit pairs. In the 12 months following an index visit, patients had a mean of 2.5 ± 2.3 additional visits. Recorded index visit symptoms ranged from dyspnea (53.6%) to orthopnea (23.1%); signs ranged from peripheral edema (52.2%) to hepatomegaly (0.6%). Of those with ejection fraction < 40%, ACEI was prescribed in 58.6%, ARB in 18.5%, BB in 85.2%, and diuretics in 70.0%. Between-visit recorded changes were infrequent: dyspnea appeared in 3.8%, resolved in 2.7%; NYHA class increased in 2.9%, decreased in 2.9%; number of signs increased in 6.0%, decreased in 5.1%; ACEI/ARB or BB added in 6.4%, removed in 6.2%; diuretic added in 3.7%, removed in 3.8%. Changes in recorded symptoms were rarely associated with initiation or discontinuation in HF medication classes.ConclusionsAmbulatory HF care in U.S. cardiology practices seldom recorded changes in symptoms, signs, and medication class. Although templated medical records and absence of medication dosing likely underestimated the degree to which clinical changes occur over serial visits for HF, these PINNACLE data suggest opportunities for greater symptom-based and therapy-focused visits.

Quality and Safety in Health Care, Part XXXIV: Coronary Artery Disease Secondary Prevention Medications.

There is an important opportunity for improvement in the care of cardiology outpatients by having greater compliance with published guidelines, and the PINNACLE (Practice Innovation and Clinical Excellence) Registry seeks to do that. One of the major areas studied by this registry is the use of secondary prevention medications for patients with coronary artery disease. Appropriate use of these medications decreases later myocardial infarctions and death from a cardiac cause.

Quality and Safety in Health Care, Part XXXIV: The PINNACLE Registry.

The PINNACLE (Practice INNovation And Clinical Excellence) program was started in 2008 by the American College of Cardiology and its National Cardiovascular Data Registry. This was the first and now the largest countrywide prospective registry to improve care quality for cardiac outpatients. The registry focuses on reporting about the adherence to guidelines in treating individuals with high blood pressure, atrial fibrillation, coronary artery disease, and/or cardiac failure.

Electronic health records and outpatient cardiovascular disease care delivery: Insights from the American College of Cardiology’s PINNACLE India Quality Improvement Program (PIQIP)

BackgroundThere has been a push toward implementation of electronic health records (EHRs) in federally-funded hospitals under the current policies initiated by the Indian government, with a lack of evidence supporting their adoption. We analyzed data from the American College of Cardiology’s PINNACLE (Practice Innovation and Clinical Excellence) India Quality Improvement Program (PIQIP) to evaluate the association between EHR use and quality of cardiovascular disease care in India. Methods and ResultsBetween 2011–2016, we collected data on performance measures for patients with coronary artery disease (CAD), heart failure (HF) and atrial fibrillation (AF) among 17 participating practices in PIQIP. There were 19,035 patients with CAD, 9,373 patients with HF, and 1,127 patients with AF. Documentation of co-morbidity burden in patients with CAD was lower among practices with EHR—hypertension (49.8% vs. 52.1%, p=0.003), diabetes (34.9% vs. 38.3%, p<0.001), and hyperlipidemia (0.2 vs. 3.9%, p<0.001). On the contrary, documentation of medication prescription was higher in CAD patients seen at practices with EHR—aspirin (63.2% vs. 17.8%, p<0.001), clopidogrel (41.7% vs. 27.4%, p<0.001), beta-blockers (61.4% vs. 9.8%, p<0.001), and ACE-i or ARBs (53.9% vs. 16.4%, p<0.001). Similarly, documentation of receipt of beta-blockers (43.8% vs. 10.7%, p<0.001), ACE-i or ARBs (40.8% vs. 16.1%, p<0.001), and beta-blockers+ACE-i or ARBs (36.4% vs. 3.6%, p<0.001) was also significantly higher in patients with HF seen at practices with EHR. Among patients with AF, documentation of oral anticoagulation use was significantly higher among EHR practices—warfarin (42.5% vs. 26.1%, p<0.001). ConclusionsDocumentation of receipt of guideline-directed medical therapy in CAD, HF, and AF was significantly higher in practices with EHRs in India compared with sites without EHRs. Our findings shed a spotlight on the value of EHRs in future health care policy-making in India with regard to widespread adoption of EHRs in primary and advanced specialty care settings across public and private sectors.

RETRACTED: Addition or removal of guideline directed medical therapy in ambulatory patients with heart failure with reduced ejection fraction relative to change in symptom severity: An analysis from the PINNACLE (Practice Innovation and Clinical Excellence) Registry®

RETRACTED: Addition or removal of guideline directed medical therapy in ambulatory patients with heart failure with reduced ejection fraction relative to change in symptom severity: An analysis from the PINNACLE (Practice Innovation and Clinical Excellence) Registry®

132 - Addition or Removal of Guideline Directed Medical Therapy in Ambulatory Patients with Heart Failure with Reduced Ejection Fraction Relative to Change in Symptom Severity. An Analysis from the PINNACLE (Practice Innovation and Clinical Excellence) Registry

132 - Addition or Removal of Guideline Directed Medical Therapy in Ambulatory Patients with Heart Failure with Reduced Ejection Fraction Relative to Change in Symptom Severity. An Analysis from the PINNACLE (Practice Innovation and Clinical Excellence) Registry

133 - Patients with Heart Failure with Mid-Range Ejection Fraction Have a Distinct Clinical Profile: An Analysis from the PINNACLE (Practice Innovation and Clinical Excellence) Registry

Background: Guidelines for management of patients with heart failure with mid-range ejection fraction (HFmrEF; EF 41–49%) do not exist. Improved understanding of patients with HFmrEF might help guide efforts to optimally manage this unique group of patients. Hypothesis: We hypothesized patients with HFmrEF represent a distinct population of HF patients as compared to patients with HF with reduced EF (HFrEF; EF ≤40%) or preserved EF (HFpEF; EF ≥50%). Methods: We examined data collected in the PINNACLE Registry® for first HF patient encounters between May 1, 2008 and June 30, 2016. Analysis was done using ANOVA F-tests (or Kruskal-Wallis tests for non-normally distributed variables) for continuous parameters and Chi-Squared tests for nominal covariates at the first diagnosed HF encounter. Results: There were 697,542 patients with a diagnosis of HF in the PINNACLE Registry® with available information for analysis. Of these, 46.5% (N = 324,387) had HFpEF, 45.4% (N = 316,628) had HFrEF, and 8.1% (N = 56,527) had HFmrEF. Compared to patients with HFrEF or HFpEF, patients with HFmrEF had more prevalent coronary artery and peripheral artery disease, and were more likely to have history of prior myocardial infarction, percutaneous coronary intervention, coronary artery bypass surgery, and peripheral arterial disease. Patients with HFmrEF had highest prevalence of diabetes and tobacco use (Table 1). Conclusions: Compared to patients with HFpEF or HFrEF, patients with HFmrEF have a unique clinical phenotype that may require targeted therapeutic strategies for optimal management.Table 1Characterization of HFmrEF PatientsCharacteristicsAll HF(N = 697542)HFrEF(EF ≤40%)(N = 316628)HFmrEF(EF 41–49%)(N = 56527)HFpEF(EF ≥50%)(N = 324387)PAge (years)69.9 ± 13.2 (697542)68.0 ± 13.4 (316628)70.6 ± 12.8 (56527)71.7 ± 12.8 (324387)<0.001Male58.2% (405924)67.5% (213809)65.9% (37276)47.7% (154839)<0.001LVEF (%)45.8 ± 16.2 (639368)29.7 ± 7.9 (274783)45.0 ± 1.9 (51599)60.1 ± 6.9 (312986)<0.001Coronary artery disease64.6% (450565)65.6% (207862)71.9% (40654)62.3% (202049)<0.001Myocardial infarction23.8% (166262)26.8% (84713)29.3% (16552)20.0% (64997)<0.001PCI/PTCA20.3% (141531)18.4% (58211)23.3% (13157)21.6% (70163)<0.001CABG13.6% (95195)13.9% (44080)17.6% (9976)12.7% (41139)<0.001Peripheral arterial disease13.4% (93205)11.5% (36266)15.5% (8754)14.9% (48185)<0.001Stroke11.9% (82769)10.2% (32447)11.9% (6703)13.4% (43619)<0.001Atrial fibrillation/flutter35.3% (246229)30.3% (96071)39.1% (22107)39.5% (128051)<0.001Diabetes (type I or II)28.0% (195472)26.6% (84374)30.7% (17332)28.9% (93766)<0.001Hypertension78.3% (546514)70.5% (223366)80.5% (45509)85.6% (277639)<0.001Chronic kidney disease4.6% (32258)3.8% (12003)5.3% (3014)5.3% (17241)<0.001Tobacco use- never42.0% (265874/633196)39.3% (110870/282222)38.2% (19667/51439)45.2% (135337/299535)<0.001Beta blocker73.4% (512222)78.7% (249260)78.6% (44457)67.4% (218505)<0.001ACEI/ARB62.1% (433203)68.3% (216114)65.6% (37069)55.5% (180020)<0.001Diuretic53.8% (375195)54.1% (171241)56.7% (32061)53.0% (171893)<0.001 Open table in a new tab