Diverse factors are associated with variations in evidence-based treatment of outpatients with heart failure (HF). However, patient and practice characteristics associated with improved use of guideline-recommended therapies over time have not been well studied. The Registry to Improve the Use of Evidence-Based Heart Failure Therapies in the Outpatient Setting (IMPROVE HF) is a prospective evaluation of a performance improvement initiative conducted at 167 practices treating outpatients with diagnosed HF or previous myocardial infarction and left ventricular ejection fraction ≤35%. Patient characteristics and care practice data were collected by chart abstraction at baseline and 24 months for 14,236 patients. Seven individual care measures and a composite measure were assessed. Practices were stratified by tertiles of composite measure improvement, and significant, independent patient and practice factors associated with improvement in the composite measure at 24 months were examined. The baseline composite performance measure was 68.4%, which increased to 80.1% at 24 months (+11.6%, p <0.001). The composite measure improvement tertiles were ≤8%, >8% to 15%, and >15%. Multivariate analyses revealed greater improvements associated only with lower practice baseline composite measure rates (p <0.001). Logistic regression showed that 2 additional variables were inversely associated with practices in the highest tertile in composite measure improvement (>15%): southern practice location (p = 0.0239) and edema (p = 0.0047). In conclusion, few patient and practice factors were associated with greater or lesser overall improvements over time in the use of guideline-recommended HF therapies. Other factors may be more important determinates of the magnitude of care improvements over time among cardiology practices participating in a performance improvement initiative.
The identification of factors associated with improvements in the use of guideline-recommended heart failure (HF) therapies can provide guidance to clinicians and practices with an interest in improving the quality of care. In addition, lessons learned from increased adherence to recommended HF therapies may be relevant to improving clinical care and patient outcomes associated with other cardiovascular conditions. Despite the substantial attention given to changing physicians’ practices and improving the quality in clinical care for patients with HF, studies identifying specific patient and practice characteristics associated with improvements in care are limited. In the present study, we evaluated factors associated with improvement in the use of guideline-recommended therapies over time in outpatient cardiology practices treating patients with HF or previous myocardial infarction (MIs) and left ventricular ejection fraction ≤35%. We also assessed differences among practices that demonstrated lesser or greater degrees of improvement in a composite care measure from baseline to 24 months and identified patient and practice characteristics that were significant predictors of improvement in the composite care measure between baseline and 24 months.
Methods
The Registry to Improve the Use of Evidence-Based Heart Failure Therapies in the Outpatient Setting (IMPROVE HF) is a prospective evaluation of the effectiveness of a practice-based performance improvement intervention on adherence to guideline-recommended treatment of patients with HF or previous MI and left ventricular systolic dysfunction. The methods of IMPROVE HF and study objectives were previously described. Patients eligible for IMPROVE HF included those attending outpatient cardiology and multispecialty practices with clinical diagnoses of HF or post-MI documented on ≥2 separate visits and left ventricular systolic dysfunction, defined as a left ventricular ejection fraction ≤35% or moderate to severe dysfunction demonstrated by echocardiography, nuclear multiple gated acquisition scan, contrast ventriculography, or magnetic resonance imaging scan. Patients with an estimated survival time <1 year because of medical conditions other than HF and those who had undergone heart transplantation were not eligible for study participation. Community and academic cardiology or multispecialty outpatient practices across the United States were invited to participate in IMPROVE HF.
A representative sample of patient medical records from each cardiology practice was screened to yield an average of 90 eligible patients for each assessment period. Trained chart reviewers abstracted patient information at baseline and at 24 months after the implementation of the performance improvement intervention. Data for 15,177 patients from 167 practices were available at baseline. Patients with data collection forms reported at baseline and 24-month follow-up with a visit in the 24-month timeframe and living at 24 months were included in the present analyses (7,605 patients from 155 sites). Data abstracted from eligible patients’ medical charts included demographics, medical history, previous treatments, New York Heart Association functional status, QRS duration on the most recent electrocardiogram, laboratory and diagnostic tests and results, HF treatments, and documentation of HF education. Contraindications and other reasons for not administering evidence-based therapies for HF were also collected. These included documentation of patient noncompliance with treatment, patient refusal, and medical, economic, social, religious, or other reasons to withhold recommended therapies. All participating practices completed a survey at baseline to assess practice characteristics, including geographic location, practice setting, affiliations with hospitals or transplantation centers, staffing patterns (e.g., number of cardiologists, interventionalist cardiologists, electrophysiologists, and HF advanced practice nurses on staff), annual number of patients treated, presence of HF or device clinics, and type of medical record system.
The IMPROVE HF Steering Committee prospectively selected 7 HF quality measures using a process previously described. Measures included the use of angiotensin-converting enzyme inhibitors and/or angiotensin receptor blockers, β blockers, aldosterone receptor antagonists, anticoagulation therapy for atrial fibrillation, implantable cardioverter-defibrillators, cardiac resynchronization therapy, and patient education about HF. Patients eligible for inclusion in the calculation for each individual care measure included only those who met the criteria for a given therapy and for whom there were no contraindications, intolerance, or documented rationale to explain why the therapy was not provided. A composite measure of quality of care was calculated by dividing the sum of the numerator for each of the 7 care measures by the sum of the denominator for each quality measure at each practice.
The Steering Committee followed a structured, evidence-based, guideline-driven process to develop the components of the performance improvement intervention, which was intended to improve efforts by practices to provide guideline-recommended HF care. The intervention included (1) a clinical decision support tool kit, (2) structured improvement strategies, and (3) chart audits with performance feedback. The clinical decision support tool kit reviewed clinical trials, current HF treatment guidelines, and evidence-based treatment algorithms for HF therapies as well as practice reminder cards summarizing treatment algorithms. Materials for the structured improvement activities included patient assessment and management forms to be completed at each visit and patient education materials. The chart audits allowed the principal investigators at each practice to create real-time practice profile reports that summarized current practice treatment patterns, provided blinded summaries of individual physician treatment practices, and generated lists of patients not receiving recommended therapies. Data from national, regional, and local practices with similar characteristics were provided as comparative benchmarks. Educational and interactive Web-based seminars were held bimonthly. Further details regarding site selection, support, and feedback are described in the IMPROVE HF primary results publication.
Measures to ensure the quality and accuracy of data included the use of 34 centralized chart reviewers, who received ongoing training and testing to maintain the accuracy of data abstraction. The average interrater reliability was quite high (κ = 0.82). Monthly reports provided assessments of data quality, including checks of completeness and accuracy. In addition, an average of 1.7 automated data quality checks were collected per data field. An audit of randomly selected practice sites confirmed the accuracy of patient data capture from the source documentation (94.5% concordance, range 92.3% to 96.3%) for 20% of the patient population from 10% of sites. All practices were approved by local or central institutional review boards or received institutional review board waivers. The coordinating center for IMPROVE HF was Outcome Sciences, Inc. (Cambridge, Massachusetts).
Prespecified statistical analyses were performed by independent biostatisticians contracted by Outcome Sciences. Assessment of adherence to guideline-recommended care was based on a longitudinal cohort of the same patients with their medical records reviewed at baseline and at 24 months after the intervention. Descriptive statistics were calculated for patient and practice characteristics at baseline and 24-month follow-up. Absolute improvement in the composite performance measure was calculated as the 24-month percentage minus baseline percentage for the composite performance measure. Multivariate stepwise regression analyses using the composite measure as a continuous variable and multivariate logistic regression using the upper tertile percent improvement in the composite measure score as a dichotomous variable identified patient and practice characteristics that were independent predictors of improvement in the composite score at 24 months. Continuous patient characteristics were averaged for each practice, and categorical patient characteristics were categorized as a percentage at each site. All statistical inference testing was 2 sided, and results were considered statistically significant if the p value was ≤0.05. Analyses were completed using SAS version 9.1 (SAS Institute Inc., Cary, North Carolina).
Results
Baseline medical records for 14,236 patients attending 155 outpatient cardiology practices from 2005 to 2008 were included in these analyses. Quality of care substantially improved in outpatient cardiology practices over the 24-month study period. Specifically, the composite performance measure increased from 68.4% at baseline to 80.1% after 24 months of participation in the IMPROVE HF initiative (absolute improvement 11.6%, p <0.001). The range of composite measure change at the practice level from baseline to 24 months was −15.9% to 46.1% (median 11.1%, 25th to 75th percentiles 5.4% to 17.6%). Practices were divided into tertiles on the basis of the percentage improvement from baseline to 24 months in the composite performance measure. Tertile 1 (≤8% improvement) included practices with worsening, no improvement, and up to 8% improvement, whereas tertiles 2 and 3 included practices with >8% to 15% improvement and >15% improvement, respectively. Significant differences between the composite measure tertiles were associated with patient age, race, type of health insurance, origin of HF, New York Heart Association functional class, sodium and potassium levels, QRS duration ≥120 ms, histories of asthma, atrial fibrillation or flutter, coronary artery disease, depression, diabetes, hypertension, and symptoms of chest pain, dyspnea, and rales on the most recent clinical examination ( Table 1 ). Most practice characteristics were similar between the 3 composite measure tertiles, with only region of practice (p = 0.004) and hospital-based practice (p = 0.037) found to be significantly different among the tertiles ( Table 2 ). Comparison of the adoption of ≥1 performance improvement strategy by composite measure tertiles revealed higher rates of improvement among practices in the highest tertile ( Table 2 ). Practices in the upper tertile had significantly greater improvement compared to the lower tertile practices when the benchmarked quality report or ≥1 of 3 performance improvement strategies was implemented (p = 0.024 and p = 0.021, respectively).
| Practice Composite Measure (Percentage Improvement) | ||||
|---|---|---|---|---|
| ≤8% | >8%–15% | >15% | ||
| Characteristic | (n = 5,209, Practice n = 51) | (n = 4,559, Practice n = 51) | (n = 4,468, Practice n = 53) | p Value ⁎ |
| Age (years) | 69.1 ± 12.9 (71.0) | 67.2 ± 13.7 (69.0) | 69.7 ± 13.0 (71.0) | <0.001 |
| Gender | 0.330 | |||
| Female | 1,503 (28.9%) | 1,294 (28.4%) | 1,331 (29.8%) | |
| Male | 3,703 (71.1%) | 3,262 (71.6%) | 3,137 (70.2%) | |
| Race | <0.001 | |||
| Black | 307 (5.9%) | 694 (15.2%) | 353 (7.9%) | |
| White | 1,972 (37.9%) | 2,252 (49.4%) | 1,798 (40.2%) | |
| Other | 66 (1.3%) | 96 (2.1%) | 95 (2.1%) | |
| Not documented/missing | 2,864 (55.0%) | 1,517 (33.3%) | 2,222 (49.7%) | |
| Insurance type | <0.001 | |||
| Medicare | 3,199 (61.4%) | 2,729 (59.9%) | 2,668 (59.7%) | |
| Medicaid | 161 (3.1%) | 225 (4.9%) | 120 (2.7%) | |
| Private | 1,279 (24.6%) | 1,146 (25.1%) | 1,096 (24.5%) | |
| Other | 73 (1.4%) | 199 (4.4%) | 227 (5.1%) | |
| Not documented | 412 (7.9%) | 169 (3.7%) | 304 (6.8%) | |
| None | 50 (1.0%) | 86 (1.9%) | 45 (1.0%) | |
| Ischemic origin of HF | 3,277 (62.9%) | 2,992 (65.6%) | 3,109 (69.6%) | <0.001 |
| Previous MI | 2,082 (40.0%) | 1,818 (39.9%) | 1,778 (39.8%) | 0.985 |
| Previous CABG | 1,664 (31.9%) | 1,396 (30.6%) | 1,372 (30.7%) | 0.281 |
| Previous PCI | 1,275 (24.5%) | 1,157 (25.4%) | 1,186 (26.5%) | 0.066 |
| Previous AF/atrial flutter | 1,751 (33.6%) | 1,297 (28.4%) | 1,338 (29.9%) | <0.001 |
| Previous PVD | 598 (11.5%) | 547 (12.0%) | 500 (11.2%) | 0.476 |
| History of diabetes mellitus | 1,777 (34.1%) | 1,610 (35.3%) | 1,458 (32.6%) | 0.027 |
| History of hypertension | 3,178 (61.0%) | 2,942 (64.5%) | 2,737 (61.3%) | <0.001 |
| History of COPD | 875 (16.8%) | 782 (17.2%) | 723 (16.2%) | 0.457 |
| History of depression | 462 (8.9%) | 475 (10.4%) | 361 (8.1%) | <0.001 |
| NYHA documentation | <0.001 | |||
| Quantitatively documented | 1,826 (35.1%) | 1,688 (37.0%) | 1,416 (31.7%) | |
| Qualitatively documented | 3,187 (61.2%) | 2,760 (60.5%) | 2,899 (64.9%) | |
| Missing | 196 (3.8%) | 111 (2.4%) | 153 (3.4%) | |
| NYHA class | <0.001 | |||
| I | 1,914 (36.8%) | 1,533 (33.6%) | 1,634 (36.6%) | |
| II | 1,900 (36.5%) | 1,789 (39.3%) | 1,658 (37.1%) | |
| III | 1,029 (19.8%) | 1,025 (22.5%) | 932 (20.9%) | |
| IV | 170 (3.3%) | 101 (2.2%) | 91 (2.0%) | |
| LVEF (%) | 25.3 ± 6.9 (25.0) | 25.4 ± 7.1 (25.0) | 25.6 ± 7.1 (25.0) | 0.109 |
| SBP (mm Hg) | 120.6 ± 19.3 (120) | 119.9 ± 18.7 (120) | 120.7 ± 18.4 (120) | 0.088 |
| DBP (mm Hg) | 70.3 ± 11.3 (70) | 70.5 ± 11.5 (70) | 70.2 ± 11.1 (70) | 0.338 |
| HR at rest (beats/min) | 72.2 ± 11.2 (72) | 72.1 ± 11.8 (71) | 72.2 ± 11.4 (72) | 0.856 |
| Chest pain | 334 (6.4%) | 382 (8.4%) | 274 (6.1%) | <0.001 |
| Dyspnea | 1,573 (30.2%) | 1,443 (31.7%) | 1,310 (29.3%) | 0.006 |
| Subcutaneous edema | 1,020 (19.6%) | 948 (20.8%) | 831 (18.6%) | <0.001 |
| Rales | 142 (2.7%) | 225 (4.9%) | 172 (3.8%) | <0.001 |
| Sodium (mEq/L) | 139.2 ± 3.4 (140.0) | 138.9 ± 3.4 (139.0) | 139.6 ± 3.5 (140.0) | <0.001 |
| BUN (mg/dl) | 26.2 ± 15.0 (22.0) | 25.6 ± 15.1 (22.0) | 25.6 ± 14.5 (22.0) | 0.089 |
| Creatinine (mg/dl) | 1.4 ± 0.7 (1.2) | 1.4 ± 0.9 (1.2) | 1.4 ± 0.8 (1.2) | 0.338 |
| BNP (pg/ml) | 649.2 ± 807.7 (349.0) | 738.4 ± 980.0 (392.0) | 759.6 ± 927.1 (457.0) | 0.004 |
| Potassium (mEq/L) | 4.4 ± 0.5 (4.4) | 4.4 ± 0.5 (4.4) | 4.4 ± 0.5 (4.4) | <0.001 |
| Hemoglobin (g/dl) | 13.3 ± 1.9 (13.4) | 13.2 ± 1.9 (13.3) | 13.2 ± 1.9 (13.2) | 0.102 |
| QRS duration (ms) | 131.5 ± 37.3 (127.0) | 128.7 ± 37.2 (120.0) | 130.5 ± 36.5 (124.0) | 0.012 |
| QRS duration >120 ms | 2,055 (54.0%) | 1,365 (49.6%) | 1,649 (53.5%) | 0.001 |
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