Comparison of Composite Measure Methodologies for Rewarding Quality of Care An Analysis From the American Heart Association's Get With The Guidelines Program
Composite indices of health care performance are an aggregation of underlying individual performance measures and are increasingly being used to rank hospitals. We sought to conduct an observational analysis to determine the influence of the opportunity-based and all-or-none composite performance measures on hospital rankings.
We examined 194 245 patients hospitalized with acute myocardial infarction between July 2006 and June 2009 from 334 hospitals participating in the Get With The Guidelines--Coronary Artery Disease (GWTG-CAD) quality improvement program. We analyzed hospital opportunity-based and all-or-none composite scores and 30-day risk-standardized all-cause mortality and readmission rates. We found that the median calculated opportunity-based score for these hospitals was 95.5 (interquartile range, 90.4, 98.0). The median all-or-none score was 88.9 (interquartile range, 79.7, 94.4). The 2 scoring methods were significantly correlated with one another (r=0.98, P<0.001). Rankings generated by the two methods were significantly correlated (r=0.93, P<0.001). The two methods had a modest correlation with the 30-day risk-standardized mortality rate (opportunity-based score: r=-0.25, P<0.001; all-or-none score: r=-0.24, P<0.001). Neither composite measure correlated with the 30-day risk-standardized readmission rate. Over time, the number of hospitals new to the top and bottom quintiles of hospital rankings diminished similarly for both composite measures. When including additional performance measures into the composite score, the two methods produced similar changes in hospital rankings.
The opportunity-based and all-or-none coronary artery disease composite indices are highly correlated and yield similar ranking of the top and bottom quintiles of hospitals. The two methods provide similarly modest correlations with 30-day mortality, but not readmission.
Available from: Eliana Santucci
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ABSTRACT: Studies have found that patients with acute coronary syndromes (ACS) often do not receive evidence-based therapies in community practice. This is particularly true in low- and middle-income countries.
To evaluate whether a multifaceted quality improvement (QI) intervention can improve the use of evidence-based therapies and reduce the incidence of major cardiovascular events among patients with ACS in a middle-income country.
The BRIDGE-ACS (Brazilian Intervention to Increase Evidence Usage in Acute Coronary Syndromes) trial, a cluster-randomized (concealed allocation) trial conducted among 34 clusters (public hospitals) in Brazil and enrolling a total of 1150 patients with ACS from March 15, 2011, through November 2, 2011, with follow-up through January 27, 2012.
Multifaceted QI intervention including educational materials for clinicians, reminders, algorithms, and case manager training, vs routine practice (control).
Primary end point was the percentage of eligible patients who received all evidence-based therapies (aspirin, clopidogrel, anticoagulants, and statins) during the first 24 hours in patients without contraindications.
Mean age of the patients enrolled was 62 (SD, 13) years; 68.6% were men, and 40% presented with ST-segment elevation myocardial infarction, 35.6% with non-ST-segment elevation myocardial infarction, and 23.6% with unstable angina. The randomized clusters included 79.5% teaching hospitals, all from major urban areas and 41.2% with 24-hour percutaneous coronary intervention capabilities. Among eligible patients (923/1150 [80.3%]), 67.9% in the intervention vs 49.5% in the control group received all eligible acute therapies (population average odds ratio [OR(PA)], 2.64 [95% CI, 1.28-5.45]). Similarly, among eligible patients (801/1150 [69.7%]), those in the intervention group were more likely to receive all eligible acute and discharge medications (50.9% vs 31.9%; OR(PA),, 2.49 [95% CI, 1.08-5.74]). Overall composite adherence scores were higher in the intervention clusters (89% vs 81.4%; mean difference, 8.6% [95% CI, 2.2%-15.0%]). In-hospital cardiovascular event rates were 5.5% in the intervention group vs 7.0% in the control group (OR(PA), 0.72 [95% CI, 0.36-1.43]); 30-day all-cause mortality was 7.0% vs 8.4% (ORPA, 0.79 [95% CI, 0.46-1.34]).
Among patients with ACS treated in Brazil, a multifaceted educational intervention resulted in significant improvement in the use of evidence-based therapies.
clinicaltrials.gov Identifier: NCT00958958.
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There have been substantial improvements in the use of evidence-based, guideline-recommended therapies for patients with acute myocardial infarction. Nevertheless, some gaps, disparities, and variations in use remain. To understand how such gaps in recommended care may be narrowed further, it may be useful to determine those factors associated with lessened adherence to guideline-based care.
The Get with the Guidelines-Coronary Artery Disease registry measured adherence with 6 performance measures (aspirin within 24 hours, discharge on aspirin and beta-blockers, patients with low ejection fraction discharged on angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, smoking cessation counseling, use of lipid-lowering medications) in 148,654 patients with acute myocardial infarction between 2002 and 2009. Logistic multivariable regression models using generalized estimating equations were utilized to identify patient and hospital characteristics associated with adherence to each of 6 measures, and to a summary score of performance for all measures, in eligible patients.
We identified 10 variables that were associated significantly with either greater adherence (hypertension, hyperlipidemia, hospital with full interventional capabilities, calendar year) or worse adherence (age, female sex, congestive heart failure, chronic renal insufficiency, atrial fibrillation, chronic dialysis) in at least 4 of the 6 treatment adherence models, as well as the summary score adherence model. Age, sex, and calendar year were significant in all models.
Use of evidence-based acute myocardial infarction treatments remains less than ideal for certain high-risk populations. The close correlations among factors associated with underperformance highlights the potential for specifically targeting and tailoring quality improvement interventions.
Available from: Keith A A Fox
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ABSTRACT: To investigate whether a hospital-specific opportunity-based composite score (OBCS) was associated with mortality in 136,392 patients with acute myocardial infarction (AMI) using data from the Myocardial Ischaemia National Audit Project (MINAP) 2008-2009.
For 199 hospitals a multidimensional hospital OBCS was calculated on the number of times that aspirin, thienopyridine, angiotensin-converting enzyme inhibitor (ACEi), statin, β-blocker, and referral for cardiac rehabilitation was given to individual patients, divided by the overall number of opportunities that hospitals had to give that care. OBCS and its six components were compared using funnel plots. Associations between OBCS performance and 30-day and 6-month all-cause mortality were quantified using mixed-effects regression analysis. Median hospital OBCS was 95.3% (range 75.8-100%). By OBCS, 24.1% of hospitals were below funnel plot 99.8% CI, compared to aspirin (11.1%), thienopyridine (15.1%), β-blockers (14.7%), ACEi (19.1%), statins (12.1%), and cardiac rehabilitation (17.6%) on discharge. Mortality (95% CI) decreased with increasing hospital OBCS quartile at 30 days [Q1, 2.25% (2.07-2.43%) vs. Q4, 1.40% (1.25-1.56%)] and 6 months [Q1, 7.93% (7.61-8.25%) vs. Q4, 5.53% (5.22-5.83%)]. Hospital OBCS quartile was inversely associated with adjusted 30-day and 6-month mortality [OR (95% CI), 0.87 (0.80-0.94) and 0.92 (0.88-0.96), respectively] and persisted after adjustment for coronary artery catheterization [0.89 (0.82-0.96) and 0.95 (0.91-0.98), respectively].
Multidimensional hospital OBCS in AMI survivors are high, discriminate hospital performance more readily than single performance indicators, and significantly inversely predict early and longer-term mortality.
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