Jennifer A. Mattera

Randomized trial of an education and support intervention to prevent readmission of patients with heart failure

OBJECTIVES We determined the effect of a targeted education and support intervention on the rate of readmission or death and hospital costs in patients with heart failure (HF). BACKGROUND Disease management programs for patients with HF including medical components may reduce readmissions by 40% or more, but the value of an intervention focused on education and support is not known. METHODS We conducted a prospective, randomized trial of a formal education and support intervention on one-year readmission or mortality and costs of care for patients hospitalized with HF. RESULTS Among the 88 patients (44 intervention and 44 control) in the study, 25 patients (56.8%) in the intervention group and 36 patients (81.8%) in the control group had at least one readmission or died during one-year follow-up (relative risk = 0.69, 95% confidence interval [CI]: 0.52, 0.92; p = 0.01). The intervention was associated with a 39% decrease in the total number of readmissions (intervention group: 49 readmissions; control group: 80 readmissions, p = 0.06). After adjusting for clinical and demographic characteristics, the intervention group had a significantly lower risk of readmission compared with the control group (hazard ratio = 0.56, 95% CI: 0.32, 0.96; p = 0.03) and hospital readmission costs of

An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure

7,515 less per patient. CONCLUSIONS A formal education and support intervention substantially reduced adverse clinical outcomes and costs for patients with HF.

An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction

Background—Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services. Methods and Results—We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points). Conclusions—This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.

An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With Heart Failure

Background— A model using administrative claims data that is suitable for profiling hospital performance for acute myocardial infarction would be useful in quality assessment and improvement efforts. We sought to develop a hierarchical regression model using Medicare claims data that produces hospital risk-standardized 30-day mortality rates and to validate the hospital estimates against those derived from a medical record model. Methods and Results— For hospital estimates derived from claims data, we developed a derivation model using 140 120 cases discharged from 4664 hospitals in 1998. For the comparison of models from claims data and medical record data, we used the Cooperative Cardiovascular Project database. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1995, 1997, and 1999–2001. The final model included 27 variables and had an area under the receiver operating characteristic curve of 0.71. In a comparison of the risk-standardized hospital mortality rates from the claims model with those of the medical record model, the correlation coefficient was 0.90 (SE=0.003). The slope of the weighted regression line was 0.95 (SE=0.007), and the intercept was 0.008 (SE=0.001), both indicating strong agreement of the hospital estimates between the 2 data sources. The median difference between the claims-based hospital risk-standardized mortality rates and the chart-based rates was <0.001 (25th and 75th percentiles, −0.003 and 0.003). The performance of the model was stable over time. Conclusions— This administrative claims-based model for profiling hospitals performs consistently over several years and produces estimates of risk-standardized mortality that are good surrogates for estimates from a medical record model.

Achieving Rapid Door-To-Balloon Times. How Top Hospitals Improve Complex Clinical Systems

Background— A model using administrative claims data that is suitable for profiling hospital performance for heart failure would be useful in quality assessment and improvement efforts. Methods and Results— We developed a hierarchical regression model using Medicare claims data from 1998 that produces hospital risk-standardized 30-day mortality rates. We validated the model by comparing state-level standardized estimates with state-level standardized estimates calculated from a medical record model. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1999–2001. The final model included 24 variables and had an area under the receiver operating characteristic curve of 0.70. In the derivation set from 1998, the 25th and 75th percentiles of the risk-standardized mortality rates across hospitals were 11.6% and 12.8%, respectively. The 95th percentile was 14.2%, and the 5th percentile was 10.5%. In the validation samples, the 5th and 95th percentiles of risk-standardized mortality rates across states were 9.9% and 13.9%, respectively. Correlation between risk-standardized state mortality rates from claims data and rates derived from medical record data was 0.95 (SE=0.015). The slope of the weighted regression line from the 2 data sources was 0.76 (SE=0.04) with intercept of 0.03 (SE=0.004). The median difference between the claims-based state risk-standardized estimates and the chart-based rates was <0.001 (25th percentile=−0.003; 75th percentile=0.002). The performance of the model was stable over time. Conclusions— This administrative claims-based model produces estimates of risk-standardized state mortality that are very good surrogates for estimates derived from a medical record model.

Failure to Improve Left Ventricular Function After Coronary Revascularization for Ischemic Cardiomyopathy Is Not Associated With Worse Outcome

Background— Fewer than half of patients with ST-elevation acute myocardial infarction (STEMI) are treated within guideline-recommended door-to-balloon times; however, little information is available about the approaches used by hospitals that have been successful in improving door-to-balloon times to meet guidelines. We sought to characterize experiences of hospitals with outstanding improvement in door-to-balloon time during 1999–2002. Methods and Results— We performed a qualitative study using in-depth interviews (n=122) with clinical and administrative staff at 11 hospitals that were participating with the National Registry of Myocardial Infarction and had median door-to-balloon times of ≤90 minutes during 2001–2002, representing substantial improvement since 1999. Data were organized with the use of NUD-IST 4 (Sage Publications Software) and were analyzed by the constant comparative method of qualitative data analysis. Eight themes characterized hospitals’ experiences: commitment to an explicit goal to improve door-to-balloon time motivated by internal and external pressures; senior management support; innovative protocols; flexibility in refining standardized protocols; uncompromising individual clinical leaders; collaborative teams; data feedback to monitor progress and identify problems and successes; and an organizational culture that fostered resilience to challenges or setbacks in improvement efforts. Conclusions— Several themes characterized the experiences of hospitals that had achieved notable improvements in their door-to-balloon times. By distilling the complex and diverse experiences of organizational change into its essential components, this study provides a foundation for future efforts to elevate clinical performance in the hospital setting.

Patients With Depressive Symptoms Have Lower Health Status Benefits After Coronary Artery Bypass Surgery

Background-Preoperative identification of viable myocardium in patients with ischemic cardiomyopathy is considered important because CABG can result in recovery of left ventricular (LV) function. However, the hypothesis that lack of improvement of LV function after CABG is associated with poorer patient outcome is untested. Methods and Results-Outcome was compared in patients with ischemic LV dysfunction (LVEF </=0.30) with and without improvement in LVEF after CABG. Of 135 consecutive patients, 128 (95%) survived CABG and 104 (77%) had pre- and post-CABG LVEF assessment. Of these 104 patients, 68 (65%) had >0.05 increase in LVEF (group A) and 36 (35%) had no significant change, or </=0.05 decrease in LVEF (group B) compared with pre-CABG LVEF. No significant differences existed in age, gender, comorbidities, baseline symptoms, baseline LVEF, or intraoperative variables between groups A and B. Group A increased LVEF from 0.24+/-0.05 to 0.39+/-0.1 (P<0.005). In Group B, LVEF did not change significantly postoperatively, 0.24+/-0.05 to 0.23+/-0.06 (P=NS). Postoperative improvement in angina and heart failure scores were similar between the 2 groups. Survival free of cardiac death was similar for both groups (93% in group A and 94% in group B, P=NS) at a mean follow-up of 32+/-23 months. Conclusions-Lack of improvement of global LVEF after CABG is not associated with poorer outcome compared with that of patients with improved LVEF, presumably because effective revascularization of ischemic myocardium, even without improvement in ventricular function, protects against future infarction and death.

An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction

Background—Depression is an established independent prognostic factor for mortality, readmission, and cardiac events after CABG surgery. However, limited data exist on whether depression influences functional outcomes after CABG. Methods and Results—We followed 963 patients who underwent first CABG between February 1999 and February 2001. At baseline and at 6 months after CABG, we interviewed patients to assess depressive symptoms using the Geriatric Depression Scale (GDS) and physical function using the Short Form-36 Physical Component Scale (PCS). The patient’s physical function was considered improved if the PCS score increased ≥5 points at 6 months. Patients with high GDS scores were younger, were more often female, and had worse physical function and higher comorbidity than patients with low GDS scores. Rates of improvement in physical function were 60.1% for a GDS score <5 (below 75th percentile), 49.8% for a GDS score between 5 and 9 (75th to 90th percentile), and 39.7% for a GDS score ≥10 (≥90th percentile; P=0.002 for the trend). Depressive symptoms remained a significant independent predictor of lack of functional improvement after adjustment for severity of coronary artery disease, angina class, baseline PCS score, and medical history. A GDS score ≥10 was a stronger inverse risk factor for functional improvement after CABG than such traditional measures of disease severity as previous myocardial infarction, heart failure on admission, history of diabetes, and left ventricular ejection fraction. Conclusions—Higher levels of depressive symptoms at the time of CABG are a strong risk factor for lack of functional benefits 6 months after CABG.

Quantitative planar thallium-201 stress scintigraphy: a critical evaluation of the method

Background— National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction. Methods and Results— We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points). Conclusions— This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.

Sex Differences in Health Status After Coronary Artery Bypass Surgery

The results of quantitative analysis of planar thallium-201 stress scintigraphy are superior to those of visual analysis. The increased sensitivity for detection of coronary artery disease is associated with maintenance of specificity. Consequently, we believe that quantitative analysis is the state-of-the-art for planar 201Tl stress scintigraphy. We emphasize that for reliable and reproducible results, rigorous quality control and strict adherence to a standardized imaging protocol are necessary. An important feature is clarity of display of computer data. In our experience, the most important feature for making quantitative analysis reliable and accessible for a broader user market is simultaneous display of the lower limits of normal with processed patient data. This provides a simple visual impression of the degree and extent of abnormal 201Tl distribution and kinetics relative to the lower limit of normal.