Measuring Performance For Treating Heart Attacks And Heart Failure: The Case For Outcomes Measurement

Development, validation, and results of a risk-standardized measure of hospital 30-day mortality for patients with exacerbation of chronic obstructive pulmonary disease

BACKGROUND

Despite its large clinical and economic significance, measuring and improving the outcomes of patients hospitalized for chronic obstructive pulmonary disease (COPD) is only beginning to emerge as a national priority for policy makers and payers.

OBJECTIVE

To facilitate the public reporting of hospital outcomes, we developed a risk-standardized measure of hospital 30-day mortality for patients admitted with exacerbation of COPD.

DESIGN

Hierarchical logistic regression model.

SETTING/PATIENTS

Medicare Part A and Part B claims in a random sample of half of all admissions for patients admitted to acute care hospitals in 2008 (development cohort) and remaining 2008 admissions (validation cohort). We also assessed model performance and predictive ability in 2007 and 2009 data.

MEASUREMENTS

Hospital risk-standardized 30-day mortality rates.

RESULTS

The model development sample consisted of 150,035 admissions at 4537 nonfederal acute care US hospitals, with a mean unadjusted hospital 30-day mortality rate of 8.6%. The mean risk-standardized mortality rate was 8.6% and ranged from 5.9% to 13.5%. The development and validation models had good discrimination (areas under the receiver operating characteristic curve 0.72 and 0.72, respectively) and predictive ability (predicted mortality at the 1st and 10th deciles 1.5%, 23.7%, and 1.6%, 23.8%, respectively) and showed no evidence of over-fitting.

CONCLUSIONS

A 30-day mortality model based on administrative claims had similar discrimination to other public reporting models and can be used to compare risk-adjusted outcomes for patients with exacerbations of COPD and to track changes in outcomes over time. The high mortality and variation in rates across institutions suggest opportunities to improve quality of care.

Establishing the feasibility of measuring performance in use of addiction pharmacotherapy

This paper presents the rationale and feasibility of standardized performance measures for use of pharmacotherapy in the treatment of substance use disorders (SUD), an evidence-based practice and critical component of treatment that is often underused. These measures have been developed and specified by the Washington Circle, to measure treatment of alcohol and opioid dependence with FDA-approved prescription medications for use in office-based general health and addiction specialty care. Measures were pilot tested in private health plans, the Veterans Health Administration (VHA), and Medicaid. Testing revealed that use of standardized measures using administrative data for overall use and initiation of SUD pharmacotherapy is feasible and practical. Prevalence of diagnoses and use of pharmacotherapy vary widely across health systems. Pharmacotherapy is generally used in a limited portion of those for whom it might be indicated. An important methodological point is that results are sensitive to specifications, so that standardization is critical to measuring performance across systems.

Does admission to a teaching hospital affect acute myocardial infarction survival?

PURPOSE

Previous studies have found that teaching hospitals produce better acute myocardial infarction (AMI) outcomes than nonteaching hospitals. However, these analyses generally excluded patients transferred out of nonteaching hospitals and did not study outcomes by patient risk level. The objective of this study was to determine whether admission to a teaching hospital was associated with greater survival after accounting for patient transfers and patient severity.

METHOD

This observational study used logistic models to examine the association between hospital teaching status and 30-day mortality of AMI patients, adjusting for patient comorbidities and common time trends. The sample included 1,309,554 Medicare patients admitted from 1996 to 2004 to 3,761 acute care hospitals for AMI. The primary outcome was 30-day all-cause, all-location mortality.

RESULTS

Mortality was slightly lower in minor teaching hospitals compared with nonteaching hospitals (odds ratio [OR] 0.97; 95% confidence interval [CI] 0.95-0.99) but not different between major teaching and nonteaching hospitals (OR 1.01; 95% CI 0.96-1.03). The odds of mortality in minor teaching hospitals decreased 4.2% relative to nonteaching hospitals during the seven-year period (OR from 0.98 to 0.94). There was no consistent pattern of association between teaching status and patient severity.

CONCLUSIONS

After correctly accounting for the ability of nonteaching hospitals to appropriately transfer patients in need of different care, there was no survival benefit on average for initial admission to a teaching hospital for AMI. Further more, higher-risk patients did not benefit from initial admission to teaching hospitals.

Comparing regression-adjusted mortality to standardized mortality ratios for trauma center profiling

Background:

Trauma center profiling is commonly performed with Standardized Mortality Ratios (SMRs). However, comparison of SMRs across trauma centers with different case mix can induce confounding leading to biased trauma center ranks. We hypothesized that Regression-Adjusted Mortality (RAM) estimates would provide a more valid measure of trauma center performance than SMRs.

Objective:

Compare trauma center ranks generated by RAM estimates to those generated by SMRs.

Materials and Methods:

The study was based on data from a provincial Trauma Registry (1999-2006; n = 88,235). SMRs were derived as the ratio of observed to expected deaths using: (1) the study population as an internal standard, (2) the US National Trauma Data Bank as an external standard. The expected death count was calculated as the sum of mortality probabilities for all patients treated in a hospital conditional on the injury severity score, the revised trauma score, and age. RAM estimates were obtained directly from a hierarchical logistic regression model.

Results:

Crude mortality was 5.4% and varied between 1.3% and 13.5% across the 59 trauma centers. When trauma center ranks from internal SMRs and RAM were compared, 49 out of 59 centers changed rank and six centers changed by more than five ranks. When trauma center ranks from external SMRs and RAM were compared, 55 centers changed rank and 17 changed by more than five ranks.

Conclusions:

The results of this study suggest that the use of SMRs to rank trauma centers in terms of mortality may be misleading. RAM estimates represent a potentially more valid method of trauma center profiling.

30-day in-hospital mortality after acute myocardial infarction in Tuscany (Italy): an observational study using hospital discharge data

Background

Coronary heart disease is the leading cause of mortality in the world. One of the outcome indicators recently used to measure hospital performance is 30-day mortality after acute myocardial infarction (AMI). This indicator has proven to be a valid and reproducible indicator of the appropriateness and effectiveness of the diagnostic and therapeutic process for AMI patients after hospital admission. The aim of this study was to examine the determinants of inter-hospital variability on 30-day in-hospital mortality after AMI in Tuscany. This indicator is a proxy of 30-day mortality that includes only deaths occurred during the index or subsequent hospitalizations.

Methods

The study population was identified from hospital discharge records (HDRs) and included all patients with primary or secondary ICD-9-CM codes of AMI (ICD-9 codes 410.xx) that were discharged between January 1, 2009 and November 30, 2009 from any hospital in Tuscany. The outcome of interest was 30-day all-cause in-hospital mortality, defined as a death occurring for any reason in the hospital within 30 days of the admission date. Because of the hierarchical structure of the data, with patients clustered into hospitals, random-effects (multilevel) logistic regression models were used. The models included patient risk factors and random intercepts for each hospital.

Results

The study included 5,832 patients, 61.90% male, with a mean age of 72.38 years. During the study period, 7.99% of patients died within 30 days of admission. The 30-day in-hospital mortality rate was significantly higher among patients with ST segment elevation myocardial infarction (STEMI) compared with those with non-ST segment elevation myocardial infarction (NSTEMI). The multilevel analysis which included only the hospital variance showed a significant inter-hospital variation in 30-day in-hospital mortality. When patient characteristics were added to the model, the hospital variance decreased. The multilevel analysis was then carried out separately in the two strata of patients with STEMI and NSTEMI. In the STEMI group, after adjusting for patient characteristics, some residual inter-hospital variation was found, and was related to the presence of a cardiac catheterisation laboratory.

Conclusion

We have shown that it is possible to use routinely collected administrative data to predict mortality risk and to highlight inter-hospital differences. The distinction between STEMI and NSTEMI proved to be useful to detect organisational characteristics, which affected only the STEMI subgroup.

More quality measures versus measuring what matters: a call for balance and parsimony

External groups requiring measures now include public and private payers, regulators, accreditors and others that certify performance levels for consumers, patients and payers. Although benefits have accrued from the growth in quality measurement, the recent explosion in the number of measures threatens to shift resources from improving quality to cover a plethora of quality-performance metrics that may have a limited impact on the things that patients and payers want and need (ie, better outcomes, better care, and lower per capita costs). Here we propose a policy that quality measurement should be: balanced to meet the need of end users to judge quality and cost performance and the need of providers to continuously improve the quality, outcomes and costs of their services; and parsimonious to measure quality, outcomes and costs with appropriate metrics that are selected based on end-user needs.

Rates and predictors of 30-day readmission among commercially insured and Medicaid-enrolled patients hospitalized with systolic heart failure

BACKGROUND

Heart failure (HF) readmission rates are primarily derived from Medicare enrollees. Given increasing public scrutiny of HF readmissions, understanding the rate and predictors in populations covered by other payers is also important, particularly among patients with systolic dysfunction, for whom most HF-specific therapies are targeted.

METHODS AND RESULTS

MarketScan Commercial and Medicaid Administrative Claims Databases were used to identify all first hospitalizations with an International Classification of Diseases-9 discharge diagnosis code for HF (primary position) and systolic HF (any position) between January 1, 2005, and June 30, 2008. Among 4584 unique systolic HF index admissions (mean age 55 years), 30-day crude readmission rates were higher for Medicaid than commercially insured patients: all-cause 17.4% versus 11.8%; HF-related 6.7% versus 4.0%, respectively. In unadjusted analysis, higher comorbidity and prior healthcare utilization predicted readmission; age, sex, and plan type did not. After adjustment for case mix, the odds of all-cause and HF-related readmission were 32% and 68% higher, respectively, among Medicaid than commercially insured patients (P<0.02 for both). No significant differences in readmission rates were seen for managed care versus fee-for-service or capitated versus noncapitated plan types.

CONCLUSIONS

Compared with commonly cited Medicare HF readmission rates of 20% to 25%, Medicaid patients with systolic HF had lower 30-day readmission rates, and commercially insured patients had even lower rates. Even after adjustment for case mix, Medicaid patients were more likely to be readmitted than commercially insured patients, suggesting that more attention should be focused on readmissions among socioeconomically disadvantaged populations.

The incomplete infrastructure for interhospital patient transfer

OBJECTIVE

Interhospital transfer of critically ill patients is a common part of their care. This article sought to review the data on the current patterns of use of interhospital transfer and identify systematic barriers to optimal integration of transfer as a mechanism for improving patient outcomes and value of care.

DATA SOURCE

Narrative review of medical and organizational literature.

SUMMARY

Interhospital transfer of patients is common, but not optimized to improve patient outcomes. Although there is a wide variability in quality among hospitals of nominally the same capability, patients are not consistently transferred to the highest quality nearby hospital. Instead, transfer destinations are selected by organizational routines or non-patient-centered organizational priorities. Accomplishing a transfer is often quite difficult for sending hospitals. But once a transfer destination is successfully found, the mechanics of interhospital transfer now appear quite safe.

CONCLUSION

Important technological advances now make it possible to identify nearby hospitals best able to help critically ill patients, and to successfully transfer patients to those hospitals. However, organizational structures have not yet developed to insure that patients are optimally routed, resulting in potentially significant excess mortality.

Revenue, relationships and routines: the social organization of acute myocardial infarction patient transfers in the United States

Heart attack, or acute myocardial infarction (AMI), is a leading cause of death in the United States (U.S.). The most effective therapy for AMI is rapid revascularization: the mechanical opening of the clogged artery in the heart. Forty-four percent of patients with AMI who are admitted to a non-revascularization hospital in the U.S. are transferred to a hospital with that capacity. Yet, we know little about the process by which community hospitals complete these transfers, and why publicly available hospital quality data plays a small role in community hospitals' choice of transfer destinations. Therefore, we investigated how community hospital staff implement patient transfers and select destinations. We conducted a mixed methods study involving: interviews with staff at three community hospitals (n = 25) in a Midwestern state and analysis of U.S. national Medicare records for 1996-2006. Community hospitals in the U.S., including our field sites, typically had longstanding relationships with one key receiving hospital. Community hospitals addressed the need for rapid AMI patient transfers by routinizing the collective, interhospital work process. Routinization reduced staff uncertainty, coordinated their efforts and conserved their cognitive resources for patient care. While destination selection was nominally a physician role, the decision was routinized, such that staff immediately contacted a "usual" transfer destination upon AMI diagnosis. Transfer destination selection was primarily driven at an institutional level by organizational concerns and bed supply, rather than physician choice or patient preference. Transfer routinization emerged as a form of social order that invoked tradeoffs between process speed and efficiency and patient-centered, quality-driven decision making. We consider the implications of routinization and institutional imperatives for health policy, quality improvement and health informatics interventions.

Association between conformity with performance measures and 1-year postdischarge survival in patients with acute decompensated heart failure

Recognition of the treatment gap in patients with heart failure (HF) led to the development of a set of process-of-care measures to improve the quality of care. To assess the association of established and emerging process-of-care measures with 1-year postdischarge survival, 496 patients with acute decompensated HF were studied. After adjustment for established prognostic factors, the relative risk (RR) for mortality in patients eligible for treatment was as follows: 0.49 (P < .001) for discharge prescription of renin-angiotensin system inhibitors (RAS-Is), 0.59 (P = .015) for β-blockers, 0.44 (P < .001) for combination therapy (ie, a β-blocker and a RAS-I), 0.87 (P nonsignificant) for aldosterone antagonists, and 0.49 (P nonsignificant) for planned cardioverter-defibrillator implantation. After adjustment for propensity scores, the RR was 0.49 (P < .001) for RAS-Is, 0.67 (P = .04) for β-blockers, and 0.57 (P < .001) for combination therapy. The data suggest that performance measures for RAS-Is, β-blockers, and combination therapy are strongly associated with improved 1-year survival.