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Results From the Cooperative Cardiovascular Project

Thomas A. Marciniak, MD; Edward F. Ellerbeck, MD; Martha J. Radford, MD; Timothy F. Kresowik, MD; Jay A. Gold, MD; Harlan M. Krumholz, MD; Catarina I. Kiefe, MD, PhD; Richard M. Allman, MD; Robert A. Vogel, MD; Stephen F. Jencks, MD

JAMA. 1998;279:1351-1357.

ABSTRACT
Context.— Medicare has a legislative mandate for quality assurance, but the effectiveness of its population-based quality improvement programs has been difficult to establish.

Objective.— To improve the quality of care for Medicare patients with acute myocardial infarction.

Design.— Quality improvement project with baseline measurement, feedback, remeasurement, and comparison samples.

Setting.— All acute care hospitals in the United States.

Patients.— Preintervention and postintervention samples included all Medicare patients in Alabama, Connecticut, Iowa, and Wisconsin discharged with principal diagnoses of acute myocardial infarctions during 2 periods, June 1992 through December 1992 and August 1995 through November 1995. Indicator comparisons were made with a random sample of Medicare patients in the rest of the nation discharged with acute myocardial infarctions from August 1995 through November 1995. Mortality comparisons involved all Medicare patients nationwide with inpatient claims for acute myocardial infarctions during 2 periods, June 1992 through May 1993 and August 1995 through July 1996.

Intervention.— Data feedback by peer review organizations.

Main Outcome Measures.— Quality indicators derived from clinical practice guidelines, length of stay, and mortality.

Results.— Performance on all quality indicators improved significantly in the 4 pilot states. Administration of aspirin during hospitalization in patients without contraindications improved from 84% to 90% (P<.001), and prescription of -blockers at discharge improved from 47% to 68% (P<.001). Mortality at 30 days decreased from 18.9% to 17.1% (P=.005) and at 1 year from 32.3% to 29.6% (P<.001). These improvements in quality occurred during a period when median length of stay decreased from 8 days to 6 days. Performance on all quality indicators except reperfusion was better in the pilot states than in the rest of the nation in 1995, and the differences were statistically significant for aspirin use at discharge (P<.001), -blocker use (P<.001), and smoking cessation counseling (P=.02). Postinfarction mortality was not significantly different between the pilot states and the rest of the nation during the baseline period, although it was slightly but significantly better in the pilot states during the follow-up period (absolute mortality difference at 1 year, 0.9%; P=.004).

Conclusions.— The quality of care for Medicare patients with acute myocardial infarction has improved in the Cooperative Cardiovascular Project pilot states. Performance on the defined quality indicators appeared to be better in the pilot states than in the rest of the nation in 1995 and was associated with reduced mortality.

INTRODUCTION

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HEALTH CARE quality is a topic of current concern. Quality has been the focus of recent articles in the medical literature^1-2 and is being addressed by a presidential commission. These current concerns about quality are partially motivated by speculations about the effect of managed health care on quality and access, and may be related to a realization that quality cannot be assumed but rather must be understood and engineered.

Since 1992 the Health Care Financing Administration (HCFA) has been implementing a continuous quality improvement approach to ensuring the quality of care for its Medicare beneficiaries. HCFA's Health Care Quality Improvement Initiative is implemented by its contractors, the peer review organizations (PROs).³ The first project of this program is the Cooperative Cardiovascular Project (CCP), which focuses on treatment of patients with acute myocardial infarction (AMI).

The CCP began with the development of quality indicators for the treatment of AMI. A steering committee convened by HCFA and the American Medical Association (AMA) drafted quality indicators heavily based on clinical practice guidelines developed by the American College of Cardiology (ACC) and the American Heart Association (AHA).⁴ The PROs in 4 states, Alabama, Connecticut, Iowa, and Wisconsin, refined the quality indicators and developed data collection instruments and computer algorithms for them. These PROs abstracted data from medical records of Medicare patients in their states who were discharged with a principal diagnosis of AMI from June 1992 through February 1993 and evaluated the rates for each quality indicator. The results of this baseline data collection have been reported previously.⁵

The 4 PROs provided the results to the practitioners in their states during 1994 and encouraged the initiation of quality improvement activities for the treatment of AMI. To evaluate the effects of these activities, we collected a follow-up sample of AMI cases in the pilot states and a comparison sample of AMI cases from the rest of the nation in 1995.

METHODS

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Sample Selection

For all samples we identified cases using hospital bills (UB-92 claims form data) in the Medicare National Claims History File. The National Claims History File includes all claims submitted for Medicare patients treated under fee-for-service arrangements but does not include UB-92 submissions for all patients treated under Medicare managed care risk contracts. We sampled only claims with an ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) principal diagnosis code of 410 (AMI), excluding codes with a fifth digit of 2, which designates a subsequent episode of care. For the baseline sample we identified all AMI claims submitted by hospitals in the 4 pilot states that had discharge dates between June 1, 1992, and December 31, 1992. We used cases from January 1993 and February 1993 for the quality improvement feedback, but we excluded these months from our analyses because the sampling for them was incomplete because of timing. We used cases with discharge dates between August 1, 1995, and November 30, 1995, for the follow-up sample. We selected this latter sampling time frame to allow 6 months of elapsed time from the completion of the feedback sessions and to accumulate a sample size sufficient for a second round of feedback sessions.

For the nonpilot indicator comparison sample we randomly selected cases from all states other than the pilot states from the follow-up period of August 1, 1995, through November 30, 1995. We randomly sampled 2400 cases to provide 90% power for detecting a 5% absolute difference in a typical quality indicator. This sample size provides low power (40%) for detecting even substantial (10%) improvement in mortality.

For mortality comparisons we sampled all AMI claims from June 1, 1992, through May 31, 1993, and from August 1, 1995, through July 31, 1996. We selected only the first AMI episode for patients with more than 1 AMI during these periods. We matched the patients to the Medicare Enrollment Database to determine survival.

Data Collection and Quality Control

Copies of medical records corresponding to discharge dates were requested from hospitals. For the baseline sample the copies were sent to and abstracted at the 4 state PROs. For the follow-up and nonpilot samples the record copies were abstracted at 2 clinical data abstraction centers. The 2 abstraction centers were established by HCFA through contracts with private organizations experienced in medical abstractions to maintain abstraction consistency and efficiency for its national quality improvement projects, including CCP.

Trained abstracters extracted predefined variables from the medical record copies. Data were entered directly into computers using interactive software with online data definitions, help, and edits. The clinical data abstracted included all variables needed to calculate the quality indicator rates as well as measures of risk, comorbidity, and complications. The CCP abstraction software, which includes the operational definitions of all variables, is available through the CCP Internet home page at http://www.hcfa.gov/.

Data quality was monitored and maintained by random reabstractions, calculation of reliability statistics such as interrater agreement rates and values,⁶ determinations of reasons for discrepancies, and improvement actions such as focused abstracter training. For the baseline sample, 912 cases were randomly selected and reabstracted by a second abstracter. For the CCP pilot follow-up sample and for other CCP samples abstracted at the clinical data abstraction centers, cases were randomly reabstracted on a continuous basis to generate reasonable confidence intervals (CIs) for reliability statistics on a quarterly basis (eg, 95% CI, 85-94 for an observed agreement rate of 90%). For all CCP samples, more than 3000 cases were reabstracted for quality control purposes at the clinical data abstraction centers.

Interrater reliability of the abstractions was good. The reliability of the baseline data has been reported previously,⁵ with agreement rates exceeding 94% and values ranging from 0.72 to 0.88 for determining treatments. For the clinical data abstraction center abstractions, overall variable agreement averaged about 95% for the time periods during which the follow-up and nonpilot samples were abstracted. Individual variable abstraction reliability varied depending on the nature of the variable. Simple laboratory or drug variables that were well documented in medical records were highly reliable, whereas softer clinical history variables that had inconsistent documentation patterns in medical records were less reliable (eg, agreement rates of about 80% for the time of symptom onset prior to hospital arrival).

We supplemented the clinical abstractions with other data, such as diagnoses and procedures, extracted from Medicare billing records. We also extracted dates of death from the Medicare Enrollment Database. Dates of death in the Medicare Enrollment Database are derived from both the discharge dates of billing records indicating a discharge disposition of death and from the Master Beneficiary Record obtained from the Social Security Administration. The Medicare Enrollment Database has accurate records of the vital status of Medicare beneficiaries,⁷ but entries from Social Security records include unverified dates of death recorded as the last day of the month when the exact date is unavailable from a death certificate. We eliminated cases with unverified dates of death from the mortality analyses if the case could not be classified with certainty at the evaluation time. For instance, for 30-day mortality statistics, we eliminated cases with unverified dates of death if survival was between 30 and 59 days after admission as described in an earlier report.⁸ We found unverified dates of death for 168 patients with confirmed AMI (ie, about 1% of such patients or 2.2% of deaths).

Quality Indicators

The CCP focuses primarily on quality indicators, measurable aspects of care that are presumed on the basis of evidence or consensus to be related to the quality of the care delivered and to favorable outcomes. The CCP indicators were developed by a panel of experts convened by HCFA and the AMA, as reported previously.⁵ Validation studies of the indicators also were reported previously.⁹ The definitions of the quality indicators are listed in Table 1.

View this table: [in this window] [in a new window] Table 1.—Quality Indicators*

Most quality indicators are defined as rates, eg, the ratio of the number of eligible patients who received a treatment to the total number of patients eligible for that treatment. We calculated indicator rates for 2 different levels of eligibility. For an eligible candidate indicator, we included all patients who met minimum eligibility requirements (eg, for aspirin use at discharge, we included all patients with confirmed AMI who were discharged alive). For an ideal candidate indicator, we considered the same set of eligible candidates but we excluded all patients with possible contraindications (eg, for aspirin use at discharge, we excluded patients with contraindications such as recent bleeding or warfarin use). Minimum eligibility requirements are shown in Table 1 under the heading Eligible and contraindications are listed under the heading Exclusions. Ideal indicators are frequently used in PRO feedback sessions because clinicians understand them to represent cases that should have been treated. Because the ideal indicators exclude many cases and may be more susceptible to measurement error and because case mix adjustment is less critical for population estimates, we analyzed both levels of indicator eligibility and compared the results for consistency. The only exception is for the smoking cessation counseling indicator. We used 1 major eligibility condition (current smoker status) and did not analyze this indicator by different levels of eligibility.

The definitions in Table 1 were converted to computer algorithms programmed in the Stata programming language.¹⁰ The indicator eligibility requirements involve evaluating many different variables. Some of these variables, such as the occurrence of significant bleeding, are soft clinical variables subject to variability in interpretation. Because the abstractions were done by 2 different sets of organizations at 2 different times, we evaluated the frequency distributions of the exclusion variables and avoided using those that appeared to have different interpretations between the baseline and follow-up abstractions or among the 4 pilot state baseline samples. We analyzed all data sets summarized in this article with the same Stata programs. Because the indicator algorithms are complex, we have made them available through the CCP Internet home page.

Feedback

The PROs in the 4 pilot states provided the results from the baseline sample to practitioners in their states from 1994 through January 1995. The PROs used consistent definitions of the indicators and similar approaches to data presentation based on continuous quality improvement theory. Results were presented in a positive manner emphasizing approaches for improvement. The PROs collaborated with appropriate professional organizations such as local chapters of the ACC, and requested quality improvement plans from hospitals if the indicator results suggested opportunities for improvement. The details of the feedback materials and sessions were left to the discretion of the individual PROs. Samples of speaker notes for typical hospital presentations are contained in the CCP data analysis package available through the CCP Internet home page.

The major setting for feedback sessions was the acute care hospital treating AMI patients. Of 390 hospitals represented in the baseline sample, 379 received CCP feedback. Fifty-four percent of the hospitals received feedback by on-site presentations by the PROs' physicians, 18% received feedback at regional seminars, 13% received feedback from telephone conferences, and 16% received feedback from report mailings. Seventy-three percent of the hospitals submitted formal responses to the PROs. Responses included creating or revising standing orders and critical pathways, additional educational efforts and data dissemination, and follow-up data monitoring. Aspirin use, smoking cessation counseling, and thrombolytic administration were the indicators most frequently addressed.

Statistical Analysis

Because our sampling used billing record diagnoses of AMI that may not be accurate, we restricted most analyses to cases with confirmation of AMI based on clinical data. We considered cases to be clinically confirmed if the creatine kinase–MB fraction was greater than 0.05, if the lactate dehydrogenase (LDH) level exceeded 1.5 times the upper limit of normal with LDH₁ greater than LDH₂, or if 2 of the following 3 conditions were documented: chest pain, a 2-fold elevation of creatine kinase level, or a report of a new AMI on an electrocardiogram.

Different units of analysis were used for different end points. For indicators we used hospitalizations, for mortality we used patients, and for invasive procedures we used episodes. For episodes we followed the ICD-9-CM convention and defined an episode as all admissions occurring within 8 weeks of the initial admission. One patient, if multiple hospitalizations or episodes were sampled, could contribute more than 1 value to an indicator or invasive procedure rate calculation. Each patient was counted only once for mortality calculations, with survival calculated from the admission date of the first hospitalization in a sample period.

We designed our sampling and data collection approach for quality improvement purposes, so our samples include cases that should be excluded from analyses for other purposes. For indicator rates we excluded cases based on transfer status at either admission or discharge if the reliability of data collection could be adversely affected. For example, for aspirin use at discharge, we excluded transfer patients because hospital records frequently do not include information about planned postdischarge medication use for patients transferred to another facility. All such exclusions are noted in the indicator definitions in Table 1. For mortality statistics we excluded cases transferred from another hospital because we did not have an estimate of the date of occurrence for the AMI, and we also excluded cases with unverified dates of death.

Analyses of the abstracted data were performed using the Stata statistical package,¹⁰ and analyses of claims data for mortality comparisons were performed using SAS.¹¹ For comparisons among all 3 samples, we used the ² test for significance of changes in categorical variables such as indicator results, and the Kruskal-Wallis test for significance of differences in the distributions of continuous variables. For 2 sample comparisons we used the ² test for categorical variables and the Wilcoxon rank sum test for continuous variables. Confidence intervals were calculated for the rate differences based on normal approximations. We also plotted Kaplan-Meier survival curves and calculated log-rank and Wilcoxon tests of significance of differences in the survival curves. All CIs are 95% and all P values are 2-tailed and unadjusted for multiple comparisons.

RESULTS

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Sample Statistics

Overall, 23535 (96%) of 24509 records for patient discharges sampled were obtained and abstracted successfully. The abstraction completion rate was slightly higher for the follow-up period. Table 2 shows summary statistics for the samples, the sizes of the analytic subsets (units of analysis) we used, and the sizes of some intermediate subsets used to derive them.

View this table: [in this window] [in a new window] Table 2.—Sample Statistics*

Patient Characteristics

Patient characteristics are shown in Table 3. Demographics of the patients in the 2 pilot samples are similar, whereas the nonpilot sample has a slightly higher proportion of blacks. For Medicare AMI discharges, women are represented almost as frequently as men. The percentage of women is slightly higher if only those aged 65 and older are included (eg, 49.8% female in the follow-up sample). The small increase in the female representation from baseline to follow-up shown in Table 3 is not statistically significant. However, we intentionally restricted data in Table 3 to patients who were not transferred from another hospital so these data report characteristics for the same subset of patients for whom we tabulated mortality. For all patients with confirmed AMI, the increase in the percentage of women in the follow-up sample is nominally statistically significant (P=.04).

View this table: [in this window] [in a new window] Table 3.—Patient Characteristics*

We sampled all Medicare AMI discharges, including those occurring in patients younger than 65 years who were eligible for Medicare because of disability or end-stage renal disease. The percentage of Medicare AMI patients younger than 65 years is approximately 6% to 7% in these samples. We included these cases in most analyses, but excluding them does not significantly change any of the differences noted herein.

Quality Indicators

Table 4 shows comparisons of the quality indicator rates in the 3 samples. The results for the pilot baseline to follow-up comparison are consistent. All indicators show significant improvements from baseline to follow-up in both the eligible and the ideal candidate versions, except for reperfusion in ideal candidates. All improvements other than reperfusion in ideal candidates are statistically significant and magnitudes of improvements in the 2 versions of the same indicator are similar.

View this table: [in this window] [in a new window] Table 4.—Comparison of Indicator Rates*

The reperfusion in ideal candidates indicator may be susceptible to variations in abstraction, because its denominator incorporates a number of soft variables such as the time from symptom onset. In addition to improvement in the reperfusion indicator in eligible candidates, the speed with which thrombolysis was accomplished improved significantly from baseline to follow-up. The median time from arrival to administration of thrombolytics decreased from 56 minutes to 41 minutes in ideal candidates (P<.001). The percentage of ideal candidates who received thrombolytics and who were administered the drugs within 1 hour after arrival improved from 57.1% to 70.8% (P<.001), and the percentage who received thrombolytics within 30 minutes (the National Heart Attack Alert Program goal) increased from 17.6% to 30.1% (P<.001).

Performance on the quality indicators was better in the pilot states in 1995 than in the rest of the nation, with all but 2 of the 13 indicator comparisons suggesting higher rates in the pilot states. The differences for 2 of the indicators, aspirin use at discharge and -blocker use at discharge, are statistically significant (P<.001), and the difference for a third indicator, smoking cessation counseling, is also statistically significant (P=.02). Time to thrombolysis did not differ significantly between the 2 samples, eg, median time to thrombolysis in ideal candidates was 41 minutes for the pilot states and 43.5 minutes for the nonpilot states (P=.99).

Mortality

Table 5 compares mortality in the 3 abstraction samples. Both short-term (30-day) and longer-term (1-year) mortality improved significantly between the baseline and follow-up periods, with about a 10% relative reduction in mortality at both evaluation times. Survival improvement did not appear to diminish with increasing length of follow-up, as shown by the Kaplan-Meier survival curves in Figure 1. Differences in survival for all ages and for those 65 years and older are statistically significant (P<.001) by both the log-rank and Wilcoxon tests.

View this table: [in this window] [in a new window] Table 5.—Comparison of Mortality Rates in Abstracted Samples*

View larger version (5K): [in this window] [in a new window] Survival curves showing improvement in survival in pilot states from baseline to follow-up period.

Table 6 compares mortality from the claims data. There were no significant differences in either 30-day or 1-year mortality between the pilot state patients and those in the rest of the nation during the baseline period. Mortality was significantly better in the pilot states during the follow-up period, and the difference in 1-year mortality between the pilot states and the rest of the nation was statistically significant (P=.004). The differences in survival during the follow-up period were also statistically significant by both the log-rank test (P=.003) and the Wilcoxon test (P=.004).

View this table: [in this window] [in a new window] Table 6.—Comparison of Mortality Rates From Claims Data*

Other Measures

Rates for invasive cardiology procedures by episode increased significantly from baseline to follow-up. Angioplasty rates increased from 15.1% to 21.9% (P<.001) and catheterization rates increased slightly from 44.5% to 47.3% (P=.001). Coronary artery bypass surgery rates remained stable from 11.2% to 12% (P=.14). These rates do not include procedures performed during nonsampled hospitalization or on an outpatient basis. Invasive procedure rates by episode cannot be estimated for the nonpilot sample because multiple discharges per episode were infrequently sampled. Procedure rates for the sampled nonpilot discharges were not significantly different from the pilot follow-up rates.

Length of stay decreased from the baseline period to the follow-up period. For patients with confirmed MI who were not transferred in or out and who did not die in the hospital, the mean length of stay decreased from 9.8 days to 7.5 days and the median decreased from 8 days to 6 days (P<.001). Length of stay for the nonpilot cases did not differ significantly from the pilot follow-up cases.

COMMENT

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The quality of care for Medicare patients with AMI has improved in the CCP pilot states between the baseline and follow-up periods. Improvements noted in the CCP quality indicators (process measures) are consistent and appear to be associated with an improvement in at least 1 important outcome measure, mortality. The magnitudes of the changes are sufficiently reassuring that meaningful improvements were accomplished, rather than small changes made significant by large sample sizes. Although a recent article has cautioned against attributing improvements in quality to large-scale programs like CCP,¹² the differences between the pilot and nonpilot indicator and mortality rates at follow-up, combined with no differences in mortality rates at baseline and severity indexes at follow-up, suggest that CCP contributed to the improvement.

The improvement in 1 indicator is particularly striking. The use of -blockers at discharge in minimally eligible patients increased from 32% to 50%, an 18% absolute increase or more than a 50% relative increase. In contrast, while the speed with which reperfusion was delivered improved dramatically, only modest improvements were noted in reperfusion rates. Only about 20% of patients 65 years and older with AMI received early reperfusion therapy.

The data show that Medicare patients with AMI have significant comorbidity, eg, diabetes in about 30% and a history of hypertension in about 60%. High comorbidity in patients 65 years and older may be one factor contributing to the low reperfusion rates. The data in Table 3 indicate slightly more comorbidity in the follow-up sample cases than in the baseline. Although some of the differences in comorbid factors are highly statistically significant, the magnitudes of the differences are usually small and could represent variations in abstracter interpretation rather than actual differences in patient characteristics. The closeness of the composite risk indexes (Medicare Mortality Predictor System [MMPS] and Acute Physiology and Chronic Health Evaluation [APACHE] III) for the pilot follow-up and nonpilot samples suggests that these samples are similar with regard to severity of illness. The data in Table 3 also suggest that the follow-up sample does not represent a healthier population and that comorbidity does not explain the lower mortality for the follow-up patients.

The sex distribution for elderly Medicare AMI patients does not show the male predominance typical of clinical trials. The distribution between men and women is close to equal for confirmed AMI in patients 65 years and older and, as the population ages, the sex distribution will shift to a female predominance in the next decade. Ischemic heart disease is very much a women's health issue for the Medicare population.

The results of the eligible and ideal indicators are consistent. Although we do not provide any evidence in this study regarding the superiority of either indicator for quality improvement feedback or for hospital rankings, our results suggest that the simpler eligible indicators are adequate for evaluating changes in large populations. The eligible indicators have an advantage of requiring much less data collection. For example, for aspirin use during hospitalization, we evaluated 22 more variables (details regarding possible contraindications) for the ideal indicator than for the eligible indicator. Eligible indicators may be more efficient for follow-up studies in populations over the course of several years or for other situations in which case mix is stable.

While we believe that these data suggest that CCP has contributed to a measurable improvement in the quality of AMI care in the pilot states, we acknowledge that our study has some limitations. The 4 pilot states are not a random subsample of the nation. The data from the follow-up period suggest that the patient characteristics are not significantly different in the pilot states than in the rest of the nation, but we lack a comparison group to confirm that the processes of care were similar in the pilot states and the rest of the nation at baseline. The similarity in mortality between the pilot states and the rest of the nation at baseline suggests that differences in care processes at baseline were minimal or noneffective.

Nonpilot follow-up results are better than pilot baseline results, suggesting that there have been improvements in care in the rest of the nation. Many factors, such as dissemination of clinical trial results, professional society educational activities, commercially sponsored programs such as the National Registry of Myocardial Infarction,¹³ other national initiatives such as the National Heart Attack Alert Program,¹⁴ and state projects such as the Connecticut Medicare Hospital Information Project¹⁵ probably have contributed to the changes in both pilot and nonpilot states.

We have not yet analyzed any effects on costs. While we do not have formal cost impact studies, we are reassured by the observations that the 2 treatments with the widest applicability that improved significantly, administration of aspirin and administration of -blockers, are inexpensive therapies, and that the process and mortality improvements were accompanied by a decreased average length of stay. We suspect that the decreased length of stay is predominantly caused by non-CCP forces, such as evolving practice patterns, the current emphasis on controlling costs in the medical community, and the influence of managed health care. The CCP may have contributed to declining lengths of stay because quality improvement mechanisms such as critical pathways promoted by the PROs during CCP feedback frequently have goals for both resource conservation and quality improvement. We believe that CCP provides some evidence that quality improvement is achievable in today's environment of cost control.

We should not be too complacent about the positive results. As compared with current clinical trials for AMI that report short-term mortality results of about 5% in selected patients, AMI in the older population remains a deadly disease. Mortality rates are 18% at 30 days and 30% at 1 year, and more patients die before they reach a hospital.¹⁶ We suspect that there may still be room for improvement even in the pilot states and that we have more lessons to learn from CCP and other sources about the optimal care of older patients diagnosed as having AMI.

Because CCP pilot baseline results suggested that opportunities for improving Medicare AMI care existed, HCFA proceeded with CCP activities in the rest of the nation in 1995 and 1996. The CCP national effort has proceeded from data collection (an 8-month sample of Medicare AMI discharges from all hospitals in nonpilot states) through feedback from the PROs. We plan to resample all states for 1997, although with a sample size that will produce reasonably precise national statistics but not hospital-specific statistics. We have learned much from the lessons of the CCP pilot, and are hopeful that the national effort will produce results comparable to those reported herein.

AUTHOR INFORMATION

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Opinions in this article should not be taken as the official position of the Health Care Financing Administration.

Reprints not available from the authors.

All support for this study was provided by the Health Care Financing Administration, Baltimore, Md.

Corresponding author: Thomas A. Marciniak, MD, Health Care Financing Administration, 7500 Security Blvd, Bldg S2-11-07, Baltimore, MD 21244 (e-mail: tmarciniak{at}hcfa.gov).

From the Health Care Financing Administration, Baltimore, Md (Drs Marciniak and Jencks); the Iowa Foundation for Medical Care, Des Moines (Drs Ellerbeck and Kresowik); the University of Kansas Medical Center, Kansas City (Dr Ellerbeck); the Connecticut Peer Review Organization, Middletown (Drs Radford and Krumholz); the Division of Cardiology, University of Connecticut, Farmington (Dr Radford); the Department of Surgery, University of Iowa, Iowa City (Dr Kresowik); MetaStar Inc, Madison, Wis, and the Department of Preventive Medicine and the Health Policy Institute, Medical College of Wisconsin, Milwaukee (Dr Gold); the Cardiovascular Section, Yale University School of Medicine, New Haven, Conn (Dr Krumholz); the Alabama Quality Assurance Foundation and the Department of Veterans Affairs, Birmingham (Drs Kiefe and Allman); the Division of Preventive Medicine (Dr Kiefe) and the Center for Aging (Dr Allman), University of Alabama at Birmingham; and the Department of Cardiology, University of Maryland, Baltimore (Dr Vogel).

REFERENCES

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1. Kerr EA, Mittman BS, Hays RD, Leake B, Brook RH. Quality assurance in capitated physician groups: where is the emphasis? JAMA. 1996;276:1236-1239. FREE FULL TEXT 2. Angell M, Kassirer JP. Quality and the medical marketplace: following elephants. N Engl J Med. 1996;335:883-885. FREE FULL TEXT 3. Jencks SF, Wilensky GR. The Health Care Quality Improvement Initiative: a new approach to quality assurance in Medicare. JAMA. 1992;268:900-903. FREE FULL TEXT 4. Gunnar RM, Bourdillon PDV, Dixon DW, et al. Guidelines for the early management of patients with acute myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Assessment of Diagnostic and Therapeutic Cardiovascular Procedures (Subcommittee to Develop Guidelines for the Early Management of Patients With Acute Myocardial Infarction). J Am Coll Cardiol. 1990;16:249-292. WEB OF SCIENCE | PUBMED 5. Ellerbeck EF, Jencks SF, Radford MJ, et al. Quality of care for Medicare patients with acute myocardial infarction: a four-state pilot study from the Cooperative Cardiovascular Project. JAMA. 1995;273:1509-1514. FREE FULL TEXT 6. Fleiss JL. The measurement of interrater agreement. In: Statistical Methods for Rates and Proportions. New York, NY: John Wiley & Sons Inc; 1981:212-236. 7. Fleming C, Fisher ES, Chang CH, Bubolz TA, Malenka DJ. Study outcomes and hospital utilization in the elderly: the advantages of a merged database for Medicare and Veterans Affairs hospitals. Med Care. 1992;30:377-391. FULL TEXT | WEB OF SCIENCE | PUBMED 8. Normand ST, Glickman ME, Sharma GVRK, McNeil BJ. Using admission characteristics to predict short-term mortality from myocardial infarction in elderly patients: results from the Cooperative Cardiovascular Project. JAMA. 1996;275:1322-1328. FREE FULL TEXT 9. Lambert-Huber DA, Ellerbeck EF, Wallace RG, Radford MJ, Kresowik TF, Allison JA. Quality of care indicators for patients with acute myocardial infarction: pilot validation of the indicators. Clin Performance Qual Health Care. 1994;2:219-222. 10. Stata Statistical Software. Release 4.0. College Station, Tex: Stata Corp; 1995. 11. SAS [computer software]. Release 6.11. Cary, NC: SAS Institute Inc; 1996. 12. Ghali WA, Ash AS, Hall RE, Moskowitz MA. Statewide quality improvement initiatives and mortality after cardiac surgery. JAMA. 1997;277:379-382. FREE FULL TEXT 13. Rogers WJ, Bowlby LJ, Chandra NC, et al. Treatment of myocardial infarction in the United States (1990 to 1993): observations from the National Registry of Myocardial Infarction. Circulation. 1994;90:2103-2114. FREE FULL TEXT 14. National Heart Attack Alert Program Coordinating Committee, 60 Minutes to Treatment Working Group. Emergency Department: Rapid Identification and Treatment of Patients With Acute Myocardial Infarction. Bethesda, Md: US Dept of Health and Human Services, National Institutes of Health, and National Heart, Lung, and Blood Institute; 1993. National Institutes of Health publication 93-3278. 15. Meehan TP, Radford MJ, Vaccarino LV, et al. A collaborative project in Connecticut to improve the care of patients with acute myocardial infarction. Jt Comm J Qual Improv. 1996;22:751-761. PUBMED 16. Ryan TJ, Anderson JL, Antman EM, et al. ACC/AHA guidelines for the management of patients with acute myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Management of Acute Myocardial Infarction). J Am Coll Cardiol. 1996;28:1328-1428. FULL TEXT | WEB OF SCIENCE | PUBMED

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Nephrol Dial Transplant 2009;24:3404-3411.
ABSTRACT | FULL TEXT  

Improved Clinical Outcome After Acute Myocardial Infarction in Hospitals Participating in a Swedish Quality Improvement Initiative
Carlhed et al.
Circ Cardiovasc Qual Outcomes 2009;2:458-464.
ABSTRACT | FULL TEXT  

Increasing smoking cessation care provision in hospitals: A meta-analysis of intervention effect
Freund et al.
Nicotine Tob Res 2009;11:650-662.
ABSTRACT | FULL TEXT  

Characteristics and Outcomes of America's Lowest-Performing Hospitals: An Analysis of Acute Myocardial Infarction Hospital Care in the United States
Popescu et al.
Circ Cardiovasc Qual Outcomes 2009;2:221-227.
ABSTRACT | FULL TEXT  

Using quality indicators to improve hospital care: a review of the literature
De Vos et al.
Int J Qual Health Care 2009;21:119-129.
ABSTRACT | FULL TEXT  

A Statewide Collaborative Initiative to Improve the Quality of Care for Patients With Acute Myocardial Infarction and Heart Failure
Brush et al.
Circulation 2009;119:1609-1615.
ABSTRACT | FULL TEXT  

Questioning Conventional Wisdom
Krumholz
Circ Cardiovasc Qual Outcomes 2009;2:59-60.
FULL TEXT  

Policy Research: Using Evidence to Improve Healthcare Delivery Systems
Ross and Gross
Circulation 2009;119:891-898.
FULL TEXT  

Declining in-hospital mortality and increasing heart failure incidence in elderly patients with first myocardial infarction.
Ezekowitz et al.
J Am Coll Cardiol 2009;53:13-20.
ABSTRACT | FULL TEXT  

Next Steps: How Can Medicare Accelerate The Pace Of Improving Chronic Care?
Foote
Health Aff (Millwood) 2009;28:99-102.
ABSTRACT | FULL TEXT  

Implementation of proven interventions in general medical inpatients: development and evaluation of a new quality indicator for drug therapy
Huang et al.
Qual Saf Health Care 2008;17:269-274.
ABSTRACT | FULL TEXT  

Outcomes Research: Generating Evidence for Best Practice and Policies
Krumholz
Circulation 2008;118:309-318.
FULL TEXT  

Efficacy of In-Hospital Multidimensional Interventions of Secondary Prevention After Acute Coronary Syndrome: A Systematic Review and Meta-Analysis
Auer et al.
Circulation 2008;117:3109-3117.
ABSTRACT | FULL TEXT  

Indwelling Urinary Catheter Use in the Postoperative Period: Analysis of the National Surgical Infection Prevention Project Data
Wald et al.
Arch Surg 2008;143:551-557.
ABSTRACT | FULL TEXT  

Long-term Prognosis of Acute Kidney Injury After Acute Myocardial Infarction
Parikh et al.
Arch Intern Med 2008;168:987-995.
ABSTRACT | FULL TEXT  

Long-term Risk of Mortality and End-Stage Renal Disease Among the Elderly After Small Increases in Serum Creatinine Level During Hospitalization for Acute Myocardial Infarction
Newsome et al.
Arch Intern Med 2008;168:609-616.
ABSTRACT | FULL TEXT  

Association of Troponin Status With Guideline-Based Management of Acute Myocardial Infarction in Older Persons
Shah et al.
Arch Intern Med 2007;167:1621-1628.
ABSTRACT | FULL TEXT  

Influence of a Performance-Improvement Initiative on Quality of Care for Patients Hospitalized With Heart Failure: Results of the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF)
Fonarow et al.
Arch Intern Med 2007;167:1493-1502.
ABSTRACT | FULL TEXT  

Certificate of Need Regulation and Cardiac Catheterization Appropriateness After Acute Myocardial Infarction
Ross et al.
Circulation 2007;115:1012-1019.
ABSTRACT | FULL TEXT  

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods
Stukel et al.
JAMA 2007;297:278-285.
ABSTRACT | FULL TEXT  

Regional Differences in Process of Care and Outcomes for Older Acute Myocardial Infarction Patients in the United States and Ontario, Canada
Ko et al.
Circulation 2007;115:196-203.
ABSTRACT | FULL TEXT  

Trends in Acute Myocardial Infarction in 4 US States Between 1992 and 2001: Clinical Characteristics, Quality of Care, and Outcomes
Masoudi et al.
Circulation 2006;114:2806-2814.
ABSTRACT | FULL TEXT  

Recent Trends in the Care of Patients With Non-ST-Segment Elevation Acute Coronary Syndromes: Insights From the CRUSADE Initiative.
Mehta et al.
Arch Intern Med 2006;166:2027-2034.
ABSTRACT | FULL TEXT  

Impact of medication therapy discontinuation on mortality after myocardial infarction.
Ho et al.
Arch Intern Med 2006;166:1842-1847.
ABSTRACT | FULL TEXT  

Diabetes and Cardiovascular Disease During Androgen Deprivation Therapy for Prostate Cancer
Keating et al.
JCO 2006;24:4448-4456.
ABSTRACT | FULL TEXT  

Assessment of the Medicare Quality Improvement Organization Program
Rollow et al.
ANN INTERN MED 2006;145:342-353.
ABSTRACT | FULL TEXT  

Survival Advantage of Black Patients with Kidney Disease after Acute Myocardial Infarction
Newsome et al.
CJASN 2006;1:993-999.
ABSTRACT | FULL TEXT  

Sex Differences in the Application of Evidence-Based Therapies for the Treatment of Acute Myocardial Infarction: The American College of Cardiology's Guidelines Applied in Practice Projects in Michigan.
Jani et al.
Arch Intern Med 2006;166:1164-1170.
ABSTRACT | FULL TEXT  

An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction
Krumholz et al.
Circulation 2006;113:1683-1692.
ABSTRACT | FULL TEXT  

An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With Heart Failure
Krumholz et al.
Circulation 2006;113:1693-1701.
ABSTRACT | FULL TEXT  

Impact of health care initiatives on outcomes of acute coronary syndromes.
Moscucci and Share
Heart 2006;92:293-295.
ABSTRACT | FULL TEXT  

Door-to-Balloon Time in Primary Percutaneous Coronary Intervention: Is the 90-Minute Gold Standard an Unreachable Chimera?
Moscucci and Eagle
Circulation 2006;113:1048-1050.
FULL TEXT  

Statins and Mortality Among Elderly Patients Hospitalized With Heart Failure
Foody et al.
Circulation 2006;113:1086-1092.
ABSTRACT | FULL TEXT  

Quality Improvement Organizations and Hospital Care--Reply
Snyder and Anderson
JAMA 2005;294:2030-2030.
FULL TEXT  

Quality Improvement Organizations and Hospital Care
Gold et al.
JAMA 2005;294:2029-2029.
FULL TEXT  

Evidence-Based Therapies and Mortality in Patients Hospitalized in December with Acute Myocardial Infarction
Meine et al.
ANN INTERN MED 2005;143:481-485.
ABSTRACT | FULL TEXT  

Improved Clinical Outcomes Associated With Metformin in Patients With Diabetes and Heart Failure
Eurich et al.
Diabetes Care 2005;28:2345-2351.
ABSTRACT | FULL TEXT  

{beta}2-Adrenergic Receptor Genotype and Survival Among Patients Receiving {beta}-Blocker Therapy After an Acute Coronary Syndrome
Lanfear et al.
JAMA 2005;294:1526-1533.
ABSTRACT | FULL TEXT  

Aspirin Use in Older Patients With Heart Failure and Coronary Artery Disease: National Prescription Patterns and Relationship With Outcomes
Masoudi et al.
J Am Coll Cardiol 2005;46:955-962.
ABSTRACT | FULL TEXT  

Prior Aspirin Use and Outcomes in Elderly Patients Hospitalized With Acute Myocardial Infarction
Portnay et al.
J Am Coll Cardiol 2005;46:967-974.
ABSTRACT | FULL TEXT  

Trends in Management and Outcomes of Patients With Acute Myocardial Infarction Complicated by Cardiogenic Shock
Babaev et al.
JAMA 2005;294:448-454.
ABSTRACT | FULL TEXT  

Quality of Care by Classification of Myocardial Infarction: Treatment Patterns for ST-Segment Elevation vs Non-ST-Segment Elevation Myocardial Infarction
Roe et al.
Arch Intern Med 2005;165:1630-1636.
ABSTRACT | FULL TEXT  

Quality of Care in U.S. Hospitals as Reflected by Standardized Measures, 2002-2004
Williams et al.
NEJM 2005;353:255-264.
ABSTRACT | FULL TEXT  

Care in U.S. Hospitals -- The Hospital Quality Alliance Program
Jha et al.
NEJM 2005;353:265-274.
ABSTRACT | FULL TEXT  

Administrative Data Feedback for Effective Cardiac Treatment: AFFECT, A Cluster Randomized Trial
Beck et al.
JAMA 2005;294:309-317.
ABSTRACT | FULL TEXT  

Mental Disorders and Revascularization Procedures in a Commercially Insured Sample
Jones and Carney
Psychosom. Med. 2005;67:568-576.
ABSTRACT | FULL TEXT  

Under-use of beta-blockers in patients with ischaemic heart disease and concomitant chronic obstructive pulmonary disease
Egred et al.
QJM 2005;98:493-497.
ABSTRACT | FULL TEXT  

Do Quality Improvement Organizations Improve the Quality of Hospital Care for Medicare Beneficiaries?
Snyder and Anderson
JAMA 2005;293:2900-2907.
ABSTRACT | FULL TEXT  

Report of the National Heart, Lung, and Blood Institute Working Group on Outcomes Research in Cardiovascular Disease
Krumholz et al.
Circulation 2005;111:3158-3166.
ABSTRACT | FULL TEXT  

Long-term Outcomes of Regional Variations in Intensity of Invasive vs Medical Management of Medicare Patients With Acute Myocardial Infarction
Stukel et al.
JAMA 2005;293:1329-1337.
ABSTRACT | FULL TEXT  

Racial Variations in Treatment and Outcomes of Black and White Patients With High-Risk Non-ST-Elevation Acute Coronary Syndromes: Insights From CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early Implementation of the ACC/AHA Guidelines?)
Sonel et al.
Circulation 2005;111:1225-1232.
ABSTRACT | FULL TEXT  

Medicare As A Catalyst For Reducing Health Disparities
Eichner and Vladeck
Health Aff (Millwood) 2005;24:365-375.
ABSTRACT | FULL TEXT  

Quality of Care of International and Canadian Medical Graduates in Acute Myocardial Infarction
Ko et al.
Arch Intern Med 2005;165:458-463.
ABSTRACT | FULL TEXT  

Management and in-hospital outcome of patients with acute myocardial infarction admitted to intensive care units at the turn of the century: results from the French nationwide USIC 2000 registry
Hanania et al.
Heart 2004;90:1404-1410.
ABSTRACT | FULL TEXT  

Antithrombotic and Thrombolytic Therapy: From Evidence to Application: The Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy
Schunemann et al.
Chest 2004;126:688S-696S.
ABSTRACT | FULL TEXT  

President's page: The appropriate cardiologist: Responsible stewardship in a golden era of cardiology
Wolk et al.
J Am Coll Cardiol 2004;44:933-935.
FULL TEXT  

Optimising care of acute coronary syndromes in three Australian hospitals
Scott et al.
Int J Qual Health Care 2004;16:275-284.
ABSTRACT | FULL TEXT  

Evidence-Based Therapies for Myocardial Infarction: Secular Trends and Determinants of Practice in the Community
Perschbacher et al.
Mayo Clin Proc. 2004;79:983-991.
ABSTRACT  

State-mandated continuing medical education and the use of proven therapies in patients with an acute myocardial infarction
Patel et al.
J Am Coll Cardiol 2004;44:192-198.
ABSTRACT | FULL TEXT  

Enhancing quality of care for acute myocardial infarction: shifting the focus of improvement from key indicators to process of care and tool use: The American College of Cardiology Acute Myocardial Infarction Guidelines Applied in Practice Project in Michigan: Flint and Saginaw Expansion
Mehta et al.
J Am Coll Cardiol 2004;43:2166-2173.
ABSTRACT | FULL TEXT  

Socioeconomic Status and Outcome Following Acute Myocardial Infarction in Elderly Patients
Rao et al.
Arch Intern Med 2004;164:1128-1133.
ABSTRACT | FULL TEXT  

The Potential Preventability of Postoperative Myocardial Infarction: Underuse of Perioperative {beta}-Adrenergic Blockade
Lindenauer et al.
Arch Intern Med 2004;164:762-766.
ABSTRACT | FULL TEXT  

Impracticability of Informed Consent in the Registry of the Canadian Stroke Network
Tu et al.
NEJM 2004;350:1414-1421.
ABSTRACT | FULL TEXT  

CathKIT: improving quality in the cardiac catheterization laboratory
Dehmer et al.
J Am Coll Cardiol 2004;43:893-899.
FULL TEXT  

Preoperative calcium-channel blockade in cardiac surgery: the good, the bad, the issues
Ferguson
J. Thorac. Cardiovasc. Surg. 2004;127:622-624.
FULL TEXT  

Data feedback efforts in quality improvement: lessons learned from US hospitals
Bradley et al.
Qual Saf Health Care 2004;13:26-31.
ABSTRACT | FULL TEXT  

Organizing Regional Perinatal Quality Improvement: Global Considerations and Local Implementation
Wirtschafter and Powers
NeoReviews 2004;5:e50-59.
FULL TEXT  

Get With the Guidelines for Cardiovascular Secondary Prevention: Pilot Results
LaBresh et al.
Arch Intern Med 2004;164:203-209.
ABSTRACT | FULL TEXT  

Risk Factors and Secondary Prevention in Women with Heart Disease
Rathore and Krumholz
ANN INTERN MED 2003;139:954-954.
FULL TEXT  

Risk Factors and Secondary Prevention in Women with Heart Disease
Shlipak et al.
ANN INTERN MED 2003;139:954-955.
FULL TEXT  

Sex Differences in Use of Coronary Revascularization in Elderly Patients After Acute Myocardial Infarction: A Tale of Two Therapies
Rathore et al.
Chest 2003;124:2079-2086.
ABSTRACT | FULL TEXT  

The Quality of Medical Care Provided to Vulnerable Community-Dwelling Older Patients
Wenger et al.
ANN INTERN MED 2003;139:740-747.
ABSTRACT | FULL TEXT  

Communitywide Trends in the Use and Outcomes Associated With {beta}-Blockers in Patients With Acute Myocardial Infarction: The Worcester Heart Attack Study
Silvet et al.
Arch Intern Med 2003;163:2175-2183.
ABSTRACT | FULL TEXT  

Aspirin, beta-blocker, and angiotensin-converting enzyme inhibitor therapy in patients with end-stage renal disease and an acute myocardial infarction
Berger et al.
J Am Coll Cardiol 2003;42:201-208.
ABSTRACT | FULL TEXT  

Use of Continuous Quality Improvement to Increase Use of Process Measures in Patients Undergoing Coronary Artery Bypass Graft Surgery: A Randomized Controlled Trial
Ferguson et al.
JAMA 2003;290:49-56.
ABSTRACT | FULL TEXT  

National and State Trends in Quality of Care for Acute Myocardial Infarction Between 1994-1995 and 1998-1999: The Medicare Health Care Quality Improvement Program
Burwen et al.
Arch Intern Med 2003;163:1430-1439.
ABSTRACT | FULL TEXT  

Regionalization and the Underuse of Angiography in the Veterans Affairs Health Care System as Compared with a Fee-for-Service System
Petersen et al.
NEJM 2003;348:2209-2217.
ABSTRACT | FULL TEXT  

Challenges and opportunities in quantifying the quality of care for acute myocardial infarction: Summary from the acute myocardial infarction working group of the American heart association/American college of cardiology first scientific forum on quality of care and outcomes research in cardiovascular disease and stroke
Spertus et al.
J Am Coll Cardiol 2003;41:1653-1663.
FULL TEXT  

Challenges and Opportunities in Quantifying the Quality of Care for Acute Myocardial Infarction: Summary From the Acute Myocardial Infarction Working Group of the American Heart Association/American College of Cardiology First Scientific Forum on Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke
Spertus et al.
Circulation 2003;107:1681-1691.
FULL TEXT  

Closing The Gap Between Science And Practice: The Need For Professional Leadership
Eagle et al.
Health Aff (Millwood) 2003;22:196-201.
ABSTRACT | FULL TEXT  

JCAHO Accreditation And Quality Of Care For Acute Myocardial Infarction
Chen et al.
Health Aff (Millwood) 2003;22:243-254.
ABSTRACT | FULL TEXT  

The Implications of Regional Variations in Medicare Spending. Part 1: The Content, Quality, and Accessibility of Care
Fisher et al.
ANN INTERN MED 2003;138:273-287.
ABSTRACT | FULL TEXT  

The Implications of Regional Variations in Medicare Spending. Part 2: Health Outcomes and Satisfaction with Care
Fisher et al.
ANN INTERN MED 2003;138:288-298.
ABSTRACT | FULL TEXT  

Validity of a Simple ST-Elevation Acute Myocardial Infarction Risk Index: Are Randomized Trial Prognostic Estimates Generalizable to Elderly Patients?
Rathore et al.
Circulation 2003;107:811-816.
ABSTRACT | FULL TEXT  

Improving the Quality of Care for Patients With Pneumonia in Very Small Hospitals
Chu et al.
Arch Intern Med 2003;163:326-332.
ABSTRACT | FULL TEXT  

Change in the Quality of Care Delivered to Medicare Beneficiaries, 1998-1999 to 2000-2001
Jencks et al.
JAMA 2003;289:305-312.
ABSTRACT | FULL TEXT  

Integrating quality into the cycle of therapeutic development
Califf et al.
J Am Coll Cardiol 2002;40:1895-1901.
ABSTRACT | FULL TEXT  

Specialty of Ambulatory Care Physicians and Mortality among Elderly Patients after Myocardial Infarction
Ayanian et al.
NEJM 2002;347:1678-1686.
ABSTRACT | FULL TEXT  

Outpatient adherence to beta-blocker therapy after acute myocardial infarction
Butler et al.
J Am Coll Cardiol 2002;40:1589-1595.
ABSTRACT | FULL TEXT  

Influence of age on outcomes in patients undergoing mitral valve replacement
Mehta et al.
Ann. Thorac. Surg. 2002;74:1459-1467.
ABSTRACT | FULL TEXT  

Association of Renal Insufficiency with Treatment and Outcomes after Myocardial Infarction in Elderly Patients
Shlipak et al.
ANN INTERN MED 2002;137:555-562.
ABSTRACT | FULL TEXT  

Sex Differences in Cardiac Catheterization after Acute Myocardial Infarction: The Role of Procedure Appropriateness
Rathore et al.
ANN INTERN MED 2002;137:487-493.
ABSTRACT | FULL TEXT  

Task Force #1--magnitude of the prevention problem: opportunities and challenges
Benjamin et al.
J Am Coll Cardiol 2002;40:588-603.
FULL TEXT  

European comparison of costs and quality in the treatment of acute myocardial infarction (2000-2001)
Gandjour et al.
Eur Heart J 2002;23:858-868.
ABSTRACT | FULL TEXT  

Use of Cholesterol-Lowering Therapy by Elderly Adults After Myocardial Infarction
Ayanian et al.
Arch Intern Med 2002;162:1013-1019.
ABSTRACT | FULL TEXT