Context.— Despite the importance of β-blockers for secondary prevention after
acute myocardial infarction (AMI), several studies have suggested that they
are substantially underutilized, particularly in older patients.
Objectives.— To describe the contemporary national pattern of β-blocker prescription
at hospital discharge among patients aged 65 years or older with an AMI, to
identify the most important predictors of the prescribed use of β-blockers
at discharge, and to determine the independent association between β-blockers
at discharge and mortality in clinical practice.
Design.— Retrospective cohort study using data created from medical charts and
administrative files.
Setting.— Acute care nongovernmental hospitals in the United States.
Patients.— National cohort of 115015 eligible patients aged 65 years or older who
survived hospitalization with a confirmed AMI in 1994 or 1995.
Main Outcome Measures.— β-Blocker as a discharge medication and mortality in the year after
discharge.
Results.— Among the 45308 patients without contraindications to β-blockers,
22665 (50.0%) had a β-blocker as a discharge medication. There was significant
variation by state, ranging from 30.3% to 77.1%. Of the 36795 patients who
were not receiving β-blocker therapy on admission, 16006 (43.5%) had
therapy initiated on or before discharge. Demographic and clinical variables
explained relatively little of the variation in the initiation of β-blocker
therapy. The prescribed use of calcium channel blockers at discharge had a
strong negative association with the use of β-blockers (odds ratio [OR]
of β-blocker use, 0.25; 95% confidence interval [CI], 0.24-0.26). The
New England region had significantly higher use of β-blocker therapy
than the rest of the country. Compared with cardiologists, internists had
similar rates (OR, 0.94; 95% CI, 0.90-1.00) and general and family practice
physicians had lower rates (OR, 0.78; 95% CI, 0.73-0.83). After adjusting
for potential confounders, β-blockers were associated with a 14% lower
risk of mortality at 1 year after discharge. The association with lower mortality
was present in subgroups stratified by age, sex, and left ventricular ejection
fraction.
Conclusions.— Many ideal patients for β-blocker therapy are not prescribed these
drugs at discharge following AMI. The clinical and demographic characteristics
of the patients do not explain much of the variation in the treatment pattern.
Geographic factors and physician specialty are independently associated with
the decision to use β-blockers. Elderly patients who are prescribed β-blockers
at discharge have a better survival rate, consistent with the findings of
randomized controlled trials of younger and lower-risk populations.
DESPITE THE IMPORTANCE of β-blockers for secondary prevention after
acute myocardial infarction (AMI),1,2
several studies have suggested that they are substantially underutilized,3-10
particularly in older patients. Although these studies agree that increasing
the appropriate use of β-blockers is an important opportunity to improve
secondary prevention after an AMI, they differ in study design and approach,
yielding very different estimates of the use of β-blockers. None provide
a national perspective on the prescribed use of β-blockers after an AMI
in the treatment of elderly patients. The studies that have linked patterns
of use of β-blockers with outcomes have been restricted to very selected
samples7 or have been dependent on claims databases
for clinical information9 but generally have
found that β-blockers are associated with increased survival.
To address these issues, we sought to describe the contemporary use
of β-blockers at hospital discharge among elderly AMI survivors who are
ideal candidates for the therapy; to compare the use of β-blockers across
the United States; to identify the most important predictors of the prescribed
use of β-blockers at discharge; and to determine the independent association
between the use of β-blockers and mortality in clinical practice. To
perform this study, we evaluated the medical records of more than 200000 hospitalizations
of Medicare beneficiaries from across the country in 1994 and 1995 with a
principal discharge diagnosis of AMI, as part of the Cooperative Cardiovascular
Project (CCP). The project, a Health Care Financing Administration (HCFA)
collaboration with health care professionals and peer review organizations,
was designed to examine patterns of care and stimulate improvements in the
care and outcomes of Medicare beneficiaries with AMI.
The study sample was obtained from patients in the CCP cohort and includes
Medicare patients aged 65 years or older from nongovernmental acute care hospitals
in the United States and Puerto Rico with a principal discharge diagnosis
of AMI, International Classification of Diseases, Ninth
Revision, Clinical Modification (ICD-9-CM)
code 410, in 1994 and 1995. We did not sample admissions that were not related
to the acute care of an AMI (in which the fifth digit of the ICD-9-CM code is 2). In the CCP states, patients were identified during
an approximately 8-month period (varying in each state) using hospital bills
(UB-92 claims data) in the Medicare National Claims History File. The file
includes all patients treated under fee-for-service plans but does not include
all of the patients treated as part of Medicare managed care risk contracts.
For patients admitted to hospitals in the CCP pilot states (Alabama, Connecticut,
Iowa, and Wisconsin), hospitalizations were sampled from a 4-month period
(August 1995 through November 1995). The hospitalizations that were abstracted
from the CCP pilot states occurred after a feedback intervention based on
an initial data collection from admissions in 1992 and 1993. Sampling in Minnesota
was slightly delayed and some hospitals were undersampled so as not to interfere
with an ongoing special study, the Minnesota Clinical Comparison and Assessment
Project (MCCAP).
The study sample was restricted to patients aged 65 years or older with
a confirmed AMI who were discharged alive. An AMI was defined as a discharge
diagnosis of an AMI and either a creatine kinase (CK) MB level higher than
0.05 or elevation of lactate dehydrogenase (LDH) more than 1.5 times normal
and LDH-1 level higher than LDH-2 level, or 2 of the following 3 criteria:
chest pain, a 2-fold elevation of the CK level, or evidence of AMI on the
electrocardiogram. We excluded patients who died during the index infarction.
For patients who were hospitalized more than once in the sample period, only
the first AMI admission was included. We excluded hospitalizations in which
patients were transferred to another acute care institution because we were
unable to determine their discharge medications. We excluded 3 patients in
whom mortality could not be confirmed or dated. We also excluded patients
who were considered to have a terminal illness, since the goals of their treatment
may not have focused on a survival benefit. (Patients were considered terminally
ill if their records documented that they were terminally ill or had a life
expectancy of less than 6 months; patients with "do not resuscitate" status
were not excluded if they did not meet the criteria for terminal illness.)
We developed restricted cohorts of patients who would be considered
ideal candidates for β-blocker therapy. Patients with contraindications
were excluded from the study whether or not they were taking β-blockers.
However, there is no clear consensus about which patients should be considered
ideal candidates for the medication. From the group of patients above, we
constructed a definition for the primary study sample of ideal candidates
for postdischarge β-blocker therapy (those without strong contraindications
to β-blockers) based on our clinical experience and the medical literature.
In developing this sample, we balanced the need to exclude patients with probable
contraindications with an effort not to be overly restrictive. Consequently,
we excluded patients with the following contraindications: bradycardia (heart
rate <50/min while not taking β-blockers), low blood pressure (systolic
blood pressure <100 mm Hg), high-grade atrioventricular block, asthma,
chronic lung disease, heart failure during the hospitalization, or chart-documented
intolerance to β-blockers. All contraindications were determined by chart
review except for asthma, which was also based on a secondary diagnostic code
(ICD-9-CM code 493.xx).
To determine if our results were dependent on our particular definition
of the sample, we performed the analyses using 3 other definitions of ideal
patients. We defined a sample based on the relative contraindications for β-blockers
listed in the American College of Cardiology (ACC)/American Heart Association
(AHA) Guidelines for the Treatment of Acute Myocardial Infarction.1 This sample (ACC/AHA cohort) was similar to our primary
sample except that we also excluded patients with heart rates less than 60/min
(rather than 50/min), peripheral vascular disease, or diabetes mellitus with
insulin therapy.1 Since the ACC/AHA guidelines
state that β-blockers are not as strongly indicated in low-risk patients,
we also developed a subset of the ACC/AHA sample that excluded patients without
any of the following high-risk characteristics, based on the guidelines: prior
myocardial infarction, an anterior myocardial infarction, advanced age (we
chose 75 years as the cutoff), or hemodynamic evidence of left ventricular
dysfunction (defined as Killip class >1). Finally, we defined a sample based
on the previously published analysis of the initial CCP pilot. For this sample,
we excluded patients with the following characteristics: heart rate less than
50/min, left ventricular ejection fraction (LVEF) less than 0.35, heart failure,
systolic blood pressure less than 100 mm Hg, chronic obstructive pulmonary
disease, depression, diabetes with insulin therapy, dementia, high-grade atrioventricular
block, no significant coronary disease by catheterizations, and low-risk characteristics
(no recurrent chest pain, no arrhythmias, no prior AMI, normal stress test,
and no LVEF <0.50).5
To obtain the information for this project from the medical records,
HCFA established 2 clinical data abstraction centers to abstract records.
These private organizations were responsible for the reliability and efficiency
of the abstraction. Trained technicians abstracted predefined variables from
copies of the hospital record and entered them directly into a computer database
using interactive software available through the HCFA Internet home page at http://www.usccp.org. Data reliability was monitored by random reabstractions,
with overall variable agreement averaging more than 90%. The agreement for β-blocker
at discharge was 97.5% and the κ was 0.64.11
The outcome variable for the first phase of the study was the frequency
of β-blockers as a discharge prescription. All discharge medications
were reviewed and oral β-blockers were identified. Topical β-blockers
were excluded. The principal end point for the second phase of the study was
mortality within 1 year of discharge. This information was ascertained from
the Medicare Enrollment Database, which was derived from the Master Beneficiary
Record from Social Security Administration data, a valid source of vital status.12,13
The independent variables in this study included age, sex, race, medical
history, hospital and discharge medications, clinical status, hospital complications,
hospital procedures, discharge disposition, and length of stay. Age was categorized
into 3 strata: 65 through 74 years, 75 through 84 years, and 85 years and
older. Comorbidities included a chart-documented history of hypertension,
diabetes mellitus, renal dysfunction (defined as blood urea nitrogen level
>14.3 mmol/L [40 mg/dL] or creatinine level >221 µmol/L [2.5 mg/dL]),
history of myocardial infarction, albumin level less than 0.003 g/L (0.03
g/dL), anemia (hematocrit <0.30), and dementia. Hospital treatment variables
on the first day of admission included aspirin, β-blockers, and thrombolytic
therapy. Hospital procedure variables included cardiac catheterization, percutaneous
coronary revascularization, and coronary artery bypass surgery. Variables
that describe clinical events or patient characteristics at any time during
the hospitalization included atrial fibrillation or flutter, stroke, recurrent
chest pain, ventricular tachycardia, intubation, and CK levels more than 4
times the normal level. Left ventricular systolic dysfunction was defined
as an LVEF of less than 0.35. Left ventricular ejection fraction levels were
measured using 1 of the following 3 methods: radionuclide ventriculography,
cardiac catheterization, or echocardiogram, prioritized in that order. Hospital
length of stay was coded as more than 12 days (yes or no), the 85th percentile
for length of stay. Discharge medication variables included aspirin, calcium
channel blockers, and angiotensin-converting enzyme inhibitors. Discharge
disposition was coded as home or to a non–acute care facility. For variables
with more than 3% missing values (ie, prothrombin time, hematocrit, creatinine,
and blood urea nitrogen), we created a dummy variable to indicate missing.
We classified the physicians' specialties on the basis of the attending physician
listed in Medicare Part A claims. Each physician's specialty was identified
by linking his or her unique physician identification number with a directory
of physician-reported specialties maintained by HCFA. For the geographic analysis,
we classified the patients into subgroups based on major regions defined by
the US Bureau of the Census: New England, Mid Atlantic, South Atlantic, East
North Central, East South Central, West North Central, Mountain, and Pacific.
For the first phase of the study, we sought to determine the frequency
with which elderly patients with an AMI were being appropriately discharged
with a prescription for a β-blocker. In several cohorts, we determined
the number of patients considered appropriate for β-blockers and their
prescribed use. Using the primary study sample, we compared the use of β-blockers
by state and territory. Among those patients who were not receiving β-blocker
therapy prior to admission, we evaluated the bivariate associations of demographic,
clinical, physician specialty, and geographic variables with the prescription
of β-blockers at discharge. Then, using the variables from the bivariate
analysis, we developed a multivariable logistic regression model by backward
stepwise selection with the prescription of β-blockers as the dependent
variable. Variables were dropped from the model at a significance level of P <.05.
For the second phase of the study, we estimated the association between
the prescribed use of β-blockers at discharge and 1-year survival, in
an unadjusted model and after adjusting for potential confounders using a
proportional hazards model. In this model, covariates selected on the basis
of clinical relevance were forced in the model. Covariates included demographic
characteristics (age, sex, and race), clinical history (history of diabetes,
dementia, myocardial infarction, heart failure, smoking, hypertension, renal
dysfunction, or stroke), hospitalization data (LVEF <0.35), a variable
indicating whether an LVEF was measured, hematocrit, albumin, heart failure,
recurrent chest pain, ventricular tachycardia, length of stay more than 12
days, CK level more than 4 times normal, cardiac catheterization, percutaneous
transluminal coronary angioplasty, coronary artery bypass surgery, the prescription
of aspirin and angiotensin-converting enzyme inhibitors at discharge, physician
specialty, and the census region of the country. We also evaluated the potential
interaction between the prescribed use of β-blockers at discharge and
age, sex, race, and LVEF by constructing separate fully adjusted models with
interaction terms and by compared results in stratified samples. For cohorts
in which patients with specific characteristics were excluded (eg, diabetes),
that variable was dropped from the model.
All calculations were performed using the software program STATA 5.0
(STATA Corp, College Station, Tex).
Of the 115,015 eligible patients (ie, age ≥65 years, confirmed AMI,
survived the hospitalization, no terminal illness, and not transferred), 69,707
patients (61%) had 1 or more of the following possible contraindications to β-blocker
treatment: 1.1% with bradycardia, 3.8% with high-grade atrioventricular block,
20.7% with asthma or chronic obstructive pulmonary disease, 5.7% with low
blood pressure, 47.0% with heart failure, and 1.0% with reported intolerance
to β-blockers. Thus, the primary study sample of 45,308 elderly AMI patients
were defined as ideal candidates for
β-blocker therapy at discharge
(Table 1).
The ideal candidates for β-blockers had a mean (SD) age of 75.3
(7.1) years; 45.7% were women. Comorbidity was common, with 61.0% having a
history of hypertension, 25.9% with diabetes, and 4.4% with renal dysfunction.
Prior heart disease was also common, with 24.9% with a prior myocardial infarction
and 6.6% with prior heart failure. In the year after discharge, 10.1% died.
Compared with the patients who met study criteria but had at least 1 strong
contraindication to β-blockers, the ideal patients were significantly
younger (75.3 years vs 77.2 years; P<.001) and
less likely to die in the year after discharge (10.2% vs 27.7%; P<.001).
Prescribed Use of β-Blockers
Of the 115015 eligible patients, 42822 (37.2%) had a β-blocker
prescribed at discharge. Of the 45308 ideal patients in the study sample,
22665 (50.0%) had a β-blocker prescribed at discharge. Table 2, Part A, and Table 2, Part B, shows the prescribed use of β-blockers at discharge
with various demographic, clinical, and geographic characteristics of the
patients. Figure 1 shows the prescribed
use of β-blockers at discharge across the country. There is significant
variation by state and by region. The 5 states with the highest use of β-blockers
were Connecticut (77.1%), Massachusetts (74.2%), Maine (68.3%), New Hampshire
(68.9%), and Vermont (66.7%). The lowest use occurred in Mississippi (30.3%),
Puerto Rico (32.1%), Oklahoma (33.5%), Arkansas (33.5%), and Nevada (36.4%).
Compared with New England, all the other census regions had significantly
lower rates.
Several other factors were notable. The prescribed use of calcium channel
blockers at discharge had a strong negative association with the prescribed
use of β-blockers. Physician specialty was also an important predictor,
with cardiologists and internists associated with higher use of β-blocker
therapy than general and family practice physicians.
Among the 8,513 patients receiving β-blocker therapy prior to admission,
6659 (78.2%) were receiving therapy at the time of discharge. Of the 36795
patients not receiving β-blocker therapy prior to admission, 16006 (43.5%)
had therapy initiated on or before discharge. The initiation of β-blocker
therapy in these patients was associated with several demographic and clinical
characteristics, but these variables alone produced a model with only moderate
discriminant ability (area under the receiver operating characteristic curve
[AUC] = 0.65). Adding discharge medications, particularly calcium channel
blockers, increased the AUC to 0.73. In the final model (Table 3), which included regions and physician specialty, the AUC
was 0.75.
β-Blockers and 1-Year Mortality
Among the ideal patients, the 1-year mortality rate was 7.7% for those
who were prescribed β-blockers compared with 12.6% for those who were
not (P<.001). The adjustment for baseline characteristics
attenuated the strength of the association between β-blocker therapy
and survival (Table 4). However,
in the fully adjusted model, the benefit persisted, with β-blocker therapy
at discharge being associated with a 14% lower risk of mortality (P<.001).
There was no significant interaction with mortality between the prescription
of β-blockers at discharge and age, sex, or LVEF. In stratified analyses,
the adjusted relative risk of mortality associated with the use of β-blockers
was 0.81 (95% confidence interval [CI], 0.72-0.91) for patients aged 65 through
74 years, 0.88 (95% CI, 0.81-0.98) for patients aged 75 through 84 years,
and 0.88 (95% CI, 0.78-0.99) for patients aged 85 years or more. The adjusted
relative risk of mortality associated with the use of β-blockers was
0.83 (95% CI, 0.76-0.91) for men and 0.89 (95% CI, 0.81-0.97) for women. The
adjusted relative risk of mortality associated with the use of β-blockers
was 0.91 (95% CI, 0.76-1.08) for patients with an LVEF less than 0.35 and
0.83 (95% CI, 0.76-0.91) for patients with an LVEF of 0.35 or more.
Comparison With Other Definitions of the Study Sample
We also developed several other samples of patients who would be considered
candidates for β-blockers (Table 5). Compared with our definition, the ACC/AHA cohorts and the CCP
cohorts were more restrictive. Despite the differences in the definitions
of the samples, they had similar rates of β-blocker use and a similar
association between β-blockers and survival.
Our principal finding is that in 1994 and 1995, across the United States,
63% of elderly survivors of an AMI were not prescribed β-blocker therapy
at discharge. Many of these patients had at least 1 strong contraindication
to the therapy as documented by detailed medical record review; however, among
those who did not have a strong contraindication for long-term β-blocker
therapy, half were not prescribed the drug at discharge. In addition, more
restrictive cohorts of patients who did not have any of the relative or absolute
contraindications to β-blocker therapy did not have substantially higher
rates. Given that mortality after AMI is high in the elderly and that β-blockers
reduce mortality in this group, our findings reveal an ample opportunity to
improve the care and outcomes for such patients. The variation in the initiation
of β-blockers among the ideal cohort is not well explained by clinical
or demographic factors alone. However, discharge medications, particularly
calcium channel blockers, did explain much more of the variation. Ideal candidates
for β-blockers who received calcium channel blockers were much less likely
to be prescribed β-blockers. This observation, which is disturbing given
the long-term benefit of β-blockers in this population, has also been
observed by others.9
Some of the remaining variation that is not explained by clinical and
demographic factors or discharge medications is explained by the region in
which the patients were hospitalized or the specialty of the admitting physician.
Compared with the New England states, physicians in many other regions were
significantly less likely to prescribe β-blockers to appropriate patients.
Among states, the use of β-blockers ranged from 30.3% in Mississippi
to 77.1% in Connecticut. The results demonstrate heterogeneity in the opportunity
for improvement, although even states and regions with higher use did not
excel in this area. Patients admitted by cardiologists and internists were
much more likely to be discharged receiving β-blockers than those admitted
by general or other types of physicians, demonstrating that opportunities
for improvement are not equal among physician groups.
Prior studies have also reported underutilization of β-blockers
for secondary prevention after an AMI.4,6,8,9,14
Some of the estimates were even lower than what we report. For example, Soumerai
and colleagues9 merged 3 large administrative
databases with data from 1987 through 1992 to examine the use of β-blockers
among elderly survivors of AMI from New Jersey. Using discharge codes and
medication dispensing (or claims) files to define a study sample of 3737 patients
without a contraindication to β-blockers, they found that 21% of eligible
patients filled a prescription for β-blocker therapy within 90 days of
discharge, a much lower estimate than we report. With their approach, about
70% of the Medicare survivors of AMI in New Jersey were considered eligible
for therapy, a much higher estimate than what we found using chart review
data. Their less selective denominator may have led to a lower estimate. Also,
the patients in their study were hospitalized 2 to 7 years before the patients
in our group. Finally, the use of prescription data may have overlooked patients
who were prescribed β-blockers at discharge but did not fill a prescription
within 90 days. On the other hand, our study would have misclassified patients
who were prescribed β-blockers at discharge but did not adhere to the
treatment plan. The New Jersey study also showed a much more prominent benefit
associated with the use of β-blockers, with a 43% lower mortality rate
compared with the 14% that we report in this study. Which estimate is correct?
Whereas the difference between the prescribed use at discharge and the actual
use may have underestimated the benefit of β-blockers in our study, the
use of administrative data to determine the patients who were ideal for treatment
and the covariates used in the multivariable analysis may have overestimated
the benefit in the Soumerai study. Our result is much closer to the estimated
20% reduction found in 16 randomized trials involving more than 18000 patients.15 The use of chart review data (rather than administrative
data) to adjust for imbalances among the groups in their susceptibility to
mortality may have provided our study with an advantage in avoiding the effects
of confounding. Nevertheless, both studies provide reassurance that β-blockers,
tested most thoroughly in younger populations, are also effective in older
patients. These results reinforce the use of β-blockers after AMI as
a quality indicator by the National Committee on Quality Assurance as part
of HEDIS 3.0.
One challenge in this study was defining the study sample. We chose
to create an ideal group of patients by excluding those with strong contraindications
to β-blockers. Heart failure was one such contraindication because β-blockers
should be initiated in this group of patients only when they are stable. We
felt that it would be reasonable to defer the initiation of β-blockers
in patients with clinical heart failure in conjunction with an AMI. To address
concerns about the study sample, we also identified several patient groups.
More restrictive definitions of the sample excluded larger numbers of patients.
Nevertheless, all the samples revealed underutilization as well as an association
between the use of β-blockers and survival.
This study does have some limitations. First, although we determined
the prescribed use of β-blockers based on retrospective chart review,
we could not determine patterns of use after discharge. As a consequence,
we may have misclassified the long-term pattern of use in some patients. However,
for the survival analysis this misclassification would have tended to diminish
the association between the use of β-blockers and improved survival.
Second, our ability to ascertain contraindications to β-blockers was
limited by the information that is documented in the charts. Third, the study
sample was hospitalized in 1994 and 1995, and it is likely that improvements
in care have occurred in the interim, perhaps partly as a result of the CCP.16 Nevertheless, these data present striking and nonuniform
opportunities to improve care across the country, and it is unlikely that
those opportunities no longer exist. The results should stimulate hospitals
and physicians to assess their current level of performance.
The study also has several important strengths. It represents the most
comprehensive evaluation of the use of β-blockers in elderly survivors
of AMI. As part of a national initiative to improve care for elderly patients
with AMI, this study involved the chart abstraction of more than 200000 records
across the country in 1994 and 1995. The charts were abstracted by trained
professionals using standardized definitions with high reliability. Also,
because the patients were Medicare beneficiaries, we had the opportunity to
determine long-term mortality for the cohort.
In summary, we report that β-blockers are underutilized in elderly
patients after AMI. Variation across the country is striking, but all areas
can improve the care of such patients by increasing the appropriate use of β-blockers.
The results of our study reinforce the survival benefit associated with the
use of β-blockers and suggest the need for a national effort to address
this issue.
1.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.Google Scholar 2.Smith SC, Blair SN, Criqui MH.
et al. Preventing heart attack and death in patients with coronary disease.
Circulation.1995;92:2-4.Google Scholar 3.Augusti A, Amau JM, Laporte J-R. Clinical trials versus clinical practice in the secondary prevention
of myocardial infarction.
Eur J Clin Pharmacol.1994;46:95-99.Google Scholar 4.Brand DA, Newcomer LN, Freiburger A, Tian H. Cardiologists' practices compared with practice guidelines: use of
beta-blockade after acute myocardial infarction.
J Am Coll Cardiol.1995;26:1432-1436.Google Scholar 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.Google Scholar 6.Gurwitz JR, Goldberg RJ, Chen Z, Gore JM, Alpert JS. Beta-blocker therapy in acute myocardial infarction: evidence for underutilization
in the elderly.
Am J Med.1992;93:605-610.Google Scholar 7.Karlson BW, Herlitz J, Hjalmarson A. Impact of clinical trials on the use of beta-blockers after acute myocardial
infarction and its relation to other risk indicators for death and 1-year
mortality rate.
Clin Cardiol.1994;17:311-316.Google Scholar 8.Sial SH, Malone M, Freeman JL, Battiola R, Nachodsky J, Goodwin JS. Beta-blocker use in the treatment of community hospital patients discharged
after myocardial infarction.
J Gen Intern Med.1994;9:599-605.Google Scholar 9.Soumerai SB, McLaughlin TJ, Spiegelman D, Hertzmark E, Thibault G, Goldman L. Adverse outcomes of underuse of β-blockers in elderly survivors
of acute myocardial infarction.
JAMA.1997;277:115-121.Google Scholar 10.Whitford DL, Southern AJ. Audit of secondary prophylaxis after myocardial infarction.
BMJ.1994;309:1268-1269.Google Scholar 11.Huff ED. Comprehensive reliability assessment and comparison of quality indicators
and their components.
J Clin Epidemiol.1997;12:1395-1404.Google Scholar 12.Fleming C, Fisher ES, Chang C-H, Bubolz TA, Melenka DJ. Studying outcomes and hospital utilization in the elderly.
Med Care.1992;30:377-391.Google Scholar 13.Kestenbaum B. A description of the extreme aged population based on improved Medicare
Enrollment Data.
Demography.1992;29:565-580.Google Scholar 14.Meehan TP, Hennen J, Radford MJ, Petrillo MK, Elstein P, Ballard DJ. Process and outcome of care for acute myocardial infarction among Medicare
beneficiaries in Connecticut: a quality improvement demonstration project.
Ann Intern Med.1995;122:928-936.Google Scholar 15.Yusuf S, Peto R, Lewis J, Collins R, Sleight P. Beta blocker during and after myocardial infarction: an overview of
the randomized trials.
Prog Cardiovasc Dis.1985;27:335-371.Google Scholar 16.Marciniak TA, Ellerbeck EF, Radford MJ.
et al. Improving the quality of care for Medicare patients with acute myocardial
infarction: results from the Cooperative Cardiovascular Project.
JAMA.1998;279:1351-1357.Google Scholar