Hospital Case Volume and Appropriate Prescriptions at
Hospital Discharge After Acute Myocardial Infarction
A Nationwide Assessment
François Schiele, MD, PhD; Frédéric Capuano, MSc; Philippe Loirat, MD;
Armelle Desplanques-Leperre, MD; Geneviève Derumeaux, MD; Jean-François Thebaut, MD;
Christine Gardel, MD; Catherine Grenier, MD
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Background—In acute myocardial infarction, the relationship between volume and quality indicators (QIs) is poorly
documented. Through a nationwide assessment of QIs at discharge repeated for 3 years, we aimed to quantify the
relationship between volume and QIs in survivors after acute myocardial infarction.
Methods and Results—Almost all healthcare centers in France participated. Medical records were randomly selected. Data
collection was performed by an independent group. QIs for acute myocardial infarction were defined by an expert consensus
group as appropriate prescription at discharge of aspirin, clopidogrel, β-blocker, statin, and an angiotensin-converting
enzyme inhibitor in patients with left ventricular ejection fraction <0.40. A composite QI was calculated through the use of
the all-or-none method. Volume was classified into 7 categories based on the number of admissions for acute myocardial
infarctions in 2008 (centers with <10 acute myocardial infarctions were excluded). Odds ratios adjusted for age and sex
with 95% confidence interval for volume categories were calculated by use of logistic regression for each QI. Temporal
changes were tested in centers that participated in all 3 campaigns. A total of 46 390 records were examined: 18 159
in 2008, 12 837 in 2009, and 15 394 in 2010. Two hundred ninety-one centers were eligible for the temporal analysis.
There was a significant increase between 2008 and 2009 in appropriate prescription of antiplatelet agents, β-blockers,
angiotensin-converting enzyme inhibitor, statins at discharge, and the composite indicator. Similarly, a significant increase
was observed between 2009 and 2010 in appropriate prescription of angiotensin-converting enzyme inhibitor and βblockers and in the composite QI. Compared with a volume of >300, a significantly lower rate of all QIs was observed in
centers with the lowest volume. Odds ratios progressively decreased with increasing volume. Despite a significant increase
in the composite QI over the 3 years, a significant relationship persisted between volume and quality of care.
Conclusions—Analysis of QIs at discharge demonstrates the existence of a relationship between volume and appropriate
prescriptions at discharge. Centers with the highest volume perform better on quality measures than centers with
lower volumes. Temporal analysis over 3 consecutive years confirms this relationship and shows that it persists despite
improvement in QIs between 2008 and 2010. (Circ Cardiovasc Qual Outcomes. 2013;6:50-57.)
Key Words: composite indicator ◼ myocardial infarction ◼ quality indicators ◼ quality of care
◼ temporal changes
E
valuation of quality of care has become an integral part
of modern health care and provides key information for
health authorities, health insurance providers, patients, the
general public, and physicians themselves. Among the factors
that can influence the quality of care, hospital case volume has
drawn considerable attention. Indeed, as early as the 1980s,
a relationship between volume of activity and mortality was
described, and it exists not only in certain surgical procedures
but also in medical conditions such as myocardial infarction,
acute heart failure, or pneumonia.1,2
However, the relationship between volume and quality
of care is complex and is characterized by wide variations
in mortality between the different levels of volume. When
quality of care is assessed by rare outcomes such as death, the
measure of volume–quality of care relationship is difficult in
centers with lower activity.3 Thus, it may be that zero mortality
in a given center could merely be the result of chance rather
than a reliable indicator of excellent care.4
Measuring the process of care rather than merely outcomes
is an alternative approach to assess overall quality of care.5
Processes of care can be estimated by quality indicators (QIs)
defined specifically for certain diseases. For instance, QIs
for acute myocardial infarction (AMI) have been developed,
and they take into account the use of reperfusion,6 medical
Received May 29, 2012; Accepted October 23, 2012.
From the French Society of Cardiology, Paris (F.S.); University Hospital Jean Minjoz, Besançon (F.S.); Haute Autorité de Santé, Saint Denis (F.C., P.L.,
A.D.-L., C. Gardel, C. Grenier); National College of French Cardiologists, Paris (G.D.); and National Professional Board of Cardiology, Paris (J.-F.T.), France.
Correspondence to Francois Schiele, MD, PhD, University Hospital Jean Minjoz, Blvd Fleming, 25000 Besançon, France. E-mail francois.schiele@
univ-fcomte.fr
© 2012 American Heart Association, Inc.
Circ Cardiovasc Qual Outcomes is available at http://circoutcomes.ahajournals.org
50
DOI: 10.1161/CIRCOUTCOMES.112.967133
Schiele et al Volume and Discharge Prescriptions After AMI 51
WHAT IS KNOWN
• Higher hospital case volume has been associated with
better outcomes for some conditions.
• Measuring processes of care rather than outcomes is an
alternative approach to assessing overall quality of care.
WHAT THE STUDY ADDS
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• We identified a relationship between case volume and
the quality of prescriptions of evidence-based therapies
for myocardial infarction at hospital discharge, whereby
centers with the highest volume perform better on quality measures than centers with lower volumes.
• Temporal analysis over 3 consecutive years confirms
this relationship and shows that it persists despite
overall improvement in quality indicators between
2008 and 2010.
• The use of a composite indicator based on discharge
prescription makes it possible to assess quality in all
participating centers, but a minimum of 30 patients
per center was required to use the composite for
benchmarking purposes.
therapy during hospitalization and at discharge,7 and composite scores.8 Current guidelines from the European Society of
Cardiology recommend that QIs be recorded after AMI with9
or without10 ST-segment elevation.
In France, the National Authority for Health (Haute Autorité
de Santé) has defined specific QIs to evaluate the management
of AMI, to benchmark performance, and to follow the evolution
of AMI management nationwide from the initial onset of symptoms until 1 year after discharge.11 Three campaigns to measure
these QIs for AMI have been implemented to date, in 2008,
2009, and 2010, throughout the whole country and in all centers
admitting patients for chest pain. The centers participating in
the assessment presented wide variation in case volume. Given
that the relationship between volume and QIs is less well documented than the volume–mortality relationship, we aimed to use
the results of this repeated nationwide assessment to quantify
the relationship between volume and QIs in survivors after AMI.
Methods
Selection of Medical Records for Evaluation
In the framework of the national system for accreditation of healthcare centers, the Haute Autorité de Santé decided to define QIs to
be measured systematically in all centers. Almost all healthcare centers in France (public and private) participated. The medical records
to be evaluated in each center were chosen by random selection of
100 records from among all those with a diagnostic code for AMI
with or without ST-segment elevation (International Classification of
Diseases, 10th revision codes I21.0, I21.1, I21.2, I21.3, I21.9, I22.0,
I22.1, I22.8, I22.9) using specialized randomization software specifically designed for this purpose (LOTAS, available at http://download.
atih.sante.fr/afficher.php?id_lot=725). In 2008, records were selected
from among the 12 months of the year; in 2009, from among the first
6 months of the year; and in 2010, from among the first 9 months.
Only the records of patients discharged alive were analyzed. Records
corresponding to patients transferred to or from another center were
excluded.
Analysis of prescriptions was performed by an independent med­ical
team using a computer-based algorithm. The coherence of data was
verified by an independent group responsible for performance measurement and improvement in hospitals (Mesure de la Performance
et l’Amélioration de la Qualité Hôpital, Patient, Sécurité, Territoire
[COMPAQH-HPST]). QIs for AMI were defined by an expert consensus group on myocardial infarction comprising cardiologists and
methodologists. QIs were based on the recommendations for management of AMI issued by the European Society of Cardiology9,10 and on
existing performance measures developed and used by the American
College of Cardiology/American Heart Association.7 Details of the
QIs can be found on the Web site of the COMPAQH group.12
Appropriate prescription (AP) was defined as prescription in the
absence of any contraindication clearly documented in the patient’s
file or nonprescription in the presence of a clearly documented
contraindication. The following QIs (discharge only) were used
­
­without taking doses into account:
• AP of the association of aspirin and clopidogrel. Contraindications
to aspirin were intolerance or allergy to aspirin, high risk of bleeding, gastroduodenal ulcer, and pregnancy. Contraindications to
clopidogrel were intolerance, high bleeding risk, and pregnancy.
High bleeding risk was accepted as justification for nonprescription of aspirin or clopidogrel when the bleeding risk evaluation
was clearly documented in the patient’s file.
• AP of β-blockers. Two types of contraindication were retained:
absolute contraindications (ie, uncontrolled heart failure, hypotension, high-degree atrioventricular block, severe chronic obstructive pulmonary disease or asthma, the Raynaud syndrome,
and hypersensitivity). In case of relative contraindications (ie,
controlled chronic obstructive pulmonary disease, asthma, diabetes mellitus, first-degree atrioventricular block, and heart failure), a documented evaluation of the risk-benefit ratio had to be
present in the file to justify nonprescription.
• Documentation of a measure of left ventricular ejection fraction
and, in case of ejection fraction <0.40, AP of an angiotensinconverting enzyme inhibitor (ACEI) or an angiotensin receptor
blocker. Contraindications were hypotension or intolerance.
• AP of statins. The only contraindication to statin therapy was
intolerance.
Statistical Analysis
The volume of activity for each center was determined on the basis
of the number of admissions for AMI in 2008, taking into account all
patients, regardless of their outcome. Centers with <10 AMIs were
not included. Centers were classified in to 7 categories according to
the number of admissions for AMI: 10 to 29, 30 to 59, 60 to 89, 90 to
119, 120 to 149, 150 to 299, and ≥300. The cutoff values for volume
categories were determined according to deciles of center volume
distribution. The number of categories was reduced to 7 by grouping
low-volume centers to maintain increments of at least 30 cases between
categories. Two groups of centers were also defined according to
the median volume (90 admissions for AMI in 2008). The results
for each QI are presented by year as number of records, number of
contraindications, and percentage AP. A composite QI was calculated
for each patient according to the all-or-none method (ie, a score of 0 is
attributed if at least 1 applicable QI scores 0, and a score of 1 is given
only when all applicable QIs score 1). Composite QIs are presented as
number (percent). The sensitivity and reproducibility of this composite
QI and a comparison with other types of composites have previously
been published elsewhere.13 Odds ratios adjusted for age and sex with
95% confidence intervals for the volume categories were calculated
using logistic regression for each QI. Adjusted odds ratios for each
volume category were calculated per year and per QI. To account for
within-hospital correlation and the hierarchical data structure, we used a
PROC GENMOD with the repeated statement. Temporal changes were
tested according to the Cochran-Armitage test for binary variables, and
only centers that participated in all 3 campaigns were included in this
analysis. All analyses were performed with SAS software, version 9.2
(SAS Institute Inc, Cary, NC).
52 Circ Cardiovasc Qual Outcomes January 2013
Figure 1. Distribution of the centers by
annual number of admissions for acute
myocardial infarction in 2008. Black bars
represent the cutoff values for volume
categories (10–30, 30–60, 60–90, 90–120,
120–150, 150–300, >300). Red bars
represent the cutoff values for deciles of
volume.
Results
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The vast majority of French healthcare centers participated in
this evaluation. Only 30 centers (4.8%) in 2008, 4 (1.2%) in
2009, and 13 (3.5%) in 2010 did not respond. A total of 46 390
records were examined: 18 159 from 598 centers in 2008, 12
837 from 330 centers in 2009, and 15 394 from 359 centers
in 2010. The distribution of centers according to volume of
activity is shown in Figure 1.
Centers with >30 records represented 84% of all records
(276 centers in 2008, 203 in 2009, and 241 in 2010), and 291
centers were suitable for the temporal analysis, representing
85.1% of all records (Figure 2). Centers with <10 admissions
for AMI (n=198) represented overall <2% of all records evaluated. After exclusion of these centers, the median volume
was 90 (25th and 75th percentiles=58 and 210, respectively).
The difference in the number of centers with >10 admissions
among 2008, 2009, and 2010 results from the different durations of the recruitment period in each year.
The results of the QI measurements for the years 2008 to
2010 are shown in Table 1. In centers that participated in all
3 consecutive years of evaluation, AP of antiplatelet agents,
β-blockers, ACEI, and statins at discharge, as well as the
composite indicator, increased significantly between 2008
and 2009. Similarly, a significant increase was observed
between 2009 and 2010 in AP of ACEI and β-blockers and
in the composite QI. The rate of AP remained consistently
high between 2009 and 2010 for antiplatelet agents (Table 1
and Figure 3). The test for temporal trend was significant for
all QIs (Figure 3). The average values for each QI in centers
that participated in all 3 campaigns are presented in Table 2
according to year and center volume. Figure 4 displays the
age- and sex-adjusted odds ratios per volume category for
each QI in each of the 3 years. Compared with a volume of
>300 cases, a significantly lower rate of all QIs was observed
in centers with the lowest volume (Table 2). In 2008 and
2009, the odds ratios progressively decreased with increasing
volume, but no clear plateau was apparent that would support
the hypothesis of a threshold (Table 2 and Figure 4).
The linear relationship between the composite indicator and
volume of activity is shown in Figure 5 and illustrates the wide
variation in composite scores, particularly in centers with a
low volume of activity.
The temporal change in the relationship between high and
low volume (>90 or <90) and the composite QI is displayed in
Figure 6. Despite a significant increase in the composite QI, a
significant relationship persisted between volume and quality
of care. The time–volume interaction was significant for all
QIs except antiplatelet agents and statins.
Discussion
This nationwide study using robust methodology to evaluate
quality of care through QIs at hospital discharge in a largescale population demonstrates the existence of a relationship
between volume and quality of care in centers treating AMI
Figure 2. Flow chart of the study centers and
records used by year. The first line presents the
number of records examined by year. Lines 2
through 4 present the number of records from centers with <10, 10 to 30, and >30 patients admitted
for acute myocardial infarction in 2008. The bottom
line presents the number of records from centers
with >10 cases in 2008 that participated in all
3 consecutive campaigns (2008, 2009, and 2010).
Schiele et al Volume and Discharge Prescriptions After AMI 53
Table 1. AP at Discharge and Contraindications to Aspirin+Clopidogrel, β-Blockers, ACEI or ARB (in Patients With LVEF <0.40),
Statins, and Composite Indicator (All or None Method) in 2008, 2009, and 2010
Evolution, P
Aspirin and clopidogrel
AP
CI to aspirin
CI to clopidogrel
2008, n (%)
2009, n (%)
2010, n (%)
2008/2009
16 151 (88.9)
12 178 (94.9)
14 583 (94.7)
2009/2010
<0.0001
0.6120
804 (4.4)
289 (2.3)
347 (2.3)
<0.0001
0.9873
1628 (9.0)
816 (6.4)
963 (6.3)
<0.0001
0.7282
<0.0001
β-Blockers
14 326 (93.1)
<0.0001
Absolute CI to β-blockers
1672 (9.2)
918 (7.2)
1219 (7.9)
<0.0001
0.0152
Relative CI to β-blockers
2047 (11.3)
1301 (10.1)
616 (4.0)
0.0015
<0.0001
…
AP
15 465 (85.2)
11 392 (88.7)
ACEI or ARB (patients with LVEF <0.40)
LVEF assessment
15 393
11 410
13 878
…
LVEF <0.40
3223
2332
2772
…
…
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AP
CI to ACEI
2685 (80.8)
2178 (93.4)
2628 (94.8)
<0.0001
0.0325
396 (11.9)
269 (11.5)
327 (11.8)
0.6609
0.7721
16 196 (89.2)
12 121 (94.4)
14 564 (94.6)
<0.0001
0.4942
<0.0001
0.7550
<0.0001
Statins
AP
CI to statins
Composite (all or none)
1121 (6.2)
624 (4.9)
736 (4.8)
11 398 (62.8)
9486 (73.9)
12 101 (78.6)
<0.0001
11 040 (94.9)
12 795 (94.8)
Centers with >10 records and data for 2008, 2009 and 2010
Aspirin and clopidogrel
AP
CI to aspirin
CI to clopidogrel
13 322 (91.0)
<0.0001
0.8814
520 (3.6)
243 (2.1)
285 (2.1)
<0.0001
0.8945
1131 (7.7)
729 (6.3)
819 (6.1)
<0.0001
0.5223
12 569 (93.2)
<0.0001
<0.0001
1070 (7.9)
<0.0001
0.0039
0.0167
<0.0001
β-Blockers
AP
12 611 (86.1)
10 359 (89.0)
Absolute CI to β-blockers
1247 (8.5)
811 (7.0)
Relative CI to β-blockers
1619 (11.1)
1180 (10.1)
549 (0.08)
ACEI or ARB (patients with LVEF <0.40)
LVEF assessment
12 726
10 366
12 147
…
…
LVEF <0.40
2658
2102
2459
…
…
AP
CI to ACEI
2156 (81.1)
1963 (93.4)
2336 (95.0)
<0.0001
0.0198
316 (11.9)
245 (11.7)
286 (11.6)
0.8044
0.9792
13 351 (91.2)
11 000 (94.5)
12 768 (94.6)
<0.0001
0.7223
Statins
AP
CI to statins
Composite (all or none)
717 (4.9)
565 (4.9)
9713 (66.3)
8654 (74.4)
625 (4.6)
10 609 (78.6)
0.8770
0.4063
<0.0001
<0.0001
AP indicates appropriate prescription; CI, contraindication; LVEF, left ventricular ejection fraction; ACEI, angiotensin-converting enzyme inhibitors; and ARB,
angiotensin receptor blockers.
in France. Indeed, admission to a hospital with a high volume
of activity was associated with better performance on QI.
This relationship was observed over 3 consecutive years, and
although performance on QIs progressed from 2008 to 2010,
the difference between high- and low-volume centers persisted.
These findings go beyond previous reports of an
association between volume and mortality, which was first
established several years ago.1,2 These observations suggest
that the difference in mortality is truly related to the quality
of care. The progression in quality with increasing volume
seems linear, without any clear threshold value. This
contradicts what has been shown for the volume–mortality
association, for which a threshold was seen of >600 cases
per year.2 No such threshold was observed in our national
evaluation because few centers reached such a high annual
volume. In addition, the use of QIs instead of mortality
outcomes and the selection of survivors of the acute phase
may explain this discrepancy.
The magnitude of the difference between the highest-and
lowest-volume centers in terms of QIs is considerable. In
54 Circ Cardiovasc Qual Outcomes January 2013
Figure 3. Evolution of the rate of quality
indicators in the 291 centers that participated in the 3 consecutive years of evaluation (2008–2010).
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2008, the absolute value of the difference was ≈10% for AP of
aspirin plus clopidogrel and ACEI and up to 15% for statins or
the composite measure. Although the differences in the rates
of QIs declined in 2009 and 2010, they remain considerably
greater than the impact of volume on mortality at 30 days
after AMI, which was ≈1% to 4%,2 even when reperfusion
QIs were taken into account.14–16 This underlines the greater
sensitivity of process-of-care measures compared with outcome measures. It is important to note that the magnitude of
the difference in QIs according to volume is comparable to the
rate of contraindications recorded for β-blockers or ACEIs.
This underlines the importance of recording QI instead of the
prescription rate alone, despite the higher complexity and cost
that this more complete procedure may incur.
Our results also underscore the existence of heterogeneous
quality of care between the volume categories as shown by
the very wide confidence intervals around the QI rates and the
scattergram plotting the composite indicator against volume
of activity, particularly in centers with low volume. Variations
in quality of care at different volumes of activity have previously been described in surgical procedures.1 Excellent measures of quality in low-volume centers may merely reflect
difficulties in measurement in these centers3 or may alternatively be explained by the fact that the physicians’ experience
Table 2. Mean (SD) of Quality Indicators According to Center Volume Categories and Year Among Centers That Participated in All 3
Consecutive Campaigns
Year
2008
2009
2010
Annual
Volume,n
Aspirin+Clopidogrel,
Mean (SD)
β-Blockers,
Mean (SD)
ACEI/ARB (LVEF <0.40),
Mean (SD)
Statins,
Mean (SD)
Composite All or None,
Mean (SD)
10–30
0.84 (0.37)
0.84 (0.37)
0.73 (0.45)
0.78 (0.41)
0.52 (0.50)
30–60
0.88 (0.32)
0.85 (0.35)
0.79 (0.41)
0.90 (0.30)
0.62 (0.49)
60–90
0.89 (0.32)
0.85 (0.36)
0.82 (0.38)
0.90 (0.30)
0.64 (0.48)
90–120
0.91 (0.29)
0.85 (0.36)
0.78 (0.42)
0.88 (0.32)
0.62 (0.48)
120–150
0.93 (0.26)
0.87 (0.34)
0.82 (0.39)
0.94 (0.25)
0.69 (0.46)
150–300
0.94 (0.24)
0.87 (0.33)
0.83 (0.37)
0.94 (0.24)
0.71 (0.45)
300–750
0.93 (0.26)
0.86 (0.34)
0.84 (0.37)
0.96 (0.19)
0.71 (0.45)
10–30
0.91 (0.28)
0.84 (0.36)
0.91 (0.28)
0.86 (0.34)
0.65 (0.48)
30–60
0.93 (0.26)
0.90 (0.30)
0.88 (0.32)
0.91 (0.28)
0.68 (0.46)
60–90
0.94 (0.23)
0.85 (0.35)
0.91 (0.28)
0.94 (0.23)
0.69 (0.46)
90–120
0.95 (0.22)
0.90 (0.30)
0.96 (0.19)
0.94 (0.23)
0.72 (0.45)
120–150
0.96 (0.21)
0.89 (0.31)
0.94 (0.24)
0.95 (0.22)
0.73 (0.44)
150–300
0.95 (0.21)
0.90 (0.31)
0.94 (0.24)
0.96 (0.20)
0.78 (0.41)
300–750
0.97 (0.18)
0.89 (0.31)
0.95 (0.22)
0.98 (0.16)
0.80 (0.40)
10–30
0.93 (0.26)
0.90 (0.30)
0.93 (0.26)
0.89 (0.31)
0.73 (0.45)
30–60
0.92 (0.27)
0.91 (0.28)
0.90 (0.31)
0.92 (0.27)
0.72 (0.45)
60–90
0.94 (0.23)
0.92 (0.27)
0.96 (0.19)
0.95 (0.22)
0.73 (0.45)
90–120
0.95 (0.22)
0.94 (0.24)
0.95 (0.22)
0.95 (0.22)
0.78 (0.42)
120–150
0.96 (0.20)
0.94 (0.24)
0.96 (0.20)
0.96 (0.19)
0.82 (0.38)
150–300
0.96 (0.20)
0.93 (0.25)
0.96 (0.18)
0.96 (0.20)
0.82 (0.39)
300–750
0.97 (0.18)
0.95 (0.21)
0.97 (0.16)
0.98 (0.15)
0.85 (0.35)
LVEF indicates left ventricular ejection fraction; ACEI, angiotensin-converting enzyme inhibitors; and ARB, angiotensin receptor blockers.
Schiele et al Volume and Discharge Prescriptions After AMI 55
Figure 4. Odds ratios for the failure of
the composite quality indicator for each
year of estimation and by volume category (reference value=centers with >300
admissions for myocardial infarction). CI
indicates confidence interval; AP, appropriate prescription.
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has a greater impact on quality than the center’s volume of
activity,16,17 according to the principle that, at a physician
level, practice makes perfect.
The strong points of our study are the robust methodology,
the use of a composite measure, and the repeated evaluations
over 3 consecutive years.
The evaluation of prescriptions at discharge is part of a
vast national evaluation program implemented by the French
National Authority for Health (Haute Autorité de Santé) in
recent years. This program made it possible for all French
healthcare centers to participate in the evaluation campaigns,
with repeated evaluations over consecutive years, using the
same methodology, and accumulating a total of >48 000
admissions evaluated. Although the decision to launch the
program was made at the initiative of the national authority
for health (an administrative body), the choice of the QIs
and related contraindications was made by an expert group
of cardiologists. In addition, all data were taken directly
from original patient files on site in each center, not from an
administrative database. Although large-scale evaluations of
this type have previously been performed in other countries,
this is the first study to report on a nationwide evaluation,
including practically all centers, with random selection
of records and without age selection. Furthermore, such a
study has never been performed in France to date. Finally,
the national social security system covers the total costs of
treatment after AMI, which may have limited certain economic
biases in prescribing habits at discharge.
Of course, improvement in clinical outcomes remains the
ultimate goal of quality-of-care initiatives. However, assessing
quality through mortality statistics remains difficult because of
the manifold factors involved in this relationship.18 Measuring
processes of care such as QIs presents some advantages over
evaluation of mortality as an outcome. In the case of AMI in
particular, specific indicators were developed almost 10 years
ago and are regularly updated to take into account therapeutic
progress. These indicators are based on the use of reperfusion
techniques6 and medical therapy during hospitalization and
Figure 5. Scattergram of the composite
indicator (all or none) versus activity
volume in 2008.
56 Circ Cardiovasc Qual Outcomes January 2013
Figure 6. Odds ratios for the absence of
appropriate prescription for each quality
indicator for each year of estimation and
by volume categorized according to the
median (>90 [high volume] or <90 [low
volume] admissions for myocardial infarction in 2008). CI indicates confidence
interval; ACEI, angiotensin-converting
enzyme inhibitor; and ARB, angiotensin
receptor blocker.
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at discharge.7 Indeed, current guidelines from the European
Society of Cardiology recommend that QIs be recorded after
AMI with9 or without10 ST-segment elevation.
In our study, we used 4 QIs at discharge that are simple
to define, have good discriminatory capacity, are based on
solid scientific evidence of efficacy, and for which wider use
is both possible and beneficial. These characteristics correspond to the basic requirements for accountability measures19
and are comparable to the QIs used by the American College
of Cardiology/American Heart Association, the National
Quality Measure Clearinghouse, or the Agency for Healthcare
Research and Quality.7
The latest update of the QIs for reperfusion from the
American College of Cardiology/American Heart Association
underlined the difficulties associated with the evaluation of
reperfusion.6 The decision not to measure QIs for reperfusion
or in-hospital treatment has the advantage of rendering the
data collection simple and reliable and makes it possible to
evaluate the totality of centers admitting patients for AMI, not
just centers equipped with reperfusion facilities.
The use of a composite QI makes it possible to give an
overall estimation of quality of care and to classify centers
according to performance.7,8 Among the different methods
of developing composite QIs, we considered the all-or-none
method to be most suited to our needs, given that the absence
of any one of the QIs included in the composite corresponds
to suboptimal management. To account for differences in
recruitment or in the random selection of patient files for analysis, we adjusted for age and sex only, which are known to
be related to underuse of guideline-recommended therapies.
Other types of composite measures are of course possible and,
although correlated to the all-or-none method, could lead to
different results.13
Consecutive evaluation over 3 calendar years with the same
methodology made it possible not only to increase the number
of admissions evaluated but also to gain insight into the temporal evolution of quality of care. Temporal change in treatment and strategies has been studied in different registries as
a marker of progressing quality of care, particularly in the
case of reperfusion20,21 but also in medical therapy22–24 with, in
parallel, temporal evolution in mortality.25–27 The progression
in QIs observed over the 3 years of our study is comparable to
that observed between 2003 and 2006 in the Joint Commission
on Accreditation of Healthcare Organizations and Centers for
Medicare and Medicaid Services evaluations.28,29 Interestingly,
the temporal changes were more pronounced for ACEI and
β-blockers than for aspirin, clopidogrel, and statins, perhaps
because of the relatively high rate already achieved for these
latter prescriptions. In our study, the volume–QI relationship
remained constant from 1 year to the next, and when centers were categorized by volume (<90 or >90 admissions per
year), there was a trend toward an increase in the difference in
quality over time.
Our study suffers from certain limitations inherent to evaluations of quality through measures of processes of care. The
exclusive use of QIs at discharge precludes the measure of the
quality of reperfusion, which is a key element of management
of AMI with ST-segment elevation that contributes to selecting patients who survive the in-hospital phase. In addition, AP
of β-blockers and statins does not necessarily imply optimal
clinical or biological effect. The lack of any parallel evaluation of mortality precludes the establishment of a link between
measures of processes of care and outcome. Furthermore, volume categories were defined on the basis of activity in 2008,
and we assumed that activity remained stable in all centers
over the 3 years of the evaluation. We cannot exclude the possibility that some centers may have had a different level of volume in 2009 or 2010. Finally, the retrospective nature of the
analysis may represent a source of error in the documentation
of indications or contraindications of the drugs under evaluation. However, in the context of multiple healthcare providers,
accurate documentation of indications and contraindications
can be considered part of the quality of care.
Conclusions
Analysis of QIs at discharge demonstrates the existence of a
relationship between volume and the quality of prescriptions
at discharge whereby centers with the highest volume perform
better on quality measures than centers with lower volumes.
Temporal analysis over 3 consecutive years confirms this
Schiele et al Volume and Discharge Prescriptions After AMI 57
relationship and shows that it persists despite improvement in
QIs between 2008 and 2010.
Acknowledgments
We are indebted to Fiona Ecarnot for editorial assistance and help
with the writing of the manuscript.
Disclosures
None.
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Hospital Case Volume and Appropriate Prescriptions at Hospital Discharge After Acute
Myocardial Infarction: A Nationwide Assessment
François Schiele, Frédéric Capuano, Philippe Loirat, Armelle Desplanques-Leperre, Geneviève
Derumeaux, Jean-François Thebaut, Christine Gardel and Catherine Grenier
Downloaded from http://circoutcomes.ahajournals.org/ by guest on June 15, 2017
Circ Cardiovasc Qual Outcomes. 2013;6:50-57; originally published online December 11, 2012;
doi: 10.1161/CIRCOUTCOMES.112.967133
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