1. health and fitness
2. drugs

Q J Med 2004; 97:21–31
doi:10.1093/qjmed/hch006
Drug treatment of stable angina pectoris and
mass dissemination of therapeutic guidelines:
a randomized controlled trial
M.-D. BEAULIEU1, J. BROPHY2, A. JACQUES3, R. BLAIS4,
R. BATTISTA5 and R. LEBEAU1
From the 1Chaire docteur Sadok Besrour en me´decine familiale,
Centre de recherche du Centre Hospitalier de l’Universite´ de Montre´al,
2
Divisions of Cardiology and Clinical Epidemiology, McGill University Health Centre,
3
Colle`ge des me´decins du Que´bec, 4De´partement d’administration de la sante´, Universite´ de
Montre´al, and 5Agence d’e´valuation des technologies et des modes d’intervention en sante´,
Montreal, Quebec, Canada
Received 8 August 2003 and in revised form 21 October 2003
Background: Public agencies responsible for implementing health care policies often adapt and
disseminate clinical practice guidelines, but the
effectiveness of mass dissemination of guidelines is
unknown.
Aim: To study the effects of guideline dissemination
on physicians’ prescribing practices for the treatment of stable angina pectoris.
Design: Randomized controlled trial.
Methods: A sample of 3293 Quebec physicians
were randomly assigned to receive a one-page
summary of clinical practice guidelines on the
treatment of stable angina (in February 1999), to
receive the summary and a reminder (in February
and March 1999, respectively), or to receive no
intervention (controls). The prescribing profiles of
participants, as well as sociodemographic characteristics of the physicians and their patients, were
examined for June–December 1999.
Results: The intervention had no effect on prescription rates of b-blockers, antiplatelet agents, or
hypolipaemic drugs. Compared to 1997 data for
the same physicians, there was an overall 10%
increase in appropriate prescription rates, irrespective of the intervention.
Discussion: In-house production and dissemination of clinical practice guidelines may not
improve physicians’ practice patterns if there is
pre-existing substantial scientific consensus on
the issue.
Introduction
When public agencies are responsible for implementing health care policies, their strategy usually
includes the in-house production and mass dissemination of clinical practice guidelines, even if
such guidelines are available from national or
international professional associations. Although
such public agencies do not usually ‘reinvent the
wheel’, they do commit substantial resources to
Address correspondence to Dr M.-D. Beaulieu, Centre de recherche du CHUM, Hoˆpital Notre-Dame, Pavillon
L.-C. Simard, 8e e´tage1560, rue Sherbrooke EstMontre´al (Que´bec) H2L 4M1, Canada.
e-mail: [email protected]
QJM vol. 97 no. 1 ! Association of Physicians 2004; all rights reserved.
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Summary
22
M.-D. Beaulieu et al.
Methods
Study population
The study population and sampling procedure
have been described in detail previously.7 Briefly,
physicians from three geographically distinct
regions were identified through the computerized
administrative databases of the Re´gie de
l’Assurance Maladie du Que´bec (RAMQ, the
Quebec Health Insurance Board), which contain
data for all physician visits, interventions, and
prescriptions for Quebec residents 65 years of age
and older. To be eligible for the survey, physicians
had to have been part of our 1997 study,7 be the
primary prescribing physician (responsible for more
than half of all anti-anginal prescriptions) for at
least one patient (see below), and still be prescribing
cardiovascular medications as of 30 December
1999. Since each prescription delivered by the
pharmacist is linked to the physician who
wrote the prescription, it was possible, from the
database, to include only prescription data
from the identified prescribing physician, that is,
prescription data is specific to the allocated primary
physician, thus avoiding prescriber-prescription
misclassification.
The validity of these databases is well established.9 Nevertheless, to confirm the diagnosis of
stable angina further, we developed an algorithm
using information in the database about medications, interventions, and hospital admission.7
Patients who matched both the ‘claim diagnosis’
and the ‘algorithm diagnosis’ were then deemed to
be undergoing treatment for stable angina. For each
of these patients, we identified the primary prescribing physician.
Intervention
The existing provincial guidelines for anti-anginal
therapy8 had been endorsed by the provincial
licensing authority, the College des Me´decins du
Que´bec (CMQ), which then developed a userfriendly, one-page summary. This summary incorporated three key messages targeting the most
problematic prescribing practices identified in our
earlier cross-sectional study,7 namely low prescribing rates for antiplatelet and hypolipaemic drugs
and for b-blockers in patients without apparent
major contra-indications. The key recommendations
in the summary were: (i) to write a prescription for
acetylsalicylic acid for patients with stable angina;
(ii) to control serum cholesterol, with a target value
for low-density lipoprotein cholesterol < 2.6 mmol/l;
and (iii) to favour b-blockers as the first choice for
anti-angina medication. Data on prescribing rates
for the three targeted medication classes by physicians practicing in the same regions as the
participating physicians were also included in the
one-page summary.
Randomization
The physicians identified in our previous study were
randomly assigned, using computer-generated
random numbers, to one of three groups. The
first group received no intervention (n ¼ 1091), the
second group received the one-page summary of
the guidelines (n ¼ 1087), and the third group
received the one-page summary, followed a month
later by a reminder notice, which included stickers
to post on patients’ charts (n ¼ 1115). The samples
thus assembled were sent to the CMQ, which, by
law, is the only body that can access the encrypted
physician identifiers used in the administrative
databases. The CMQ mailed the one-page summary
to the two intervention groups in February 1999,
and the reminder notice to the second intervention
group in March 1999.
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adapting existing guidelines and disseminating them
under their own auspices. This process is perceived
as necessary to establish local (or regional) credibility of guidelines, and is often the best way that
the agencies can reach all their constituencies.
Literature on the impact of large-scale dissemination of guidelines is scarce and inconsistent, leading
to uncertainty about its value. Dissemination of
guidelines appears less effective than intense
continuing medical education (CME)-based interventions.1–3 Nonetheless, guideline availability
may contribute to meaningful changes in practice
patterns when applied to large populations.4,5
However, the impact of such mass dissemination,
and whether this relates to the novelty of the
message, the complexity of the guidelines, characteristics of the physicians, or uptake by other
stakeholders such as hospitals and local professional
associations, is often unclear.3,5,6
We have previously demonstrated significant
under-use of recommended anti-anginal therapies
in some regions within the province of Quebec,7
despite the existence of provincial guidelines.8
Therefore, we performed a randomized controlled
trial to study the effects of guideline dissemination
on physicians’ prescribing practices for the treatment of stable angina pectoris. This study was one
component of a government-funded initiative to
support the development of a ‘guideline infrastructure’ in the province.
Disseminating therapeutic guidelines
Outcome variables
Explanatory variables
In addition to information on physician visits and
prescriptions, the RAMQ files contained sociodemographic characteristics of both patients and
physicians (including, for the latter, year of graduation and speciality). We created a variable ‘cotreatment’. Co-treatment between a general practitioner and a cardiologist or internist was deemed
to exist if there was concomitant billing during the
Figure 1. Randomization of physicians in the study.
year for a complete major medical examination for
a different category of physicians than his principal
prescribing physician. The patient could appear
only once in the database.
Comorbidities were identified by drug usage:
oral hypoglycaemics, including acarbose with or
without insulin, as an indicator of diabetes; theophylline with or without b2-agonist, steroid, or
ipratropium inhaler, as an indicator of chronic
obstructive pulmonary disease (COPD); and any
two of the angiotensin-converting enzyme inhibitor,
diuretic, or digoxin triad, as an indicator of heart
failure.
Statistical analysis
For each outcome variable, multilevel logistic
regression was used to study the impact of certain
predictors at the patient and physician levels,
while taking into account the covariance between
observations sharing the same hierarchical structure.
We used the formula proposed by Snijders and
Bosker,10 which produces intra-class correlation
coefficients as measures of the variation between
physicians and the logit of the dependent variable.
The ML-Win software package (version 1.0) was
used.11
Results
Of the 3293 physicians in our initial study,7 967
(29.4%) were not in the database in 1999, hence
were considered lost to follow-up. Thus 2326
(70.6%) were available for the current study
(Figure 1). Since our database was anonymous, it
was impossible to track down what happened to
those physicians. The only way not to be in the
database, was if a physician did not prescribe any
cardiovascular medication as a principal prescriber
in any of the three study regions, during the 1999
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We studied the prescribing profiles of the participating physicians for the period June–December
1999 by examining data in the RAMQ files, as
described previously.7 A 6-month period between
the intervention and the outcome measures was
chosen to reflect the usual follow-up period for
patients with stable angina, as suggested by our visit
database. A shorter observation period was deemed
to short to show any changes, and a longer one, too
far from the intervention to be confident in attributing observed changes to it.
We defined three outcome variables according
to the guidelines:8 exposure to b-blockers as the
anti-ischaemic regimen of choice (as monotherapy
or with calcium-channels blockers and/or nitrates);
exposure to antiplatelet drugs (which is supposed
to be part of all regimens, unless contra-indications
are present); and exposure to hypolipaemic drugs
(which were then recommended if LDL-cholesterol
was > 2.6 mmol/l). Since each class of drugs has
its contra-indications, we considered the exposure
to each one as independent, even if it was likely that
the majority of patients would receive a drug from
each of the three classes. The following classes of
medications were considered to represent treatment of stable angina: anti-ischaemics (b-blockers,
calcium-channel blockers, long-acting nitrates),
antiplatelet agents, and hypolipaemics.
23
47
232
338
150
650 (84.7)
75 (9.8)
42 (5.5)
6.5 7.0
39.8 31.6
8.1 11.6
Professional experience
< 10 years
10–20 years
21–30 years
> 30 years
Medical training
General practitioner
Cardiologist
Internist
Mean SD number of
patients in database
according to physician’s
training
General practitioner
Cardiologist
Internist
Data are numbers (%), except where stated.
(6.1)
(30.2)
(44.1)
(19.6)
545 (71.1)
222 (28.9)
Control
(n ¼ 767)
Sex
Male
Female
Characteristic
(5.5)
(33.4)
(42.2)
(18.9)
6.5 6.4
43.4 40.9
10.1 15.2
676 (88.3)
65 (8.5)
25 (3.2)
42
256
323
145
541 (70.6)
225 (29.4)
Guideline
(n ¼ 766)
(8.2)
(37.1)
(36.8)
(17.9)
6.1 6.7
43.6 44.1
9.6 11.1
665 (83.9)
80 (10.1)
48 (6.1)
65
294
292
142
553 (69.7)
240 (30.3)
Guideline þ recall
(n ¼ 793)
(6.6)
(33.6)
(41.0)
(18.8)
6.4 6.7
42.3 38.9
9.3 12.6
1991 (85.6)
220 (9.5)
115 (4.9)
154
782
953
437
1639 (70.5)
687 (29.5)
Total 1999
study group
(n ¼ 2326)
Based on ANOVA
test, 449.24 (0.000)
8.97 (0.175)
16.14 (0.013)
0.34 (0.843)
Test of difference
between groups
w2 (p value)
(9.4)
(27.8)
(26.0)
(36.8)
Not available
856 (88.5)
52 (5.4)
59 (6.1)
91
269
251
356
687 (71.0)
280 (29.0)
Lost to follow-up
between 1997–1999
(n ¼ 967)
Not calculated
15.92 (0.000)
146.32 (0.000)
0.11 (0.769)
Test of difference
between 1999 study
group vs. lost to follow-up
w2 (p value)
Characteristics of the 2326 physicians in the 1999 study database by study group, and comparing those ’lost to follow-up’ between the 1997 and 1999 studies
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Table 1
24
M.-D. Beaulieu et al.
Disseminating therapeutic guidelines
study period. We hypothesized that the majority had
either moved or retired, since the RAMQ prescribing
database is up-to-date without delays as far as
physicians’ data is concerned. This hypothesis is
supported by the observation that physicians who
were not found in the 1999 database were elderly,
hence with a greater probability of having retired
(Table 1). Some may have been on sick leave or
stopped prescribing cardiovascular medications,
reflecting a career reorientation. However, ‘lost to
follow-up’ was equally distributed in the three study
groups.
Male doctors (70.5%), general practitioners (GPs)
(85.6%), and doctors with > 10 years but < 31 years
of experience (74.6%) constituted the majority of
the sample (Table 1). On average, GPs had fewer
patients represented in the database than did
cardiologists and internists. Of the 10 883 patients,
25
about half were men and about half were older
than 75 years (Table 2). Approximately 20% of the
patients were receiving a medication for each of
the three selected comorbidities. Shared treatment
by a generalist and a cardiologist or internist was
observed for 70.9% of the patients. The three groups
(controls and two intervention groups) were comparable in this respect.
The distribution of the prescriptions across the
three categories of anti-ischaemic drugs were the
following: 2162 (20%) patients were on b-blockers
only; 1364 (12.5%) were on b-blockers and nitrates;
1615 (13.9%) were on b-blockers and calciumchannels blockers; and 1760 (16%) were on triple
therapy. A total of 4088 (37.6%) of patients had
no b-blockers in their anti-angina regimen (either
calcium-channels blockers or nitrates or a combination of the two).
Table 2 Characteristics of the 10 883 patients in the study sample database, according to physician study group
Characteristic
w2 (p value)
Guideline
(n ¼ 3487)
Guideline þ recall
(n ¼ 3827)
Sex
Male
Female
1880 (52.7)
1689 (47.3)
1731 (49.6)
1756 (50.4)
1954 (51.1)
1873 (48.9)
6.51 (0.039)
Age
65–69 years
70–74 years
75 years
834 (23.4)
989 (27.7)
1746 (48.9)
782 (22.4)
936 (26.8)
1769 (50.7)
815 (21.3)
1072 (28.0)
1940 (50.7)
6.95 (0.325)
Location of residence
Urban
Rural
Suburban
1927 (54.0)
351 (9.8)
1291 (36.2)
2096 (60.1)
322 (9.2)
1069 (30.7)
2356 (61.6)
364 (9.5)
1107 (28.9)
53.61 (0.000)
697 (19.5)
586 (16.4)
650 (18.2)
730 (20.9)
592 (17.0)
634 (18.2)
774 (20.2)
687 (18.0)
728 (19.0)
2.16 (0.340)
3.15 (0.208)
3.86 (0.425)
2527 (70.8)
2438 (69.9)
2749 (71.8)
4.45 (0.108)
1725 (45.1)
1534 (40.1)
568 (14.8)
4.25 (0.374)
4.2 4.0
4.0 4.6
F 7.35 (0.001)a
832 (24.3)
2376 (69.4)
216 (6.3)
1045 (27.9)
2475 (66.0)
231 (6.2)
35.07 (0.000)
Medication for
COPD
Heart failure
Diabetes
Co-treatment by a generalist
and cardiologist or internist
No. of physicians who prescribed CAD treatment drugs in previous year
1
1659 (46.5)
1618 (46.4)
2
1381 (38.7)
1392 (39.9)
3
529 (14.8)
477 (13.7)
Mean SD no. of visits to
principal prescriber
4.4 4.4
Principal site of visits to principal prescriber*
Acute care services
798 (22.6)
Private office
2503 (71.0)
Other
224 (6.4)
Data are numbers (%), except where stated. COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease.
*Figures do not sum to total n of each group, because of lack of a principal site of visits for some patients.
a
The test used here is an ANOVA rather than w2.
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Control
(n ¼ 3569)
26
M.-D. Beaulieu et al.
Table 3 Summary of multilevel logistic regression models predicting prescription of selected cardiovascular medications in
1999
b-Blockers
Antiplatelet
Hypolipaemics
Patient characteristics
Sex
Male
Female (reference category)
1.15 (1.06,1.25)*
1.00
1.43 (1.32,1.55)*
1.00
1.12 (1.03,1.22)*
1.00
Age
65–69 years (reference category)
70–74 years
75 years
1.00
0.98 (0.87,1.11)
0.79 (0.71,0.88)*
1.00
1.01(0.90,1.14)
0.94 (0.84,1.04)
1.00
0.92 (0.82,1.03)
0.49 (0.44,0.54)*
Location of residence
Urban (reference category)
Rural
Suburban
1.00
1.23 (1.01,1.46)*
0.99 (0.89,1.11)
1.00
1.13 (0.96,1.32)
1.10 (0.99,1.22)
1.00
1.10 (0.92,1.30)
0.93 (0.83,1.05)
Co-treatment by a generalist
and cardiologist or internist
No
Yes
1.00
1.08 (0.98,1.19)
1.00
0.94 (0.85,1.03)
1.00
1.29 (1.17,1.42)*
Medication for COPD
No
Yes
1.00
0.36 (0.32,0.40)*
1.00
0.93 (0.84,1.02)
1.00
0.82 (0.74,0.92)*
Heart failure
No
Yes
1.00
0.61 (0.55,0.68)*
1.00
0.73 (0.66,0.81)*
1.00
0.72 (0.64,0.81)*
Diabetes
No
Yes
1.00
1.00 (0.90,1.11)
1.00
1.28 (1.15,1.42)*
1.00
1.22 (1.10,1.36)*
No. of physicians who prescribed
CAD treatment drug in previous year
1
2 (reference category)
3
0.70 (0.64,0.77)*
1.00
1.58 (1.38,1.81)*
0.75 (0.69,0.82)*
1.00
1.51 (1.33,1.72)*
1.06 (0.97,1.17)
1.00
1.13 (0.99,1.28)
Physician characteristics
Group assignment
Control (reference category)
Guideline
Guideline þ recall
1.00
1.00 (0.88,1.13)
1.04 (0.92,1.18)
1.00
1.05 (0.94,1.18)
1.07 (0.95,1.20)
1.00
1.02 (0.90,1.16)
0.95 (0.83,1.08)
Sex
Female (reference category)
Male
1.00
0.93 (0.81,1.07)
1.00
1.00 (0.87,1.14)
1.00
0.84 (0.72,0.97)*
Medical training
General practitioner
Cardiologist (reference category)
Internist
0.68 (0.58,0.81)*
1.00
0.94 (0.72,1.23)
1.20 (1.03,1.40)*
1.00
1.45 (1.12,1.87)*
0.86 (0.73,1.02)
1.00
1.10 (0.84,1.45)
Professional experience
0–10 years
11–20 years (reference category)
> 20 years
0.83 (0.62,1.10)
1.00
1.01 (0.89,1.13)
1.10 (0.83,1.45)
1.00
0.87 (0.77,0.97)*
0.92 (0.68,1.24)
1.00
0.69 (0.61,0.78)
(Continued )
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Class of drug . . .
Disseminating therapeutic guidelines
27
Table 3 Continued
Class of drug . . .
b-Blockers
Antiplatelet
Hypolipaemics
Number of patients by physician
1–5
6–10 (reference category)
11–25
> 25
0.89 (0.75,1.05)
1.00
0.99 (0.85,1.15)
0.98 (0.81,1.19)
1.01 (0.86,1.19)
1.00
1.05 (0.91,1.21)
1.25 (1.05,1.49)*
1.03 (0.86,1.22)
1.00
1.18 (1.01,1.38)*
1.21 (0.99,1.47)
Intra-class correlation
0.069
0.038
0.074
Data are odd ratios (95%CI) for receiving a prescription for the class of drug. COPD, chronic obstructive pulmonary disease;
CAD, coronary artery disease. *Statistically significant at p 0.05.
Impact of intervention and predictors
of prescribing profiles: results of
multilevel regression analysis
Comparison between 1997 and
1999 profiles
Although the intervention had no impact on
prescribing patterns, all prescribing profiles
improved from 19977 to 1999 (Figure 2a). We
observed an overall increase of 10% in the
prescribing rates for antiplatelet agents and bblockers from 1997 to 1999, and a smaller overall
Discussion
Our results augment current knowledge in two
respects. First, disseminating a simplified version of
current guidelines for treating stable angina had little
overall effect on prescribing practices. Secondly,
certain physician characteristics were associated
with more appropriate prescribing of some drug
classes.
In previous experimental studies of continuing
medical education (CME) methods, mass dissemination of information in traditional printed format did
not significantly alter patterns of practice,3,12,13 and
our observations are consistent with those findings.
However, we should be prudent in extrapolating
these results to all methods of mass dissemination
of information. Diffusion of information is the first
step in knowledge transfer,14 and must occur as part
of any global strategy for change. Time series
and before-and-after studies with controls have
suggested that mass dissemination of information
alone may contribute to the desired evolution in
practices at the health system level.3,5,6,15 We now
need to determine whether we can identify particular situations and specific guideline characteristics that will encourage appropriate change.
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At the patient level, patients receiving medications
for COPD and heart failure were less likely to
receive prescriptions for b-blockers and, to a lesser
extent, for antiplatelet agents and hypolipaemics
(Table 3). However, diabetic patients were more
likely to receive the latter two classes of medication.
Co-treatment by a generalist and a cardiologist or
an internist increased the likelihood of taking a
hypolipaemic drug. Patients who received prescriptions for anti-angina medication from more than one
physician—but not necessarily the combination of a
GP and a cardiologist or internist—were more likely
to have prescriptions for a b-blocker and for an
antiplatelet drug.
At the physician level, the intervention (group
assignment) had no impact on prescribing rates
(Table 3). GPs were less likely to prescribe bblockers than cardiologists but more likely to
prescribe antiplatelet drugs. Doctors with > 20
years of experience tended to prescribe antiplatelet
agents significantly less often, whereas high-volume
physicians (those with more than 25 patients in the
database) had a higher probability of prescribing
these drugs. The percentage of variation in prescribing profile attributable to physician characteristics,
as estimated by the intra-class correlation coefficients, was 6.9% for b-blockers, 3.8% for antiplatelet agents, and 7.4% for hypolipaemics.
increase in the prescribing rates for hypolipaemic
drugs. However, for hypolipaemic drugs, these
increases were not distributed equally among
patient age groups: greater increases were seen
for patients aged 70 years (Figure 2b). We used
logistic regression to explore the predictors of
improvement toward the targeted recommendations
(Table 4). Being a cardiologist was associated with a
greater likelihood of prescribing each of the three
classes of medication. Men were more likely to
prescribe antiplatelet agents, and physicians with
less experience (11–20 years) were less likely to
prescribe hypolipaemic drugs.
28
M.-D. Beaulieu et al.
Table 4 Summary of logistic regression models predicting increase in prescriptions of selected cardiovascular medications
between 1997 and 1999
Physician characteristics
b-Blockers
Antiplatelets
Hypolipaemics
Sex
Male
Female (reference category)
0.95 (0.73,1.24)
1.00
1.3 (1.01,1.73)*
1.00
0.90 (0.69,1.18)
1.00
Professional experience
< 10 years
10–20 years
21–30 years
> 30 years (reference category)
0.56 (0.30,1.07)
0.86 (0.62,1.18)
1.08 (0.81,1.45)
1.00
0.66 (0.34,1.27)
1.19 (0.87,1.64)
1.36 (1.02,1.82)*
1.00
1.15 (0.62,2.14)
0.89 (0.65,1.22)
1.12 (0.84,1.49)
1.00
Medical training
General practitioner
Cardiologist
Internist (reference category)
1.46 (0.87,2.46)
4.2 (2.28,7.62)*
1.00
1.23 (0.73,2.06)
1.9 (1.05,3.39)*
1.00
1.12 (0.66,1.88)
1.6 (1.16,2.19)*
1.00
1.04 (0.96,3.29)
1.08 (0.87,2.56)
1.12 (0.79, 2.34)
Number of patients in the database
Treated as a continuous variable:
contribution of each additional patient
Data are odds ratios (95%CI) for an increase in prescription rate, compared with reduction or no change in prescription rate.
*Statistically significant at p 0.05.
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Figure 2. Prescription of drugs of interest in 1997 study and 1999 (this study), presented as mean percentage of patients in
each physician’s practice who were receiving the drug.
Disseminating therapeutic guidelines
angina patients seen by a physician, the physician’s
specialty, or co-treatment by a GP and a cardiologist
or internist. In contrast, studies from the US
have identified better practice profiles and better
outcomes for patients with acute coronary syndromes who were being treated by a cardiologist, or
by a primary care physician and a cardiologist,
relative to patients treated by a primary care
physician alone.20,21 Our results do suggest that
cardiologists were more likely to have improved
their prescribing practices with time. There might be
several reasons for this. Cardiologists have more
rapid patient turnover, tending to see more new
patients in a given period than GPs do, and it is
easier to initiate a new regimen in a new patient
than to modify the existing regimen of a known
patient. Furthermore, it has been suggested that
family physicians are slower or more prudent than
specialists in modifying their practices, particularly
if it means changing a regimen that is already
known to work for a given patient.22 We could not
assess the contribution of this phenomenon, since
we did not analyse differences in practice for new
and previously known patients. It is also possible
that cardiologists are more comfortable prescribing
b-blockers to patients with relative contra-indications, such as older age, diabetes, or cardiac failure,
contraindications that are now being challenged
on the basis of current research.23 Other reasons
might be a greater propensity among cardiologists
to change their prescribing practices, or greater
exposure of cardiologists to new practice guidelines.
Finally, it is likely that cardiologists see patients with
more severe degree of coronary diseases, which can
influence their prescription profiles and the way
they adapt to new knowledge. Although we were
able to control for confounding attributable to some
co-morbidities, namely diabetes, COPD and heart
failure, we were not in a position to assess coronary
disease severity.
Our study had several strengths. First, we had
access to all information related to physician visits
and prescriptions for the entire physician sample
and their patients 65 years of age and older. We
used a multilevel approach, the best method to take
into account the hierarchical structure of the data.
We cannot attribute the absence of a difference
between intervention and control groups to a lack of
power: because of the large sample size, this study
had a power of 80% to detect a 7% difference
between the study groups at the 5% level.
The study also had some limitations. We are not
comfortable generalizing the results to patient
populations aged < 65 years for two major reasons.
First, younger patients are under a variety of
reimbursement schemes, with different co-payment
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The internal characteristics of guidelines, such
as their complexity and acceptability, have been
shown to influence uptake,4,6 and our intervention
was developed to address perceived shortcomings
in practice guidelines for stable angina (complexity,
unappealing format, and inaccessibility). Physicians’
agreement with guideline content is also important.15,16 For example, the Health Service Utilization and Research Commission of Saskatchewan
found that three of eight guidelines disseminated to
physicians with no additional intervention had an
impact on services, four had no significant impact,
and one had an impact opposite to that intended.5
The guidelines that had an impact were perceived
as conveying an innovation, responded to a
perceived need for information, and were not
perceived as inconsistent with current trends in
treatment. In our negative study, we may have
presented physicians with a message that was not
perceived as innovative and that did not respond
to perceived needs.
With regard to physicians’ uptake of practice
guidelines on the pharmacological treatment of
stable angina, our results are reassuring in that
they show improvements in the prescription rates of
b-blockers, antiplatelet agents, and hypolipaemic
drugs in patients aged 65 years, relative to
results obtained 2 years earlier for the same
physician sample.7 The small and shrinking
variation attributable to physician characteristics,
as indicated by the intra-class coefficient of the
multilevel regressions, confirms a certain standardization of practice (from 0.079 in the 1997 study to
0.069 in 1999 for b-blockers; from 0.044 to 0.038
for antiplatelet agents; and from 0.095 to 0.074 for
hypolipaemic drugs). In the current study, patients’
clinical characteristics had more effect on prescribing practices than physicians’ characteristics, which
suggests that clinical reasons are the principal
determinants of prescribing decisions, as should
be the case. Still, certain groups, specifically women
and patients aged over 70, were less likely to
receive treatment in accordance with the guidelines,8 as was the situation in our 1997 study,7 and
in other studies of patients with coronary artery
disease.17–19 We cannot conclude on the appropriateness of treatment on a patient basis, since we
do not have the necessary individual clinical
information to do so. Nonetheless, the generally
favourable evolution of prescribing practices is
encouraging, and is in agreement with the overall
messages of the current guidelines.
As in 1997,7 patients being treated by GPs were
less likely to receive b-blockers. However, we did
not identify any consistent association between
optimal treatment profiles and the number of
29
30
M.-D. Beaulieu et al.
Acknowledgements
We thank Ms Peggy Robinson for her help in the
preparation of the manuscript. Dr Brophy receives
financial support from le Fonds de Recherche en
Sante´ du Que´bec (FRSQ). This project was funded
by the Health Transition Fund, Health Canada. The
results do not necessarily reflect the opinions of
Health Canada.
M-DB received financial support from Aventis
Pharma in 2000 to attend conferences to present
preliminary results of an RCT to evaluate the
effectiveness of a workshop to modify physicians’
performances of periodic health examinations in
adults. She also received a research grant from this
company in 1998 to complete that study, which was
also funded by the Medical Research Council of
Canada.
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