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R J McManus a Department of Primary Care and
General Practice, University of Birmingham, Birmingham B15 2TT, b University Medical Centre Nijmegen, Department of Medical
Technology Assessment, 253 MTA, 6500 HB Nijmegen, Netherlands Correspondence to: F
D R Hobbs f.d.r.hobbs{at}bham.ac.uk
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Abstract |
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Objective:
To assess the effect of using
different risk calculation tools on how general practitioners and
practice nurses evaluate the risk of coronary heart disease with
clinical data routinely available in patients' records.
Design:
Subjective estimates of the risk of
coronary heart disease and results of four different methods of
calculation of risk were compared with each other and a reference
standard that had been calculated with the Framingham equation;
calculations were based on a sample of patients' records, randomly
selected from groups at risk of coronary heart disease.
Setting:
General practices in central England.
Participants:
18 general practitioners and 18 practice nurses.
Main outcome measures:
Agreement of results of
risk estimation and risk calculation with reference calculation;
agreement of general practitioners with practice nurses; sensitivity
and specificity of the different methods of risk calculation to detect
patients at high or low risk of coronary heart disease.
Results:
Only a minority of patients' records
contained all of the risk factors required for the formal calculation
of the risk of coronary heart disease (concentrations of high density lipoprotein (HDL) cholesterol were present in only 21%). Agreement of
risk calculations with the reference standard was moderate (
=0.33-0.65 for practice nurses and 0.33 to 0.65 for general practitioners, depending on calculation tool), showing a trend for
underestimation of risk. Moderate agreement was seen between the risks
calculated by general practitioners and practice nurses for the same
patients (
=0.47 to 0.58). The British charts gave the most sensitive
results for risk of coronary heart disease (practice nurses 79%,
general practitioners 80%), and it also gave the most specific results
for practice nurses (100%), whereas the Sheffield table was the most
specific method for general practitioners (89%).
Conclusions:
Routine calculation of the risk of
coronary heart disease in primary care is hampered by poor availability of data on risk factors. General practitioners and practice nurses are
able to evaluate the risk of coronary heart disease with only moderate
accuracy. Data about risk factors need to be collected systematically,
to allow the use of the most appropriate calculation tools.
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What is already known on this topic
Estimates of risk have been shown to be inaccurate General practitioners and practice nurses can use risk calculation tools accurately when given patient data in the form of scenarios What this study adds
When data about risk factors were available, risk calculations made by general practitioners and practice nurses were moderately accurate compared to a reference calculation When adequate information about risk factors is not available, subjective estimates are a reasonable alternative to calculating risk |
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Introduction |
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Cardiovascular disease is the most important cause of death in the world today,1 with a lifetime risk at age 40 of 1 in 2 for men and 1 in 3 for women in developed countries.2 In the United Kingdom, 66 000 people aged under 75 die from cardiovascular disease each year.3 The British government has set a target of a reduction in cardiovascular disease in this age group of at least two fifths by 2010. Prevention on this scale requires major action to reduce the adverse consequences of risk factors for cardiovascular disease. 4 5 Specific interventions will need to be used for hypercholesterolaemia, 6 7 hypertension, 8 9 smoking,10 and diabetes 11 12 (primary prevention strategies), and people already suffering from cardiovascular disease will need to be treated (secondary prevention).13-15
People with the highest risk of coronary heart disease stand to gain the most, in absolute terms, from interventions, and effective methods to identify such people are required. To date, most emphasis has been placed on secondary prevention; those most likely to benefit from secondary prevention are identified relatively easily on the basis of a history of cardiovascular disease. Identification of patients suitable for primary prevention is less straightforward, and recent guidelines have recommended the use of formal risk scoring with an algorithm based on the Framingham equation to identify high risk patients.16-19 The recent national service framework for coronary heart disease in the United Kingdom will eventually require primary prevention of coronary heart disease on the basis of risk calculations for coronary heart disease.20 Although the Framingham equation has been shown to predict events when it was applied retrospectively to placebo populations recruited to statin trials,21 evidence for the use of risk calculations in primary care is conflicting.
General practitioners and practice nurses are able to use risk tables accurately when given patient data in the form of scenarios.22 However, accuracy was only moderate in a study that compared risks calculated in daily practice by general practitioners and practice nurses using the New Zealand risk tables with a reference calculation of risk.23
An alternative to calculation is for clinicians to use their knowledge
of the patient to estimate the risk subjectively. This method is quick
and does not need a full set of risk factors to provide an answer
but
studies that evaluated this approach showed disappointing results. A
Canadian study found that doctors accurately estimated the relative
risk for hypothetical patients, but that they systematically
overestimated the absolute risk of developing coronary heart
disease.24 Another study, in the United Kingdom, compared
subjective estimates of risk with calculations made using the
Framingham equation and found that general practitioners consistently underestimated the risk.25
We are not aware of any study that directly compared subjective
estimates of risk with formal calculations on the basis of data
available routinely in patients' records. This study aimed to assess
the accuracy with which general practitioners and practice nurses
apportion the risk of coronary heart disease, in a quasi-routine clinical setting, by estimating and calculating, with four different calculation tools, the risk of coronary heart disease, by using a
randomly selected sample of patient records, quota sampled for varied
risk factors for cardiovascular disease.
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Methods |
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We recruited 18 practices from the Midlands Research
Practices Consortium
a research network that comprises more than 70 general practices scattered across the West Midlands. The network's
overall practice populations are generalisable, in terms of
socioeconomic gradient and type of location, to England and Wales.
Each practice performed computerised searches to identify patients in five groups at risk of coronary heart disease: those with hypertension, type 1 or 2 diabetes or hypercholesterolaemia; those who were current smokers; and those with current coronary heart disease (defined as history of angina, previous myocardial infarction, or previous coronary artery bypass or coronary angioplasty). We asked practices to use their own disease registers in the searches, because this represents the way that groups at risk of coronary heart disease would be identified by risk scoring in routine practice. Once the five groups had been identified, we randomly selected 10 sets of notes by choosing two patients from each group. Quota sampling was used to ensure that the sample contained no fewer than three women and no fewer than three patients over 65 years of age.
Four different risk calculation tools, representing the most widely used tools and a spectrum of different formats (risk chart or electronic calculator), were selected for comparison. The tools were the Sheffield table (a paper chart),26 the New Zealand hypertension guideline risk table (a paper chart),19 the joint European societies' recommendations on prevention of coronary heart disease (a wall chart),27 and the joint British societies' recommendations on the prevention of coronary heart disease in clinical practice (a computer program, which is also available as a paper chart).28 Each tool uses slightly different data to calculate risk (see table 1).
In each practice, a general practitioner and a practice nurse estimated and calculated risks separately and blinded to each other in a dedicated non-clinical session (to approximate to an audit session in the practice). The practitioners were asked first to subjectively estimate the coronary heart disease risk for the 10 chosen patients, using only information in the patients' notes and computer records. They were then asked to calculate the risk, using the four different calculation tools, from the information available in the patient's records. To prevent an ordering effect, each practice used the calculation tools in a different predetermined sequence. Instructions about how to use the calculation tools were as given in the first published descriptions of the tools. 19 26-28 For each patient, the general practitioner or practice nurse recorded the risk calculation (or explained why they were not able to calculate it).
Analysis
The risks obtained with each of the tools were divided into
high or low risk. The recommendations in the national service framework
for coronary heart disease define high risk as a >30% risk of
coronary heart disease at 10 years, and they say that interventions,
such as statins, should be used in primary prevention for patients with
risks higher than this. The nearest equivalent to this level provided
by each table was chosen as the cut-off value: >3% annual risk of
coronary heart disease for the Sheffield table, >20% risk of
cardiovascular disease at five years for the New Zealand table
(note the apparently higher risk band used because cardiovascular risk
rather than coronary heart disease risk was calculated), >20% risk of
coronary heart disease at 10 years for the European chart, and >30%
risk of coronary heart disease at 10 years for the British program.
All estimates and calculations were compared with one prospectively
derived "reference standard" score of risk, which was calculated
for each patient by using a computerised version of the original
Framingham equation16 and data independently collected from the patients' records by researchers. Where data
for example, concentrations of total cholesterol or high density lipoprotein (HDL)
cholesterol
were missing, age and sex adjusted national averages were
used in the reference calculation.29 In line with current
British recommendations, the reference standards were classified as
high risk if the risk of coronary heart disease at 10 years was greater
than 30% or if the patient had pre-existing cardiovascular
disease.20
We performed analyses with SPSS for Windows (version 10). We compared estimates and calculations of risk with reference calculations by using the K statistic to test agreement above chance,30 and estimates made by general practitioners and practice nurses for the same patient were also compared. We separately examined risks calculated for patients with pre-existing cardiovascular disease to find out in how many scores for the risk of coronary heart disease had been calculated inappropriately. We determined the sensitivity and specificity of each method compared with the reference calculation.
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Results |
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Availability of relevant data in routine patient records
The records of 70 patients contained evidence of
cardiovascular disease; these patients could be classified as being at
high risk of coronary heart disease without risk estimation or
calculation. Risk calculation was appropriate for the remaining 110 patients
sex and age were documented in all cases. Blood pressure and
smoking status were recorded for most patients, although cholesterol concentrations, particularly of HDL cholesterol, were present in fewer
records (table 1). The number of patients who could be classified from
these data with each calculation tool varied from 92 (51%) for the
British program and New Zealand table to 161 (89%) for the Sheffield
table (table 1).
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Subjective risk estimation and formal risk scoring
Subjective estimates by practice nurses agreed with the
reference calculation in 125 (69%,
=0.38) cases and with general
practitioner estimates in 131 (71%,
=0.45) cases (table 2). The
number of formal (objective) risk calculations attempted and the
proportion correct varied (table 2). Nurses using the British program
achieved the closest agreement with the reference calculation
(
=0.65), but attempted the fewest calculations with this tool (96, 53%). General practitioners achieved the closest agreement with the
reference calculation when using the British program (
=0.55), the
New Zealand table (
=0.53), and the Sheffield table (
=0.51), but
they attempted fewer calculations with the former (99 v 134 v 131). The greatest number of calculations was attempted
with the European table (148, 82% by practice nurses and 149, 83% by
general practitioners), but little agreement with the reference
calculation was seen (
=0.38 for practice nurses, 0.33 for general
practitioners).
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Some risk calculations were completed for people for whom risk scoring
was inappropriate
for example, patients with a history of coronary
heart disease, who automatically are eligible for secondary prevention
(table 3). Partly because of this systematic error in scoring, the
overall trend using objective risk scoring was towards an
underestimation of risk (table 2).
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Repeatability of subjective estimates and formal risk
calculations
comparing results from general practitioners and practice nurses for the same patient
was moderate (between
=0.47 for
estimates and
=0.58 for scoring risk with the British program)
(table 4).
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Sensitivity was lowest for practice nurses using the Sheffield table to calculate risk (58%) and highest for general practitioners using the British program (80%) (table 5). Specificity was lowest for practice nurses using the New Zealand table (63%) and highest for practice nurses using the British program (100%).
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Discussion |
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In this study, general practitioners and practice nurses were asked to assess whether people were at high or low risk of coronary heart disease, consistent with the recommendations of the national service framework for coronary heart disease. The greatest overall accuracy was achieved when primary care clinicians used the British program to calculate coronary heart disease risk.
Limitations of formally calculating risk
An important limitation of using formal calculations to
assess the risk of coronary heart disease in primary care is that
information necessary for determining risk factors may not be
available. This is a particular problem for the New Zealand table and
British program, which use concentrations of HDL cholesterol (the notes
of only a fifth of patients (23/110) contained this information when
patients with existing coronary heart disease were excluded). In
contrast, it was possible to calculate risk for most patients with the
Sheffield and European tools.
A second problem is that the calculations may be used
inappropriately
risk scores were calculated in up to 40% of patients with coronary heart disease, even though such patients can be classified as high risk because of their disease history alone. This
tended to be less of a problem with the British program, perhaps
because the instructions about not applying the program to such
patients were clearer.
Accuracy of tools
When enough data are available, general practitioners and
practice nurses can achieve reasonable accuracy with the different calculation tools. The British program was the tool that was used most
reliably
it gave the best results in terms of sensitivity for general
practitioners and practice nurses and specificity for practice nurses.
With the possible exception of the British program, risk calculators
were no more accurate than subjective assessment for determining the
risk of coronary heart disease. This is likely to be because the
calculators were used in inappropriate patients and because of the poor
availability of data needed for calculations.
For the New Zealand table and the British program, risk was calculated for several patients in whom data about concentrations of HDL cholesterol were not available. Although it should only have been possible to use the table to calculate risk in 22 out of 110 patients without known coronary heart disease, nurses and general practitioners gave results for 78 patients and 64 patients, respectively. In most of these cases, the clinician seems to have assumed that the concentration of HDL cholesterol was 1 mmol/l.
Accuracy of tools in identifying patients at high or low risk
Assessing whether people are at high or low risk of
coronary heart disease is the most clinically relevant way of using the
risk calculation tools, because a dichotomous decision has to be made
as to whether or not to treat each patient. Cut-off values closest to
30% risk at 10 years were chosen for each calculation tool; this will
have resulted in some variation in the results from the different tools
and the reference standard since, with the exception of the British
program, the cut-off values were slightly different from this level. As
expected, a higher threshold (such as the 3% per year risk used in the
Sheffield table) gave a less sensitive but more specific calculation,
but a lower threshold (such as the 20% 10 year risk used in the
European chart) did not give the expected more sensitive and less
specific assessments. It is not clear why; perhaps the choice of >20%
10 year risk as the cut-off value for the European chart (necessary because of the categories used in that chart) may have led to its
relatively poor performance.
Accuracy of estimates and calculations
Past studies have not compared the results of subjective
estimates with calculations in the same patients. Grover et al asked
253 general practitioners attending an educational meeting to determine
risk for four theoretical patients.24 The general
practitioners systematically overestimated the absolute baseline risk
of developing coronary disease and the risk reductions associated with
specific interventions. Montgomery et al compared absolute risk
estimations for 397 patients with hypertension with risk scores
calculated with the Framingham equation.25 Estimates were
correct in 21% of patients; 63% of risks were underestimated and 16%
overestimated. Neither study analysed the results in terms of the
choices between high and low risk and whether to initiate formal
preventive treatment or not, which is the most important decision for
primary care.
Accurate use of tools
Few studies have looked at how accurately professionals use
tables to calculate risk. In a Scottish study that used case histories
to test how accurately general practitioners and practice nurses used
the Sheffield and New Zealand tables and the British program, high and
low risk thresholds were used, and enough data were provided to make
all calculations possible; the table and program performed best in this
study, producing calculations that were correct in most
cases.22 Peters et al found only moderate agreement
between the reference standard and risk scores calculated by 34 general
practitioners and five practice nurses who used the New Zealand table
for 228 hypertensive patients (weighted
=0.56).23
Limitations of our study
The main limitations of our study are that the general
practitioners and practice nurses performed the estimates and
calculations in protected time outside of consultations, and that they
were all drawn from practices with an interest in research. Results
achieved within the time pressures of a consultation would be expected
to be worse than those in our study.
The lack of information (especially about concentrations of HDL cholesterol) in the patient records meant that we had to use estimates to calculate the reference standard, as has been the case in past studies.23 Although such estimates may introduce some error, the reference standard will still represent the best evaluation of risk that is possible, given what is known about the patient.
Implications for clinical practice
The present study did not directly measure the accuracy
with which general practitioners and practice nurses use a particular
table. However, the results suggest that problems with extracting data
from records and applying the tools only to appropriate patients may be
at least as important as simple errors in calculations.
Adequate training is required to ensure that the risk calculation tools
are used only for appropriate patients. The availability of data about
risk factors needed for these tools, especially concentrations of total
cholesterol and HDL cholesterol, needs to be improved
a point
emphasised in the national service framework for coronary heart
disease. In the absence of complete data, subjective estimates of risk
seem to be a reasonable alternative.
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Acknowledgments |
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Contributors: FDRH had the initial idea for the study and RM, JM, HP, and FDRH devised the study. RS and CM recruited the practices. RM, RS, and CM collected the data from practices. RM, JM, and AR performed the analysis. RM, JM and FDRH wrote the first draft of the paper. All authors contributed to subsequent drafts and approved the final version. FDRH will act as guarantor.
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Footnotes |
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Funding: This study was funded by the Midlands research practice consortium, which is supported by Budget 1 NHS research and development competitive funding.
Competing interests: None declared.
Further information on members of
the Midlands Research Practice Consortium is available on bmj.com
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(Accepted 15 October 2001)
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