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Explaining variation in cancer survival between eleven
jurisdictions in the International Cancer Benchmarking
Partnership: a primary care vignette survey
Journal: BMJ Open
Manuscript ID: bmjopen-2014-007212
Article Type: Research
Date Submitted by the Author: 02-Dec-2014
Complete List of Authors: Rose, Peter; University of Oxford, 2. Department of Primary Health Care Rubin, Greg; Durham University, School of Medicine and Health Perera, Rafael; University of Oxford, Primary Health Care
Almberg, Sigrun; Norwegian University of Science and Technology, Department of Cancer Research and Molecular Medicine, Faculty of Medicine Barisic, Andriana; Cancer Care Ontario, Department of Prevention and Cancer Control Dawes, Martin; University of British Columbia, Department of Family Practice Grunfeld, Eva; University of Toronto, Department of Family and Community Medicine Hart, Nigel; Queen's University Belfast, School of Medicine, Dentistry and Biomedical Sciences - Centre for Public Health Neal, Richard; Bangor University, North Wales Centre for Primary Care
Research Pirotta, Marie; University of Melbourne, General Practice and Primary Care Academic Centre Sisler, Jeff; University of Manitoba, Department of Family Medicine Konrad, Gerald; University of Manitoba, Department of Family Medicine Toftegaard, Berit; Aarhus University, Research Unit for General Practice, Department of Public Health Thulesius, Hans; Kronoberg County Research Council, Family Medicine, Department of Clinical Sciences Vedsted, Peter; Aarhus University, Research Unit for General Practice, Department of Public Health
Young, Jane; University of Sydney, Cancer Epidemiology and Services Research (CESR) Hamilton, Willie; University of Exeter Medical School, Primary Care Diagnostics ., ICBP Module 3 Working Group; ICBP Module 3 Working Group, ICBP Module 3 Working Group
<b>Primary Subject Heading</b>:
General practice / Family practice
Secondary Subject Heading: Health policy, Health services research
Keywords: HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, International
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Explaining variation in cancer survival between eleven jurisdictions in the International Cancer
Benchmarking Partnership: a primary care vignette survey
Corresponding author - Peter W Rose, Department of Primary Care Health Sciences, University of
Oxford, New Radcliffe House, 2nd Floor, Radcliffe Observatory Quarter, Woodstock Road, Oxford,
OX2 6GG, United Kingdom, peter.rose@phc.ox.ac.uk, 07738 587 370
Greg Rubin, Professor of General Practice and Primary Care, Wolfson Research Institute, Queen's
Campus, Durham University, Stockton on Tees, TS17 6BH, United Kingdom, g.p.rubin@durham.ac.uk
Rafael Perera-Salazar, Department of Primary Health Care Sciences, University of Oxford, New
Radcliffe House, 2nd Floor, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG,
United Kingdom, rafael.perera@phc.ox.ac.uk
Sigrun Saur Almberg, Department of Cancer Research and Molecular Medicine, Faculty of Medicine,
Norwegian University of Science and Technology (NTNU), N-7491 Trondheim, Norway,
sigrun.saur@ntnu.no
Andriana Barisic, Research Associate, Department of Prevention and Cancer Control, Cancer Care
Ontario, 620 University Avenue, Toronto, Ontario, M5G 2L7, Canada,
Andriana.Barisic@cancercare.on.ca
Martin Dawes, Head, Department of Family Practice, David Strangway Building, University of British
Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada,
martin.dawes@familymed.ubc.ca
Eva Grunfeld, Director, Knowledge Translation Research Network Health Services Research Program,
Ontario Institute for Cancer Research; Professor and Vice Chair Research, Department of Family and
Community Medicine, University of Toronto, 500 University Avenue, Toronto, Ontario, M5G 1V7,
Canada, Eva.Grunfeld@utoronto.ca
Nigel Hart, Clinical Senior Lecturer, School of Medicine, Dentistry and Biomedical Sciences - Centre
for Public Health, Queen's University Belfast, University Road Belfast, BT7 1NN, United Kingdom,
n.hart@qub.ac.uk
Richard D Neal, Professor of Primary Care Medicine and Director, North Wales Centre for Primary
Care Research, Bangor University, Gwenfro Units 4-8, Wrexham Technology Park, Wrexham, LL13
7YP, United Kingdom, r.neal@bangor.ac.uk
Marie Pirotta, Primary Health Care Research Evaluation and Development Senior Research Fellow,
Department of General Practice, 200 Berkeley Street, Carlton Victoria 3053, Australia,
m.pirotta@unimelb.edu.au
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Jeffrey Sisler, Associate Dean, Division of Continuing Professional Development and Associate
Professor, Department of Family Medicine, University of Manitoba, 727 McDermot Avenue,
Winnipeg, Manitoba, R3E 3P5, Canada, Jeff.Sisler@med.umanitoba.ca
Gerald Konrad, Associate Professor, Department of Family Medicine, University of Manitoba 5-400
Tache Avenue, Winnipeg, Manitoba, Canada, GKONRAD@exchange.hsc.mb.ca
Berit Skjødeberg Toftegaard, PhD Research Fellow Research, Unit for General Practice, Department
of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C, Denmark,
berit.toftegaard@feap.dk
Hans Thulesius, Associate Professor of Family Medicine, Department of Clinical Sciences, Kronoberg
County Research Council, Box 1223, 351 12 Växjö, Sweden, hansthulesius@gmail.com
Peter Vedsted, Professor, Research Unit for General Practice, Department of Public Health, Aarhus
University, Bartholins Allé 2, 8000 Aarhus C, Denmark, p.vedsted@feap.dk
Jane Young, Professor in Cancer Epidemiology, Public Health, School of Public Health, D02-QE11
Research Institute for Mothers and Infants, The University of Sydney, 2006, Australia,
jane.young@sydney.edu.au
William Hamilton, University of Exeter Medical School, College House, St Luke's Campus, Magdalen
Road, Exeter, EX1 2LU, United Kingdom, W.Hamilton@exeter.ac.uk
The ICBP Module 3 Working Group* (See Appendix A)
Word count: 3627
Abbreviations: International Cancer Benchmarking Partnership (ICBP), Primary care practitioners
(PCP), Positive Predictive Value (PPV)
Keywords: Survey, primary care, cancer, diagnosis, investigations,
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ABSTRACT
Objectives
The International Cancer Benchmarking Partnership (ICBP) is a collaboration between six countries
and 12 jurisdictions with similar primary care led health services. This study investigates factors that
may contribute to cancer survival differences across these jurisdictions.
Design
A validated survey set out in two parts: direct questions on primary care structure and practice
relating to cancer diagnosis, and clinical vignettes, assessing management of scenarios relating to
the diagnosis of lung, colorectal or ovarian cancer.
Participants
2795 primary care physicians (PCPs) in 11 jurisdictions: New South Wales and Victoria (Australia),
British Columbia, Manitoba, Ontario (Canada), England, Northern Ireland, Wales (United Kingdom),
Denmark, Norway, Sweden.
Primary and secondary outcome measures
Analysis compared the cumulative proportion of PCPs in each jurisdiction opting to investigate or
refer at each phase for each vignette with 1 year survival and conditional 5 year survival rates for the
relevant cancer and jurisdiction. Logistic regression was used to explore whether PCP characteristics
or system differences in each jurisdiction were correlated with readiness to investigate.
Results
Four of five vignettes showed a statistically significant correlation (p<0.05 or better) between
readiness to investigate or refer to secondary care at the first phase of each vignette and cancer
survival rates for that jurisdiction. No consistent associations were found between readiness to
investigate and selected PCP demographics, practice or health system variables.
Conclusions
We demonstrate a correlation between the readiness of PCPs to investigate symptoms indicative of
cancer and cancer survival rates, one of the first possible explanations for the variation in cancer
survival between ICBP countries. No specific health system features consistently explained these
findings. Some jurisdictions may consider lowering thresholds for PCPs to investigate for cancer –
either directly, or by specialist referral to improve outcomes.
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ARTICLE SUMMARY
Strengths and limitations of this study:
• A novel, large and logistically complicated study using a validated survey
• Data was analysed from 2795 PCPs across 11 jurisdictions
• Response rates were sub-optimal and respondents were not totally representative of the
PCPs in all jurisdictions
• It is difficult to assess the effect of these limitations on the interpretation of results but
sensitivity analyses and the literature suggest it would not be large
Funding: This work was supported by Canadian Partnership Against Cancer; Cancer Care Manitoba;
Cancer Care Ontario; Cancer Council Victoria; Cancer Institute New South Wales; Danish Health and
Medicines Authority; Danish Cancer Society; Department of Health, England; Department of Health,
Victoria; Northern Ireland Cancer Registry; The Public Health Agency, Northern Ireland; Norwegian
Directorate of Health; South Wales Cancer Network; Swedish Association for Local Authorities and
Regions; Tenovus; British Columbia Cancer Agency; Public Health Wales and the Welsh Government
Competing Interests: WH is the clinical lead for the ongoing revision of the NICE 2005 guidance on
investigation of possible cancer, CG27. His contribution to this article is in a personal capacity, and is
not to be interpreted as representing the view of the Guideline Development Group, or of NICE
itself. The authors declared no conflicts of interest.
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INTRODUCTION
Significant differences in cancer survival have been demonstrated between countries with similar
health systems[1]. Poor outcomes may arise from late presentation, diagnostic delays and treatment
differences, or combinations of these[1-6]. Lengthened time between first presentation to medical
care and diagnosis (the diagnostic interval)[7] are associated with poorer outcomes[8-10]. Detailed
knowledge about how the diagnostic interval is managed in health systems may explain these
differences in survival.
The International Cancer Benchmarking Partnership (ICBP) is a collaboration across six countries
(Australia, Canada, Denmark, Norway, Sweden and the United Kingdom) and 12 jurisdictions of
comparable wealth and universal access to health care, established to examine international
differences in cancer outcomes and identify possible causes. Cancer survival is higher in Australia,
Canada, and Sweden, intermediate in Norway and lower in Denmark and the UK [1]. Differences
between the countries in the proportion diagnosed with the cancer at an early stage, suggest that
differences in the period prior to diagnosis contribute to the international variation in cancer
survival, along with other potential factors, such as access to treatment and the quality of
treatments[2-6].
Public awareness of signs and symptoms and beliefs about cancer appear to be quite similar across
jurisdictions and are therefore unlikely to account for much of the variation seen between countries.
However, differences in perceived barriers to seeing the GP have been reported[11]. Differences in
the way cancer symptoms are recognised and managed in primary care may contribute to the
observed survival differences. For example, European inter-country differences in clinical diagnostic
practice have been reported for gastrointestinal disorders[12]. A stronger ‘gatekeeper’ role –
whereby primary care practitioners (PCPs) manage entry to specialist care and investigations – is
also associated with worse cancer survival[13]. This ‘gatekeeper issue’ is exemplified by the finding
that higher rates of endoscopy referrals within individual UK general practices are associated with a
lower mortality from oesophago-gastric cancer[14].
The aims of this study were to describe the readiness of PCPs to consider investigation or referral for
symptoms possibly indicative of cancer, and to relate this to international differences in primary care
structure and practice. Our hypothesis was that there is a positive correlation between the
proportion of PCPs who would investigate a specific symptom set for cancer and survival rates (for
the given cancer) across jurisdictions. We also investigated whether the readiness of PCPs to
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investigate these cases could be explained by differences in primary care structure or PCP
characteristics.
METHODS
We conducted an international vignette survey amongst a sample of PCPs in participating
jurisdictions.
Survey development
We developed an online survey of PCPs exploring differences in their behaviours, attitudes,
knowledge and skills relating to cancer diagnosis. This was validated, initially in England and then in
all jurisdictions. This process has been described elsewhere[15].
Structure
The survey was in two parts: direct questions consisting of demographic details of the respondents
and questions relating to service provision, access to investigations and waiting times following
secondary care referrals; vignettes on management choices for a patient presenting with symptoms
suggestive of either lung (two vignettes), colorectal (two vignettes) or ovarian cancer (one vignette).
Respondents were randomly presented with two vignettes (of different cancer sites), and were
asked to complete the survey relating to their own practice rather than perceived best practice.
Respondents were aware the survey was part of a study linked to cancer.
Each vignette had two or three phases: phase one represented the first patient presentation; phases
two and three represented subsequent visits, where the patient’s symptoms had developed; each
phase had a pre-defined positive predictive value (PPV) for the cancer based on previous work to
ensure a defined increase in cancer risk at each phase (Table 1)[16-18]. Respondents were not
informed of the PPV for each set of symptoms and signs in the survey. However specifying the PPVs
in the analysis at each phase enabled a comparison of the readiness to act both within vignettes and
between vignettes of the same cancer. The response of primary interest was opting to identify
possible cancer either by referral to secondary care or by undertaking a definitive diagnostic
investigation in primary care: requesting either of these ended that vignette. The definitive tests
were determined by an expert panel and included chest Xray or Lung CT for lung vignettes,
colonoscopy or abdominal CT for colorectal vignettes, abdominal CT or abdominal or trans-vaginal
ultrasound for the ovarian vignette[15].
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The final survey
The survey was completed in 11 jurisdictions: New South Wales and Victoria (Australia), British
Columbia, Manitoba, Ontario (Canada), England, Northern Ireland, Wales (United Kingdom),
Denmark, Norway, Sweden.
Each jurisdiction decided on a method of sampling and approach to potential participants (by post or
email), depending on local conditions and the availability of databases with PCP contact details and
participation incentives (Supplementary Table 1). All surveys were completed online.
Participants
Participants were PCPs working predominantly in clinical practice, including locums and those
working in ‘out-of-hours’ services: retired PCPs, and those in training were not eligible. Considering
all jurisdictions, the online surveys were completed between May 2012 and July 2013; the start
dates and end dates in each jurisdiction varied.
The representativeness of each sample was assessed by comparing gender, age and place of
qualification between respondents and data for all PCPs in each jurisdiction.
Sample size
Each jurisdiction aimed to recruit at least 200 respondents. This provided a 95% confidence interval
(CI) +/- 7% for equally distributed responses (e.g. 50% responding ‘yes’), and +/- 6% CI for less
equally distributed responses (e.g. 20% responding ‘yes’).
Analysis
Direct questions, relating to demographics and primary care structure factors, were analysed using
descriptive statistics. The questions relating to average waiting times for tests and results were
analysed by estimating the mean time from ordering a test to receiving the results by using the mid-
point of each waiting time category.
Analysis of the vignettes was undertaken in two stages. Our hypothesis was explored by comparing
the cumulative proportion of PCPs opting to investigate or refer at each phase for each vignette
using 1 year survival rates for the relevant cancer.
Linear correlations were estimated between the proportions opting to investigate at each phase and
survival rates.
Weighted Regression
When comparing between jurisdictions, weighted linear regression was used to adjust for different
sample sizes in each jurisdiction, based on the total number of respondents for each vignette. A
regression model was fitted for each phase and each vignette using 1 year survival as the outcome
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with the number of PCPs acting at each phase as a single explanatory variable. The weights were the
inverse of the variance of the proportion at a given phase for each jurisdiction. No weighted
regression models were possible for jurisdictions where all PCPs had opted to investigate at a given
phase.
Logistic Regression – Multilevel model
Weighted regression did not allow us to explore if individual PCP characteristics and access to tests
(within each jurisdiction) were associated with opting to investigate. Therefore, in the second stage
of the analysis, we fitted separate multilevel logistic regression models using opting to investigate as
the outcome and estimated the association with (a) PCP characteristics, (b) access to tests, (c)
jurisdiction level survival (1 and conditional 5 year) as reported by Coleman and colleagues [1] and
(d) a full model including PCP characteristics and access to tests. This last model only included those
variables significantly associated in models (a) and (b) to reduce the chances of identifying spurious
associations.
We identified variables that might influence opting to investigate in models (a) and (b) as well as the
expected direction of effect (Supplementary Table 2). As with the weighted regression, analyses
were performed by vignette as explanatory variables were different for each cancer. These variables
are not independent and therefore some basic model selection (based on statistical significant
associations p-value <0.05) was used to determine the choice of variables included in model (c).
Sensitivity analyses
Previous studies comparing survival rates between England or the UK to other countries suggested
that later diagnosis could be a factor contributing to poorer outcomes: thus, opting to investigate or
refer later in the process of clinical presentation would contribute to the delay in diagnosis in poorer
performing jurisdictions[1,19]. Both 1 year survival and 5 year survival conditional on surviving at
least 1 year (conditional 5 year survival) reflect a longer diagnostic interval due to delay in primary
care, but neither are a perfect measure of this[19]. We chose 1 year survival as the primary outcome
measure as we anticipated that it more directly reflects activity in primary care. We then undertook
sensitivity analysis using conditional 5 year survival to check that our findings were also confirmed
using this outcome.
Denmark has substantially changed its primary care referral procedures since the latest reported
comparative survival figures[20,21]. This change in procedures was apparent in the results with
Denmark appearing as an outlier in vignettes 3 and 4 related to the diagnosis of colorectal cancer;
analyses of these two vignettes were repeated excluding Denmark.
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Australia oversampled rural PCPs to ensure the views of this minority were adequately represented.
A post hoc sensitivity analysis was undertaken to address this: we formed a data set with a sample of
rural PCPs so that this was representative of the rural/urban split in Australia and compared these
with the results of the whole data set.
Governance
At all stages the methodology, sampling and analysis were discussed with four separate working
groups: the module lead of each jurisdiction, the Programme Board overseeing the whole ICBP
programme, an academic steering group comprising the module chair and three academic PCPs with
an interest in cancer (PWR, GR, WH, PV) and an academic reference group comprising primary care
academics from within and outside ICBP jurisdictions.
RESULTS
The online survey was completed by 2795 PCPs. Almost all jurisdictions received at least 200
responses; only the Northern Ireland response (the smallest total population) was substantially
below this target. Crude response rates (most jurisdictions stopped the survey when the sample size
was reached) varied between jurisdictions from 5.5% (England) to 45.6% (Manitoba) (Appendix
Table 1).
Characteristics of respondents are summarised in Table 2. There were significantly more female
PCPs in the samples from Victoria, Ontario and British Columbia and fewer from Norway, when
compared with their national data. The samples from England, Wales, Northern Ireland, New South
Wales, Victoria, Sweden, Norway and Ontario had fewer doctors who had qualified outside the
country and Manitoba had more (for Canadian provinces and Australian states this meant training
outside Canada and Australia respectively). Respondents from England and Norway were older
whereas respondents from New South Wales and all Canadian provinces were younger compared
with national data.
Vignette Results
In four of the five vignettes there was a statistically significant correlation (p<0.05) between opting
to investigate for cancer in a jurisdiction at phase one and the cancer survival in that jurisdiction
(Figure 1). Only phase one results are presented; nearly all PCPs had taken action to refer or
investigate for a potential diagnosis of cancer by the end of phase 2.
Vignette 1 (lung cancer) was the only vignette that did not show any statistically significant
correlations. In this vignette, the estimated positive predictive value (PPV) for lung cancer for the
symptoms presented at phase one was 0.9% (although this was not explicitly presented in the
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vignette) and yet the range of respondents opting to investigate at this phase between jurisdictions
was 40% to 80% (Table 1). The estimated PPV for lung cancer in phase one of vignette 2 was higher
at 3.6% and yet the range of respondents opting to investigate at this phase was 4% to 52%.
The lung and ovarian cancer vignettes were usually completed by the use of a test (chest X-Ray for
lung cancer, ultrasound for ovarian cancer) rather than by specialist referral. In contrast, more than
half of the colorectal vignettes were completed by referral.
Consistent with the correlation results, statistically significant associations were found using
weighted regression between the one year survival and readiness to investigate at phase one for
vignettes 2, 3, 4 (after Denmark was excluded) and 5. For the sensitivity analysis based on the
conditional 5 year survival, this association was found at phase one for vignettes 2, 3, and 4 (after
Denmark was excluded) (Table 1).
Logistic Regression analysis
No factors (PCP characteristics, access to tests or length of time from ordering test to receiving
results) showed a consistent association with the readiness to investigate. The only two PCP
characteristics associated with the outcome were that doctors who trained outside their jurisdiction
were more likely to refer or investigate cases earlier in vignettes 3 and 4 (both colorectal) and older
doctors were more likely to refer or investigate cases earlier in vignette 4. The former association
was investigated further using data from Manitoba (the only jurisdiction to have more doctors
trained outside of the jurisdiction); within this dataset there was no association found between
place of training and readiness to investigate. The latter association was no longer statistically
significant when excluding Denmark as part of the sensitivity analysis; while training outside was still
significant (data not shown).
Similarly, adjusting for rural/urban split amongst Australian PCPs did not significantly affect the
results.
Direct questions – access to diagnostics and secondary care advice
Similarities and differences in primary care system factors are reported between jurisdictions.
Reported direct access, to blood tests for cancer diagnosis, plain X-rays and ultrasound was greater
than 70% across all jurisdictions (Table 3). Reported access to other tests was variable: direct access
to endoscopy was less common in Canada. The United Kingdom and Denmark had comparatively
low levels of direct access to CT and MRI scanning.
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With the exception of plain X-rays, the total wait from request to receipt of report for imaging or
endoscopy was reported to be over four weeks in most jurisdictions and over 12 weeks in some.
Total wait between a referral for a suspected cancer and a patient’s first specialist appointment was
between two and three weeks for all jurisdictions (Table 4). Most PCPs reported they could expedite
access to tests if cancer was suspected. With the exception of the United Kingdom, most PCPs
reported ready access to secondary care advice about investigation or referral of suspected cancer
from a specialist (Table 5).
While there was variation across jurisdictions in terms of access to diagnostics and secondary care
advice, none of these factors were associated with PCP readiness to act.
DISCUSSION
Principal findings
Using an online survey in 11 jurisdictions, we have demonstrated a correlation which suggests a
relationship between the readiness of PCPs to investigate or refer for suspected cancer and cancer
survival in each jurisdiction. This is the first time that readiness to investigate for cancer – either
directly or by referral to secondary care – has been shown to correlate with cancer survival. Evidence
suggests that variations between health care systems have an impact on health outcomes[22].
There is significant variation between jurisdictions in the access that PCPs have to diagnostic tests.
Whether greater access to tests improves outcomes depends on the sensitivity of the test and how
the waiting time for test results compares with the waiting time if a referral is made. PCPs may not
be aware of the fastest way to diagnose cancer: referral or primary care investigation. Our data
indicate significantly long waits in some jurisdictions for the results of tests undertaken in primary
care. However access to tests was not associated with readiness to investigate or refer. Further
research is required in this complex area.
Strengths and weaknesses
This was a novel, large, logistically complex survey using a validated tool in 11 jurisdictions with
primary care based health systems. Once a respondent engaged in the online survey the proportion
who went on to complete it was high. The vignettes had face validity; they directly reflected clinical
practice and were universally applicable[15]. Moreover, since the study was completed, the
vignettes have been adopted as part of a GP education programme in the UK in light of their
applicability to primary care. There is evidence that using vignettes in a survey correlates well to
clinical practice[23]. Vignettes have also been used recently in a similar context[24]. While surveys
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using hypothetical vignettes are not ideal we chose vignette based surveys as a cost effective way to
maintain consistency across all jurisdictions.
The poor response rates in some jurisdictions and the lack of representativeness of the respondents
in several jurisdictions (based on demographic data) are weaknesses. It is difficult to assess whether
and by how much these two factors would affect the interpretation of the results. Two jurisdictions
achieved a response rate over 25%; in other jurisdictions response rates ranged from 5.5% to 18.7%.
A significant obstacle to achieving better response rates in some jurisdictions was limited availability
of comprehensive and up to date email addresses for PCPs. The response rates achieved are broadly
in line with lower response rates for online surveys generally[25]. Furthermore, response rates in
physician surveys have been declining in recent years[26].
Those responding were not wholly representative of their local PCP population, but the differences
in gender and country of qualification were bidirectional. It is unlikely that selection bias will operate
in different directions in each country i.e. that we should have the highest investigating or referring
doctors in some and the lowest in others. If we hypothesized that those participating were the very
best and most interested GPs, they would be more likely to investigate or refer earlier, irrespective
of jurisdiction, and so these results would be likely to underestimate true differences between
jurisdictions.
In jurisdictions where respondents were less representative of the local PCP population, respondents
were in general more likely to be women, to have qualified in that country and to be younger.
Although training outside the country was associated with opting to act earlier in the colorectal
vignettes, sensitivity analysis using Manitoba data suggested this is unlikely to have substantially
affected overall results. A systematic review of studies of primary care referrals suggested that less
than 10% of the observed variation in referral rates could be accounted for by practice and GP
characteristics[27]. It is therefore unlikely that the minor unrepresentativeness of some samples has
materially altered the findings.
Earlier diagnosis could lead to perceived better outcomes through two mechanisms: earlier stage at
diagnosis or lead time bias. Our correlations were significant for both one year and conditional five
year survival, suggesting that lead time bias is less of an issue.
The vignettes all described hypothetical patients with symptoms which have been shown to be
significantly associated with the given cancer.
The survey was conducted in 2012/13 and therefore reflects clinical practice at this time. The latest
comparative survival data for the three cancers in participating jurisdictions is from 2007. The
jurisdictions had no major changes to cancer diagnostic pathways during this time, with the
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exception of Denmark, which in 2009 introduced significant reforms to improve diagnostic access for
PCPs. Consequently, Denmark was often an outlier in the analyses: sensitivity analyses including and
excluding Denmark strengthened our findings.
Comparison with other research
An analysis of the health systems in the ICBP jurisdictions showed few significant differences[28].
Poorer outcomes have been correlated with the strength of the ‘gatekeeping’ role of PCPs in
different health systems[13]: our findings broadly support this. Denmark has deliberately
reorganised cancer diagnostic services to reduce the gatekeeping role by enabling PCPs to undertake
timely investigation of patients with alarm well as vague symptoms[21]Our results suggest that
Danish PCPs now behave more like PCPs in jurisdictions with better cancer outcomes. Gatekeeping
may encourage PCPs to over-use other diagnostic strategies, such as the ‘test of time’[29] which
could contribute to longer diagnostic intervals. Other possible reasons to account for our results
include PCPs’ knowledge and PCPs’ relationships with specialists.
Implications
In this study PCPs opted to investigate at low levels of risk, possibly reflecting bias because this was a
survey relating to cancer. However, recent work suggests that patients prefer to be investigated
when cancer is a possibility, even at low risk levels[23]. If risk thresholds at which symptoms are
investigated were to be lowered, health economic considerations would need to be taken into
account. The use of risk prediction tools[30,31] may aid PCPs in this respect. Our findings also
suggested that PCPs were not necessarily aware of the positive predictive values of groups of
symptoms. Across all jurisdictions, the speed of referral was inversely related to the PPV for lung
cancer in the two lung vignettes. However, these counterintuitive responses are consistent with
referral guidelines in some of the jurisdictions. Variation in readiness to investigate or refer to
secondary care by PCPs for patients with a differential diagnosis of cancer might explain some of the
variation in cancer survival between ICBP jurisdictions. It is unlikely that a single solution to this
variation will work across all jurisdictions. However, solutions are likely to include initiatives that
empower PCPs toward earlier investigation of cancer and to reduce the barriers that inhibit
specialist referral. Such changes are likely to require changes in local policy leading to increased
access to investigations and diagnostics, more efficient referral pathways and the re-drafting of local
referral guidelines to facilitate referral at risk levels below those currently mandated.
Future research
Future research should investigate which factors do affect the readiness of a PCP to investigate or
refer a patient. While not explored in detail in this study, a range of system factors could be
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influencing how PCPs respond to symptomatic patients; areas for further investigation could include
further research to confirm these findings and additional research to investigate the influence of
clinical guidelines, the comprehensiveness of primary care health systems in each country,
conversion rates of those investigated or referred who are diagnosed with cancer and the nature of
the relationship between primary and secondary care.
Author Contribution Statement: PWR, GR, RPS, SSA, AB, MD, EG, NH, RDN, MP, JS, GK, BST, HT, JY,
WH and the ICBP Module 3 Working Group contributed to the manuscript. PWR wrote the original
manuscript. PWR, GR, RPS, SSA, AB, MD, EG, NH, RDN, MP, JS, GK, BST, HT, JY, WH and the ICBP
Module 3 Working Group contributed to the study design, data collection, data interpretation,
review process; reading and considering the analysis, being involved in discussion and contributing
variously to the iterative writing and commenting process. Every author takes responsibility for the
entire content of the manuscript.
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APPENDIX A: MODULE 3 WORKING GROUP
Andriana Barisic, Research Associate, Department of Prevention and Cancer Control, Cancer Care
Ontario, 620 University Avenue, Toronto, Ontario, M5G 2L7, Canada
Martin Dawes, Head, Department of Family Practice, David Strangway Building, University of British
Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada
Diana Dawes, Research Associate, Department of Family Practice, David Strangway Building,
University of British Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3,
Canada
Mark Elwood, Vice-President, Family and Community Oncology, BC Cancer Agency; Clinical
Professor, School of Population and Public Health, UBC; Honorary Professor, Department of
Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
Kirsty Forsdike, Senior Research Assistant, Department of General Practice, 200 Berkeley Street,
Carlton Victoria 3053, Australia
Eva Grunfeld, Director, Knowledge Translation Research Network Health Services Research Program,
Ontario Institute for Cancer Research; Professor and Vice Chair Research Department of Family and
Community Medicine, University of Toronto, 500 University Avenue, Toronto, Ontario, M5G 1V7,
Canada
Nigel Hart, Clinical Senior Lecturer, School of Medicine, Dentistry and Biomedical Sciences - Centre
for Public Health, Queen's University Belfast 2013, University Road Belfast, BT7 1NN, United
Kingdom
Breann Hawryluk, Project Planning Coordinator, Department of Patient Navigation, Cancer Care
Manitoba, 675 McDermot Street, Winnipeg, Manitoba, Canada
Gerald Konrad, Associate Professor, Department of Family Medicine, University of Manitoba 5-400
Tache Avenue, Winnipeg, Manitoba, Canada
Anne Kari Knudsen, Administrative leader, Department of Cancer Research and Molecular Medicine,
Norwegian University of Science and Technology, 7489 Trondheim
Magdalena Lagerlund, Department of Learning, Informatics, Management and Ethics, Karolinska
Institute, Berzelius väg 3, Stockholm 171 77, Sweden
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Claire McAulay, Research Officer, Public Health, School of Public Health, D02-QE11 Research
Institute for Mothers and Infants, University of Sydney NSW 2006 Australia
Jin Mou, Postdoctoral Fellow, Department of Family Practice, Research Office, Department of Family
Practice, David Strangway Building, University of British Columbia, 5950 University Boulevard,
Vancouver, British Columbia, V6T 1Z3, Canada
Richard D Neal, Professor of Primary Care Medicine and Director, North Wales Centre for Primary
Care Research, Bangor University, Gwenfro Units 4-8, Wrexham Technology Park, Wrexham, LL13
7YP, United Kingdom
Marie Pirotta, Primary Health Care Research Evaluation and Development Senior Research Fellow,
Department of General Practice, 200 Berkeley Street, Carlton Victoria 3053, Australia
Jeffrey Sisler, Associate Dean, Division of Continuing Professional Development and Professor,
Department of Family Medicine, University of Manitoba, 727 McDermot Avenue, Winnipeg,
Manitoba, R3E 3P5, Canada
Berit Skjødeberg Toftegaard, PhD Research Fellow, Research Unit for General Practice, Department
of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C, Denmark
Hans Thulesius, Associate Professor, Lund University, Box 117, SE-221 00 Lund, Sweden
Peter Vedsted, Professor, Research Unit for General Practice, Department of Public Health, Aarhus
University, Bartholins Allé 2, 8000 Aarhus C, Denmark
David Weller, James Mackenzie Professor of General Practice, Centre for Population Health Sciences,
University of Edinburgh, Doorway 1, Medical Quad Teviot Place, Edinburgh, EH8 9DX, United
Kingdom
Jane Young, Professor in Cancer Epidemiology, Public Health, School of Public Health, D02-QE11
Research Institute for Mothers and Infants, The University of Sydney, 2006, Australia
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ACKNOWLEDGEMENTS
Kate Aldersey, Martine Bomb, Catherine Foot, Brad Groves and Samantha Harrison of Cancer
Research UK for managing the ICBP programme. John Archibald at Sigmer Technologies Ltd for
hosting the online survey. Alice Fuller for help with data management. We would also like to
acknowledge and thank our ICBP clinical committee members and working group members in each
jurisdiction who were not part of the central team, but who contributed to the review of our results
and this paper.
Programme Board: Ole Andersen (Danish Health and Medicines Authority, Copenhagen, Denmark),
Søren Brostrøm (Danish Health and Medicines Authority, Copenhagen, Denmark), Heather Bryant
(Canadian Partnership Against Cancer, Toronto, Canada), David Currow (Cancer Institute New South
Wales, Sydney, Australia), Dhali Dhaliwal (Cancer Care Manitoba, Winnipeg, Canada), Anna Gavin
(Northern Ireland Cancer Registry, Queens University, Belfast, UK), Gunilla Gunnarsson (Swedish
Association of Local Authorities and Regions, Stockholm, Sweden), Jane Hanson (Welsh Cancer
National Specialist Advisory Group, Public Health Wales, Cardiff, UK), Todd Harper (Cancer Council
Victoria, Carlton, Australia), Stein Kaasa (University Hospital of Trondheim, Trondheim, Norway),
Nicola Quin (Cancer Council Victoria, Carlton, Australia), Linda Rabeneck (Cancer Care Ontario,
Toronto, Canada), Michael A Richards (Care Quality Commission, London, UK), Michael Sherar
(Cancer Care Ontario, Toronto, Canada), Robert Thomas (Department of Health Victoria, Melbourne,
Australia).
Academic Reference Group:
Jon Emery, Professor of Primary Care Cancer Research, University of Melbourne and Clinical
Professor of General Practice, University of Western Australia, Australia
Niek de Wit, Professor of General Practice, Julius Centre for Health Sciences and Primary Care,
University Medical Centre, Utrecht, Netherlands
Roger Jones, Editor, British Journal of General Practice and Emeritus Professor of General Practice,
King's College, London, United Kingdom
Jean Muris, Associate Professor in Family Medicine, Maastricht University, Netherlands
Frede Olesen, Professor, Research Unit for General Practice, Department of Public Health, University
of Aarhus, Denmark
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Table 1: Summary of the vignettes
Vignette
Cancer
Patient details
Management options Phase 1 Phase 2 Correlation between survival
and referral or test at phase 1
(weighted regression analysis)
Definitive
actions
Non-definitive actions PPV Refer /
Test (%) *
PPV Refer /
Test (%)*
1 year
survival
P value
Conditional 5 year
survival
P value
1 Lung Phase 1 68-year old female, ex-smoker with persistent cough for 3
weeks but no other symptoms, taking ramipril for
hypertension. Ear, throat and chest exams were normal.
Secondary care
referral
Chest x-ray
Chest CT
• Antibiotics
• Oral steroids
• Anti-tussive medicines
• Stop ramipril
• Advise visit to pharmacy to
try remedies there
• Tell her that no action is
needed at this stage
0.9 40-80 3·9 95-100 0.654 0.647
Phase 2 Patient returns after another 3 weeks, saying cough has
persisted and now there are streaks of blood in the sputum.
No weight loss, but a chest examination reveals some
crepitations at the left base. Any tests previously undertaken
were normal.
0.357
(excluding
Denmark)
0.911
(excluding
Denmark)
Phase 3 Patient returns with ongoing symptoms and you decide to
order a chest X-ray. The report says there is mild
cardiomegaly but the lung fields are clear.
2 Lung Phase 1 62 years old man with COPD, a heavy smoker for over 40
years. He presented with respiratory symptoms.
Secondary care
referral
Chest x-ray
Chest CT
• Advise increased use of
salbutamol inhaler
• Antibiotics
• Oral steroids
• Antibiotics and add new
inhaler- steroid or
salmeterol
• Anti-tussive medicines
• Advise visit to pharmacy to
try remedies there
• Tell him that no action is
needed at this stage
3.6 5-50 >10·0 87-100 <0.001 <0.001
Phase 2 Patient returns in 3 weeks, complains of constant ache in left
shoulder. Patient attributes pain to persistent cough; he is
also producing grey coloured sputum in larger quantities
than usual, but no other chest symptoms. No weight loss. On
exam he has still has a bilateral upper lobe wheeze and some
crepitations at the left base. Examination of his shoulder is
normal.
<0.001
(excluding
Denmark)
<0.001
(excluding
Denmark)
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Vignette
Cancer
Patient details
Management options Phase 1 Phase 2 Correlation between survival
and referral or test at phase 1
(weighted regression analysis)
Definitive
actions
Non-definitive actions PPV Refer /
Test (%) *
PPV Refer /
Test (%)*
1 year
survival
P value
Conditional 5 year
survival
P value
3 Colorectal Phase 1 43 year old woman with IBS for more than 10 years, but the
IBS has got worse recently. She has abdominal pain every
day, unchanged bowel habit and no other symptoms. She
has no family history of cancer.
Secondary care
referral
Colonoscopy
Abdominal CT
• Prescribe medication for
IBS
• Give dietary advice
• Offer psychological
therapies (counselling and
CBT)
• Tell her that no action is
needed at this stage
0.7 5-45 1.2 48-89 0.014
0.025
Phase 2 The patient returns to see you. Her recent blood test has
returned a haemoglobin level of 10.5g/dl.
0.003
(excluding
Denmark)
0.002
(excluding
Denmark)
4** Colorectal Phase 1 68 year old man with no relevant medical history. He has
experienced loose stools twice a day, most days for over 4
weeks. He has no other symptoms. Examination incl. rectal
exam was normal.
Secondary care
referral
Colonoscopy
Abdominal CT
• Offer medication e.g.
loperamide, antispasmodic,
analgesia.
• Advice on diet
• Tell him that no action is
needed at this stage
0.9 20-40 1.9 77-89 0.071
0.093
Phase 2 Any tests selected are negative. Patient returns 2 weeks
later, describing that the diarrhoea remains much the same
but he now also has intermittent sharp abdominal pain.
Abdominal and PR examinations are normal.
0.004
(excluding
Denmark)
0.001
(excluding
Denmark)
Phase 3 All tests are negative. A further two weeks later patient
describes two brief episodes of rectal bleeding (bright red)
two days apart.
5** Ovarian Phase 1 53 year old woman whose last period was 6 months ago. She
had experienced abdominal pain for the last 3 weeks. She
has had no other symptoms and the same sexual partner for
20 years.
Secondary care
referral
Abdominal
ultrasound
Pelvic CT
• Prescribe analgesia
• Prescribe anti-spasmodic
• Undertake investigations
now
• Tell her that no action is
needed at this stage
0.3 40-75 0.7 68-90 0·007
0.610
Phase 2 All investigations to date have been normal. The patient
presents one month later with urinary frequency. She says
the abdominal pain is still present but comes less often.
Abdominal examination is normal. A urine dipstick for blood,
protein, nitrite, white cells and sugar is negative.
0.009
(excluding
Denmark)
0.744
(excluding
Denmark)
Phase 3 Patient returns 6 weeks later saying pain is worse, she is
passing urine every 3 hours, day and night and has noticed
that her abdomen seems swollen. You examine her abdomen
and it does looks distended but you cannot feel any other
abnormality.
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* Range of respondent who completed the vignette at this stage by referral or undertaking a definitive diagnostic test.
** Stage 3 results not reported as nearly 100% of respondents referred or undertook definitive test by this stage
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Table 2: Representativeness of samples: comparison of respondent characteristics with whole jurisdiction data
Sub-categories ENG WA NI VIC NSW SWE NO DK ONT MAN BC
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al*
Su
rve
y
p v
alu
e
Na
tion
al*
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
N 35527 251 2015 218 1178 130 20360 189 20360 256 5467 199 5373 230 3590 255 12296 610 1323 228 5833 229
(%)
(%) (%) (%) (%) (%) (%) (%) (%) (%) (%)
Male 52.9 41.8
0.1
98
56.0 61.0 0.1
98
0
55.0 56.0 0.8
01
8
61.0 53.0 0.0
03
4
61.0 56.0 0.0
83
9
54.0 53.0 0.8
38
4
58.3 66.5 0.0
13
2
56.4 57.3 0.7
90
2
57.6 51.6 0.0
03
8
62.6 59.2 0.3
32
8
60.6
45.0
<0
.00
01
Female 47.1 58.2 44.0 39.0 45.0 44.0 39.0 47.0 39.0 44.0 46.0 47.0 41.7 33.5 43.6 42.7 42.4 48.4 37.4 40.8 39.4
55.0
Place of
Qualification
Within
jurisdiction
≠77.4 91.2
0.0
00
4
82.0 89.0
0.0
09
6
≠77.4 100.0
<0
.00
01
66.0 74.0
0.0
02
9
66.0 74.0
0.0
08
6
2010:
77.0
89.0
<0
.00
01
61.6 74.8
<0
.00
01
not
available
98.4
74.6 90.1 <
0.0
00
1
53.1 48.7
<0
.00
01
not
available
72.9
Outside
jurisdiction
≠22.6
8.8
18.0 11.0
≠22.6
0.0
34.0
26.0
34.0 26.0
2010:
23.0
11.0
38.4 25.2
1.6
24.7 9.9
46.9 51.3
27.1
Age Bands Under 30 1.0 0.4
0.0
13
1.0 0.0
0.1
27
7
0.1 0.80
0.4
72
<35:
7.0
6.0
0.0
86
4
<35:
7.0
10.0
0.0
46
9
<40®:
7.0
33.0
<0
.00
01
4.6 0.0
<0
.00
01
<34:
0.11
0.4
0.6
52
5
1.7 14.0
<0
.00
01
4.7 7.9
<0
.00
01
<30
1.2 17.9
<0
.00
01
30-44 42.0 14.7 39.0 39.9 40.0 36.9 35-
44®:
20.0
24.0 35-44®:
20.0
24.0 35-
44®:
10.0
9.0 43.3 30.9 35-44:
20.1
18.8 32.2 26.1 31-45®:
33.2
37.3 30-39®:
18.9
21.0
45-54 34.4 13.2 37.0 39.4 35.0 39.2 31.0 36.0 31.0 28.0 28.0 25.0 21.2 19.6 29.2 29.0 28.0 27.8 46-55®:
30.1
33.8 40-49®:
24.4 21.8
55-64 18.4 12.4 20.0 20.2 23.0 20.8 55+:
42.0
34.0 55+®:
42.0
38.0 43.0 26.0 25.5 40.9 40.8 40.4 24.7 23.6 56-64®:
20.6
17.1 50-59®:
29.9 26.6
65+ 4.0 17.9 3.0 0.5 1.9 2.30 12.0 8.0 5.5 8.7 9.6 11.4 13.4 8.5 9.4 3.95 60-69®:
20.7 10.5
unknown 0.1 17.9
70-79®:
4.4 1.3
80+®:
0.6 0.9
Key
®Where age groups sub-groups differ they are marked in bold and italic
*using Australian National statistics
≠ UK naFonal figures used
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Table 3: Direct access* to investigations (%)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
Cancer diagnosis blood tests #
Blood tests 98.0 99.5 81.7 69.3 80.7 89.8 70.9 75.8 94.0 89.0 75.7
95%CI 95.2 to 99.3 96.6 to 100 75.9 to 86.3 62.8 to 75.1 77.2 to 83.7 85.3 to 93.1 64.5 to 76.6 69.1 to 81.4 90.1 to 96.5 81.2 to 93.9 69.3 to 81.1
Endoscopy
Upper GI endoscopy 26.0 66.1 7.4 13.7 19.5 56.5 18.0 46.2 68.1 68.5 66.1
95%CI 20.8 to 31.9 58.9 to 72.8 4.5 to 11.8 9.6 to 18.9 16.4 to 22.9 50.1 to 62.6 13.2 to 23.5 38.9 to 53.2 61.9 to 73.8 59.1 to 77.2 59.3 to 72.2
Flexi sig 17.7 34.9 13.1 13.2 17.7 54.9 16.2 34.2 40.6 14.8 32.3
95%CI 13.3 to 23.1 28.2 to 42.2 9.2 to 18.3 9.2 to 18.4 14.7 to 21.0 48.6 to 61.1 11.7 to 21.6 27.8 to 41.5 34.6 to 47.0 8.9 to 23.0 26.1 to 38.8
Colonoscopy 26.4 61.9 7.9 13.2 22.4 52.5 17.1 45.2 33.1 19.8 22.0
95%CI 21.1 to 32.3 54.5 to 68.8 4.9 to 12.3 9.2 to 18.4 19.1 to 26.0 46.2 to 58.8 12.5 to 22.6 37.9 to 52.2 27.4 to 39.3 13.3 to 29.2 16.8 to 28.2
Imaging
Xray Whole body^ 99.2 100.0 96.1 92.5 98.0 92.2 74.3 86.4 82.5 89.9 87.6
95%CI 96.9 to 99.9 97.5 to 100 92.4 to 98.1 88.1 to 95.5 96.4 to 98.9 88.0 to 95.0 68.1 to 79.8 80.6 to 90.7 77.1 to 86.9 82.3 to 94.6 82.3 to 91.5
CT Whole body 99.6 100.0 92.6 86·4 95.1 22.0 73.5 84.3 21.5 27.5 46.3
95%CI 97.5 to 100 97.5 to 100 88.2 to 95.5 81.1 to 90.4 93 to 96.7 17.1 to 27.7 67.2 to 79.0 78.4 to 89.0 16.7 to 27.2 19.6 to 37.0 39.6 to 53.2
MRI Whole body 44.9 54.0 62.0 74·6 91.6 16.9 70.4 68.2 19.9 11.0 31.2
95%CI 38.7 to 51.2 46.6 to 61.2 55.4 to 68.3 68.3 to 80.0 89 to 93.6 12.6 to 22.2 64.0 to 76.2 61.1 to 74.5 15.3 to 25.5 6.1 to 18.8 25.2 to 37.9
Ultrasound Whole body 98.0 98.9 93.0 84·2 95.4 78.2 70.9 82.3 78.1 79.8 71.1
95%CI 95.2 to 99.3 95.8 to 99.8 88.7 to 95.8 78.7 to 88.6 93.4 to 96.9 72.4 to 82.9 64.5 to 76.6 76.1 to 87.2 72.4 to 82.9 70.8 to 86.7 64.5 to 76.9
* Direct access: PCP can order the test without specific referral to secondary care
# Survey did not define which specific tests
^ Access to all individual body parts
Note: Exact 95%CI calculated for these figures
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Table 4: Average wait times for tests and results (weeks)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
X-ray
Test 0.56 0.57 0.56 0.55 0.54 0.95 1.37 1.43 0.79 0.91 0.82
Result 0.50 0.51 0.71 0.68 0.57 0.79 0.69 0.67 1.03 1.36 1.28
Total wait 1.06 1.08 1.27 1.23 1.11 1.74 2.06 2.10 1.82 2.27 2.10
95%CI 1.00 to 1.12 1.03 to 1.13 1.17 to 1.37 1.15 to 1.32 1.08 to 1.13 1.62 to 1.86 1.91 to 2.21 1.88 to 2.33 1.68 to 1.95 2.01 to 2.52 1.94 to 2.25
CT
Test 0.81 0.82 4·29 4·13 3·01 2.65 3.30 4.07 3.50 5.55 5.38
Result 0.52 0.52 1·02 0·96 0·78 0.98 0.85 1.02 1.39 1.77 1.44
Total wait 1.33 1.34 5·31 5·09 3·79 3.63 4.15 5.09 4.89 7.32 6.82
95%CI 1.24 to 1.42 1.24 to 1.44 4·87 to 5·75 4·69 to 5·49 3·59 to 3·68 3.33 to 3.93 3.88 to 4.43 4·60 to 5.57 4.60 to 5.18 6.57 to 8.07 6.35 to 7.29
MRI
Test 2.39 2.76 12.36 9.10 6.05 5.06 6·13 6.16 4.73 9.04 8.37
Result 0.60 0.56 1.39 1.36 0.88 1.12 1·05 1.24 1.52 2.55 1.56
Total wait 2.99 3.32 13.75 10.46 6.93 6.18 7·18 7.40 6.25 11.60 9.93
95%CI 2.64 to 3.34 2.84 to 3.80 13.12 to 14.38 9.82 to 11.09 6.61 to 7.25 5.66 to 6.69 6·72 to 7·63 6·73 to 8·06 5.90 to 6.60 10.63 to 12.57 8.32 to 30.55
Ultrasound
Test 1.11 1.26 4.30 5.88 1.80 2.71 3.99 3.76 3.73 6.38 6.08
Result 0.52 0.53 0.88 1.04 0.65 0.84 0.78 0.93 1.19 1.62 1.31
Total wait 1.63 1.79 5.18 6.92 2.46 3.55 4.77 4.69 4.93 8.00 7.39
95%CI 1.50 to 1.76 1.56 to 2.02 4.71 to 5.66 6.36 to 7.48 2.32 to 2.59 3.23 to 3.88 4.39 to 5.14 4.25 to 5·13 4.64 to 5.21 7.35 to 8.66 6.90 to 7.88
Upper GI endoscopy
Test 5.56 5·11 9.05 9·35 6·01 2·45 5.95 4.71 3.99 8.37 8.17
Result 1.38 0·83 1.49 1·82 1·36 0·77 0.95 1.46 1.35 1.58 1.67
Total wait 6.94 5·94 10.54 11·17 7·37 3·22 6.90 6.17 5.34 9.95 9.84
95%CI 6.35 to 7.53 5.24 to 6.64 9.85 to 11.72 10.49 to 11.84 1.03 to 7.72 2.97 to 3.47 6.45 to 7.35 5.63 to 6.72 5.02 to 5.66 9.16 to 10.74 9.18 to 10.50
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Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
Flexi sigmoidoscopy
Test 5.26 5.06 9.19 9.01 5.79 2.39 6·28 5·55 4·15 8·21 8.20
Result 1.38 0.87 1.55 1.91 1.34 0.76 0·94 1·54 1·46 2·04 1.66
Total wait 6.64 5.93 10.74 10.91 7.14 3.15 7·22 7·09 5·61 10·25 9.86
95%CI 6.06 to 7.22 5.21 to 6.65 10.03 to 11.44 10.20 to 11.63 6.75 to 7.48 2.89 to 3.41 6·76 to 7·65 6·53 to 7·65 5·26 to 5·95 9·35 to 11·15 9.21 to 10.50
Colonoscopy
Test 5.78 5.36 10.48 10.16 6.70 2.51 6.69 6.25 4.15 8.69 9.06
Result 1.38 0.84 9.61 1.91 1.37 0.78 0.98 1.54 1.56 2.00 1.70
Total wait 7.16 6.20 20.09 12.07 8.08 3.29 7.67 7.79 5.71 10.69 10.76
95%CI 6.54 to 7.78 5.49 to 6.91 19.13 to 21.06 11.38 to 12.75 7.72 to 8.43 3.01 to 3.58 7.20 to 8.13 7.16 to 8.41 5.33 to 6.08 9.80 to 11.58 10.08 to 11.44
Average wait time between a referral and first specialist appointment (Days)
Not available Not available 15.44 19.21 15.05 4.90 13.70 14.50 10.09 13.53 18.05
95%CI Not available Not available 14.10 to 16.78 17.56 to 20.87 14.25 to 15.85 4.78 to 5.32 12.72 to 14.68 13.32 to 15.68 9.91 to 10.28 12.62 to 14.44 16.75 to 19.35
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Table 5: Access to advice and faster tests (%)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
% agree /
strongly
agree
Can get
specialist
advice within
48 hours
Investigations 67.4 61.1 67.7 47.8 51.1 80.4 81.8 84.4 31.8 27.6 28.4
95%CI 61.6 to 73.2 54.1 to 68.1 61.6 to 73.8 41.3 to 54.3 47.1 to 55.1 75.5 to 85.3 76.8 to 86.8 79.3 to 89.5 26.0 to 37.6 19.2 to 36.0 22.4 to 34.4
Referrals 59.5 64.3 62.5 45.2 44.2 80.7 73.9 79.8 35.8 27.5 25.7
95%CI 53.5 to 65.5 57.5 to 71.1 56.2 to 68.8 38.7 to 51.7 40.2 to 48.2 75.9 to 85.5 68.2 to 79.6 74.2 to 82.4 29.9 to 41.7 19.1 to 35.9 19.9 to 31.5
Can arrange
faster access
to tests, if
suspicious
87.4 84.7 53.3 64·5 75.5 92.5 82.6 78.8 66.2 70.7 56.0
95%CI 83.3 to 91.5 79.6 to 89.8 46.8 to 59.8 58.3 to 70.7 72.0 to 79.0 89.3 to 95.7 77.7 to 87.5 73.1 to 84.5 60.3 to 72.1 62.2 to 79.2 49.4 to 62.6
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Figure 1: Scatterplots of vignette results and weighted regression analysis
B = 5.31 Std. Error = 11.465 p-value = 0.654 B = -5.874 Std. Error = 12.382 p-value = 0.647
B = 37.544 Std. Error = 5.963 p-value = <0.001 B = 31.916 Std. Error = 5.653 p-value = <0.001
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B = 23.832
Std. Error = 7.879 p-value = 0.014 B = 12.923 Std. Error = 4.818 p-value = 0.025
Excluding Denmark (as an outlier)
B = 30.433
Std. Error = 7.280 p-value = 0.003 B = 17.670 Std. Error = 3.913 p-value = 0.002
B = 41.077
Std. Error = 20.043 p-value = 0.071 B = 22.374 Std. Error = 11.89 p-value = 0.093
Excluding Denmark (as an outlier)
B = 70.084
Std. Error = 17.887 p-value = 0.004 B = 42.185 Std. Error = 8.604 p-value = 0.001
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B = 28.227
Std. Error = 7.908 p-value = 0.007 B = 6.533 Std. Error = 12.321 p-value = 0.610
Key
BC British Columbia
D Denmark
E England
M Manitoba
NO Norway
NI Northern Ireland
NSW New South Wales
O Ontario
S Sweden
W Wales
V Victoria
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Supplementary Table 1: Overview of PCP sampling methods used in each jurisdiction
Country Jurisdiction Primary care
physician sampling
Number of PCPs
invited
Crude response
rate (%)
Invitation format Incentives Reminders
Australia New South
Wales
PCPs were sampled
from a commercial list
(AMPCo).
2,246 11.3 A primer letter was
sent by post. Followed
by an invitation sent by
post with a link to the
survey and login
details.
1st arm: $75 voucher
(unconditional)
2nd arm: $75 voucher
(conditional)
3rd arm: No incentive
Three reminders sent
at four, six and eight
weeks after the
primary invitation.
Victoria 2,400 7.9 1st arm: $50 voucher
(unconditional)
2nd arm: $50 voucher
(conditional)
3rd arm: No incentive
Three reminders sent
at two, four and six
weeks after the
primary invitation.
Canada British
Columbia
PCPs were sampled
from lists held by the
British Columbia
College of Family
Physicians and the
University of British
Columbia Department
of Family Practice.
Over 4,200 5.5 Email invitations Entered into a draw for
an iPad (3 to give away)
on completion of the
survey
n/a
Manitoba PCPs were sampled
from a list held by the
College of Physicians
and Surgeons of
Manitoba.
500 45.6 A primer letter was
sent by post· Followed
by an invitation sent by
post with a link to the
survey and login
details.
$10 coffee voucher sent
with the letter
Two weeks after the
primary invitation.
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Country Jurisdiction Primary care
physician sampling
Number of PCPs
invited
Crude response
rate (%)
Invitation format Incentives Reminders
Ontario PCPs were sampled
from a list held by the
College of Physicians
and Surgeons of
Ontario.
3,175 18.7 Postal invitations None Two reminders were
sent in January 2013.
Denmark PCPs were sampled
from the national PCP
organisation which
represents all
practising PCPs in
Denmark.
1,000 25.5 Postal invitations and
emails reminders
125 Danish Kroner to
PCP on completion of
the survey
Two weeks after the
primary invitation.
Norway PCPs were sampled
from the national PCP
organisation.
2,000 11.5 Postal invitations None Three reminders sent
five, 10 and 17 weeks
after the primary
invitation.
Sweden Random selection
from a public list of
GPs in the Uppsala-
Orebro and Stockholm
regions where there
are 2,700 practising
PCPs.
2,000 9.9 Postal invitations and
the first 537 also
received postal invites.
None Two reminders were
sent, one September
and another in
October 2012.
United
Kingdom
England A first tranche were
sampled from a list of
contact details from a
commercial provider.
The second tranche
4,584 5.5 Email invitations £25 to PCP or charity on
completion of the
survey
Two weeks after the
primary invitation.
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Country Jurisdiction Primary care
physician sampling
Number of PCPs
invited
Crude response
rate (%)
Invitation format Incentives Reminders
were sampled from a
commercial list of
PCPs who had
attended a training
course (GP Update).
Northern
Ireland
The first tranche were
sampled by email
invitation addressed
to Practice Managers
in each of the 353
practices in Northern
Ireland.
The second tranche
were sampled by the
sending of invitations
via surface mail to
those on a publically
available list of all GPs
working within this
jurisdiction.
1,163 11.2 Email invitations Entered into a draw for
an iPad on completion
of the survey
Two weeks after the
primary invitation.
Wales All PCPs in Wales were
sampled.
1,861 11.7 A primer letter was
sent by post. Followed
by an invitation sent by
post with a link to the
survey and login
details.
£50 voucher to PCP or
charity donation on
completion of the
survey
Two weeks after
invitation, and for the
third tranche of
invitations a second
reminder two weeks
after the first.
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Supplementary Table 2: Choice of variables with reason for selection
Variable Hypothesised Effect
PCP status PCPs in regular in-hours practice better than other status (i.e. locums, out of hours only)
Gender None
Time since qualification PCPs with 10-20 years of experience better than those with 0-10 or 20-30 years
Place of qualification
Within vs. outside jurisdiction
Within jurisdiction is better as PCPs are more familiar with the health system and referral
pathways
Sole PCP in practice Sole PCPs isolated, fewer resources and may not refer as often
More than half of registered patients rural Rurality creates increased barriers to investigation or referral
Consultation length Longer consultation length has a positive impact on referrals and investigations
Time spent on cancer education in the last year More time spent in cancer specific education is better
Access to advice on investigations Access to advice is better
Access to advice on referrals Access to advice is better
Wait for first appointment Shorter is better
Length of time from ordering test to getting result in PCP Shorter is better
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Variable Hypothesised Effect
Lung vignette: Access to CXR/CT lung Access to either is better
Colorectal vignette: access to colonoscopy or abdo CT Access to either is better
Ovary vignette: access to TVUS/ US abdo/ abdo CT/pelvis CT Access to any one is better
Faster access if cancer suspected Faster access better
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Explaining variation in cancer survival between eleven
jurisdictions in the International Cancer Benchmarking
Partnership: a primary care vignette survey
Journal: BMJ Open
Manuscript ID: bmjopen-2014-007212.R1
Article Type: Research
Date Submitted by the Author: 11-Mar-2015
Complete List of Authors: Rose, Peter; University of Oxford, 2. Department of Primary Health Care Rubin, Greg; Durham University, School of Medicine and Health Perera, Rafael; University of Oxford, Primary Health Care
Almberg, Sigrun; Norwegian University of Science and Technology, Department of Cancer Research and Molecular Medicine, Faculty of Medicine Barisic, Andriana; Cancer Care Ontario, Department of Prevention and Cancer Control Dawes, Martin; University of British Columbia, Department of Family Practice Grunfeld, Eva; University of Toronto, Department of Family and Community Medicine Hart, Nigel; Queen's University Belfast, School of Medicine, Dentistry and Biomedical Sciences - Centre for Public Health Neal, Richard; Bangor University, North Wales Centre for Primary Care
Research Pirotta, Marie; University of Melbourne, General Practice and Primary Care Academic Centre Sisler, Jeff; University of Manitoba, Department of Family Medicine Konrad, Gerald; University of Manitoba, Department of Family Medicine Toftegaard, Berit; Aarhus University, Research Unit for General Practice, Department of Public Health Thulesius, Hans; Kronoberg County Research Council, Family Medicine, Department of Clinical Sciences Vedsted, Peter; Aarhus University, Research Unit for General Practice, Department of Public Health
Young, Jane; University of Sydney, Cancer Epidemiology and Services Research (CESR) Hamilton, Willie; University of Exeter Medical School, Primary Care Diagnostics ., ICBP Module 3 Working Group; ICBP Module 3 Working Group, ICBP Module 3 Working Group
<b>Primary Subject Heading</b>:
General practice / Family practice
Secondary Subject Heading: Health policy, Health services research
Keywords: HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Health policy < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, International
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health services < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, ONCOLOGY
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Explaining variation in cancer survival between eleven jurisdictions in the International Cancer
Benchmarking Partnership: a primary care vignette survey
Corresponding author - Peter W Rose, Department of Primary Care Health Sciences, University of
Oxford, New Radcliffe House, 2nd Floor, Radcliffe Observatory Quarter, Woodstock Road, Oxford,
OX2 6GG, United Kingdom, peter.rose@phc.ox.ac.uk, 07738 587 370
Greg Rubin, Professor of General Practice and Primary Care, Wolfson Research Institute, Queen's
Campus, Durham University, Stockton on Tees, TS17 6BH, United Kingdom, g.p.rubin@durham.ac.uk
Rafael Perera-Salazar, Department of Primary Health Care Sciences, University of Oxford, New
Radcliffe House, 2nd Floor, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG,
United Kingdom, rafael.perera@phc.ox.ac.uk
Sigrun Saur Almberg, Department of Cancer Research and Molecular Medicine, Faculty of Medicine,
Norwegian University of Science and Technology (NTNU), N-7491 Trondheim, Norway,
sigrun.saur@ntnu.no
Andriana Barisic, Research Associate, Department of Prevention and Cancer Control, Cancer Care
Ontario, 620 University Avenue, Toronto, Ontario, M5G 2L7, Canada,
Andriana.Barisic@cancercare.on.ca
Martin Dawes, Head, Dept. of Family Practice, David Strangway Building, University of British
Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada,
martin.dawes@familymed.ubc.ca
Eva Grunfeld, Director, Knowledge Translation Research Network Health Services Research Program,
Ontario Institute for Cancer Research; Professor and Vice Chair Research, Department of Family and
Community Medicine, University of Toronto, 500 University Avenue, Toronto, Ontario, M5G 1V7,
Canada, Eva.Grunfeld@utoronto.ca
Nigel Hart, Clinical Senior Lecturer, School of Medicine, Dentistry and Biomedical Sciences - Centre
for Public Health, Queen's University Belfast 2013, University Road Belfast, BT7 1NN, United
Kingdom, n.hart@qub.ac.uk
Richard D Neal, Professor of Primary Care Medicine and Director, North Wales Centre for Primary
Care Research, Bangor University, Gwenfro Units 4-8, Wrexham Technology Park, Wrexham, LL13
7YP, United Kingdom, r.neal@bangor.ac.uk
Marie Pirotta, Primary Health Care Research Evaluation and Development Senior Research Fellow,
Department of General Practice, 200 Berkeley Street, Carlton Victoria 3053, Australia,
m.pirotta@unimelb.edu.au
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Jeffrey Sisler, Associate Dean, Division of Continuing Professional Development and Associate
Professor, Department of Family Medicine, University of Manitoba, 727 McDermot Avenue,
Winnipeg, Manitoba, R3E 3P5, Canada, Jeff.Sisler@med.umanitoba.ca
Gerald Konrad, Associate Professor, Department of Family Medicine, University of Manitoba 5-400
Tache Avenue, Winnipeg, Manitoba, Canada, GKONRAD@exchange.hsc.mb.ca
Berit Skjødeberg Toftegaard, PhD Research Fellow Research, Unit for General Practice, Department
of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C,
Denmark, berit.toftegaard@alm.au.dk
Hans Thulesius, Associate Professor of Family Medicine, Department of Clinical Sciences, Kronoberg
County Research Council, Box 1223, 351 12 Växjö, Sweden, hansthulesius@gmail.com
Peter Vedsted, Professor, Research Unit for General Practice, Department of Public Health, Aarhus
University, Bartholins Allé 2, 8000 Aarhus C, Denmark, p.vedsted@alm.au.dk
Jane Young, Professor in Cancer Epidemiology, Public Health, School of Public Health, D02-QE11
Research Institute for Mothers and Infants, The University of Sydney, 2006, Australia,
jane.young@sydney.edu.au
Willie Hamilton, University of Exeter Medical School, College House, St Luke's Campus, Magdalen
Road, Exeter, EX1 2LU, United Kingdom, W.Hamilton@exeter.ac.uk
The ICBP Module 3 Working Group* (See Appendix A)
Word count: 3998
Abbreviations: International Cancer Benchmarking Partnership (ICBP), Primary care practitioners
(PCP), Positive Predictive Value (PPV)
Keywords: Survey, primary care, cancer, diagnosis, investigations,
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ABSTRACT
Objectives
The International Cancer Benchmarking Partnership (ICBP) is a collaboration between six countries
and 12 jurisdictions with similar primary care led health services. This study investigates primary care
physician behaviour and systems that may contribute to the timeliness of investigating for cancer
and subsequently international survival differences.
Design
A validated survey administered to primary care physicians (PCPs) via the internet set out in two
parts: direct questions on primary care structure and practice relating to cancer diagnosis, and
clinical vignettes, assessing management of scenarios relating to the diagnosis of lung, colorectal or
ovarian cancer.
Participants
2795 PCPs in 11 jurisdictions: New South Wales and Victoria (Australia), British Columbia, Manitoba,
Ontario (Canada), England, Northern Ireland, Wales (United Kingdom), Denmark, Norway, Sweden.
Primary and secondary outcome measures
Analysis compared the cumulative proportion of PCPs in each jurisdiction opting to investigate or
refer at each phase for each vignette with 1 year survival and conditional 5 year survival rates for the
relevant cancer and jurisdiction. Logistic regression was used to explore whether PCP characteristics
or system differences in each jurisdiction affected the readiness to investigate.
Results
Four of five vignettes showed a statistically significant correlation (p<0.05 or better) between
readiness to investigate or refer to secondary care at the first phase of each vignette and cancer
survival rates for that jurisdiction. No consistent associations were found between readiness to
investigate and selected PCP demographics, practice or health system variables.
Conclusions
We demonstrate a correlation between the readiness of PCPs to investigate symptoms indicative of
cancer and cancer survival rates, one of the first possible explanations for the variation in cancer
survival between ICBP countries. No specific health system features consistently explained these
findings. Some jurisdictions may consider lowering thresholds for PCPs to investigate for cancer –
either directly, or by specialist referral to improve outcomes.
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ARTICLE SUMMARY
Strengths and limitations of this study:
• A novel, large and logistically complicated study using a validated survey
• Data was analysed from 2795 PCPs across 11 jurisdictions
• Response rates were sub-optimal (ranging from 5.5% in England and British Columbia to
45.6% in Manitoba) and respondents were not totally representative of the PCPs in all
jurisdictions
• It is difficult to assess the effect of these weaknesses on the interpretation of results but
sensitivity analyses and the literature suggest it would not be large
INTRODUCTION
Significant differences in cancer survival have been demonstrated between countries with similar
health systems[1]. Poor outcomes may arise from late presentation, diagnostic delays and treatment
differences, or combinations of these[1-6]. There is some evidence that delay between presentation
and diagnosis (the diagnostic interval)[7] is associated with poorer outcomes[8-11] but the factors
involved are complex and the strength of the relationship is unclear . Detailed knowledge about how
the diagnostic interval is managed in health systems may explain these differences in survival.
The International Cancer Benchmarking Partnership (ICBP) is a collaboration across six countries
(Australia, Canada, Denmark, Norway, Sweden and the United Kingdom) and 11 jurisdictions of
comparable wealth and universal access to health care, established to examine international
differences in cancer outcomes and identify possible causes. Cancer survival is higher in Australia,
Canada, and Sweden, intermediate in Norway and lower in Denmark and the UK [1]. Differences
between the countries in the proportion diagnosed with the cancer at an early stage, suggest that
differences in the period prior to diagnosis contribute to the international variation in cancer
survival, along with other potential factors, such as access to treatment and the quality of
treatments[2-6].
Public awareness of signs and symptoms and beliefs about cancer appear to be quite similar across
jurisdictions and are therefore unlikely to account for much of the variation seen between countries.
However, differences in perceived barriers to seeing the GP have been reported [12]. Differences in
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the way cancer symptoms are recognised and managed in primary care may contribute to the
observed survival differences. For example, European inter-country differences in clinical diagnostic
practice have been reported for gastrointestinal disorders[13]. A stronger ‘gatekeeper’ role –
whereby primary care practitioners (PCPs) manage entry to specialist care and investigations – is
also associated with worse cancer survival[14]. This ‘gatekeeper issue’ is exemplified by the finding
that higher rates of endoscopy referrals within individual UK general practices are associated with a
lower mortality from oesophago-gastric cancer[15]. There are many system factors that will
influence a PCPs decision to act including guidelines, access to investigations, culture of
collaboration between primary and secondary care and these will all contribute to PCP
behaviour[16].
The aims of this study were to describe the readiness of PCPs to consider investigation or referral for
symptoms possibly indicative of cancer, and to relate this to international differences in primary care
structure and practice. Our hypothesis was that there is a positive correlation between the
proportion of PCPs who would investigate a specific symptom set for cancer and survival rates (for
the given cancer) across jurisdictions. We also investigated whether the readiness of PCPs to
investigate these cases could be explained by differences in primary care structure or PCP
characteristics.
METHODS
We conducted an international vignette survey amongst a sample of PCPs in participating
jurisdictions.
Survey development
We developed an online survey of PCPs exploring differences in their behaviours, attitudes,
knowledge and skills relating to cancer diagnosis. Development involved iterative discussion with
international partners at every stage of development. The overall validation was initially undertaken
in England with two rounds of validation using a cognitive interviewing technique with PCPs
following completion of the draft survey. Validation of the completed survey was tested in all
jurisdictions, particularly to ensure that translation had not altered meaning. There were two
questions relating to access to tests and internal consistency was measured by comparison of the
answers to these questions. The development and validation has been described in detail
elsewhere[17].
Structure
The survey was in two parts: direct questions consisting of demographic details of the respondents
and questions relating to service provision, access to investigations and waiting times following
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secondary care referrals; vignettes on management choices for a patient presenting with symptoms
suggestive of either lung (two vignettes), colorectal (two vignettes) or ovarian cancer (one vignette).
Respondents were randomly presented with two vignettes (of different cancer sites), and were
asked to complete the survey relating to their own practice rather than perceived best practice.
Respondents were aware the survey was part of a study linked to cancer.
Each vignette had two or three phases: phase one represented the first patient presentation; phases
two and three represented subsequent visits, where the patient’s symptoms had developed; each
phase had a pre-defined positive predictive value (PPV) for the cancer based on previous work to
ensure a defined increase in cancer risk at each phase (Table 1)[18-20]. Respondents were not
informed of the PPV for each set of symptoms and signs in the survey. However specifying the PPVs
in the analysis at each phase enabled a comparison of the readiness to act both within vignettes and
between vignettes of the same cancer. The response of primary interest was opting to identify
possible cancer either by referral to secondary care or by undertaking a definitive diagnostic
investigation in primary care: requesting either of these ended that vignette. The definitive tests
were determined by an expert panel and included chest Xray or Lung CT for lung vignettes,
colonoscopy or abdominal CT for colorectal vignettes, abdominal CT or abdominal or trans-vaginal
ultrasound for the ovarian vignette[17].
The final survey
The survey was completed in 11 jurisdictions: New South Wales and Victoria (Australia), British
Columbia, Manitoba, Ontario (Canada), England, Northern Ireland, Wales (United Kingdom),
Denmark, Norway, Sweden. All surveys were completed online.
Each jurisdiction decided on a method of sampling and approach to potential participants (by post or
email), depending on local conditions and the availability of databases with PCP contact details and
participation incentives. While variation in sampling methods and approaches might be expected to
introduce sample bias and to affect response rates, there are no observable trends that would
suggest that this is true (Supplementary Table 1).
Participants
Participants were PCPs working predominantly in clinical practice, including locums; retired PCPs,
and those in training were not eligible. Considering all jurisdictions, the online surveys were
completed between May 2012 and July 2013; the start dates and end dates in each jurisdiction
varied.
The representativeness of each sample was assessed by comparing gender, age and place of
qualification between respondents and data for all PCPs in each jurisdiction.
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All participants gave their consent for their data to be used by completing the online survey.
Approvals to conduct this study were sought from ethics committed in each jurisdiction
(Supplementary Table 2).
Sample size
Each jurisdiction aimed to recruit at least 200 respondents. This provided a 95% confidence interval
(CI) +/- 7% for equally distributed responses (e.g. 50% responding ‘yes’), and +/- 6% CI for less
equally distributed responses (e.g. 20% responding ‘yes’).
Analysis
Direct questions, relating to demographics and primary care structure factors, were analysed using
descriptive statistics. The questions relating to average waiting times for tests and results were
analysed by estimating the mean time from ordering a test to receiving the results by using the mid-
point of each waiting time category.
Analysis of the vignettes was undertaken in two stages. Our hypothesis was explored by comparing
the cumulative proportion of PCPs opting to investigate or refer at each phase for each vignette
using percentage 1 year survival rates in each jurisdiction for the relevant cancer.
Linear correlations were estimated between the proportions opting to investigate at each phase and
survival rates.
Weighted Regression
When comparing between jurisdictions, weighted linear regression was used to adjust for different
sample sizes in each jurisdiction, based on the total number of respondents for each vignette. A
regression model was fitted for each phase and each vignette using 1 year survival as the outcome
with the number of PCPs acting at each phase as a single explanatory variable. The weights were the
inverse of the variance of the proportion at a given phase for each jurisdiction. No weighted
regression models were possible for jurisdictions where all PCPs had opted to investigate at a given
phase.
Logistic Regression – Multilevel model
Weighted regression did not allow us to explore if individual PCP characteristics and access to tests
(within each jurisdiction) were associated with opting to investigate. Therefore, in the second stage
of the analysis, we fitted separate multilevel logistic regression models using opting to investigate as
the outcome and estimated the association with (a) PCP characteristics, (b) access to tests, (c)
jurisdiction level survival (1 and conditional 5 year) as reported by Coleman and colleagues [1] and
(d) a full model including PCP characteristics and access to tests. This last model only included those
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variables significantly associated in models (a) and (b) to reduce the chances of identifying spurious
associations.
We identified variables that might influence opting to investigate in models (a) and (b) as well as the
expected direction of effect (Supplementary Table 3). As with the weighted regression, analyses
were performed by vignette as explanatory variables were different for each cancer. These variables
are not independent and therefore some basic model selection (based on statistical significant
associations p-value <0.05) was used to determine the choice of variables included in model (c).
Sensitivity analyses
Previous studies comparing survival rates between England or the UK to other countries suggested
that later diagnosis could be a factor contributing to poorer outcomes: thus, opting to investigate or
refer later in the process of clinical presentation would contribute to the delay in diagnosis in poorer
performing jurisdictions[1,19]. Both 1 year survival and 5 year survival conditional on surviving at
least 1 year (conditional 5 year survival) could reflect a longer diagnostic interval due to delays,
including in primary care, but neither are a perfect measure of this[21]. We chose 1 year survival as
the primary outcome measure as we anticipated that it more directly reflects activity in primary
care. We then undertook sensitivity analysis using conditional 5 year survival to check that our
findings were also confirmed using this outcome.
Denmark has substantially changed its primary care referral procedures since the latest reported
comparative survival figures[22,23]. This change in procedures was apparent in the results with
Denmark appearing as an outlier in vignettes 3 and 4 related to the diagnosis of colorectal cancer;
analyses of these two vignettes were repeated excluding Denmark.
Australia oversampled rural PCPs to ensure the views of this minority were adequately represented.
A post hoc sensitivity analysis was undertaken to address this: we formed a data set with a sample of
rural PCPs so that this was representative of the rural/urban split in Australia and compared these
with the results of the whole data set.
Governance
At all stages the methodology, sampling and analysis were discussed with four separate working
groups: the module lead of each jurisdiction, the Programme Board overseeing the whole ICBP
programme, an academic steering group comprising the module chair and three academic PCPs with
an interest in cancer (PWR, GR, WH, PV) and an academic reference group comprising primary care
academics from within and outside ICBP jurisdictions.
RESULTS
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The online survey was completed by 2795 PCPs. Almost all jurisdictions received at least 200
responses; only the Northern Ireland response (the smallest total population) was substantially
below this target. Crude response rates (most jurisdictions stopped the survey when the sample size
was reached) varied between jurisdictions from 5.5% in England and British Columbia to 45.6% in
Manitoba (Appendix Table 1).
Characteristics of respondents are summarised in Table 2. There were significantly more female
PCPs in the samples from Victoria, Ontario and British Columbia and fewer from Norway, when
compared with their national data. The samples from England, Wales, Northern Ireland, New South
Wales, Victoria, Sweden, Norway and Ontario had fewer doctors who had qualified outside the
country and Manitoba had more (for Canadian provinces and Australian states this meant training
outside Canada and Australia respectively). Respondents from England and Norway were older
whereas respondents from New South Wales and all Canadian provinces were younger compared
with national data. Northern Ireland was included for completeness, even though their recruitment
fell below target, acknowledging that confidence intervals would be wider than anticipated.
Vignette Results
In four of the five vignettes there was a statistically significant correlation (p<0.05) between opting
to investigate for cancer in a jurisdiction at phase one and the cancer survival in that jurisdiction
(Figure 1). Only phase one results are presented; nearly all PCPs had taken action to refer or
investigate for a potential diagnosis of cancer by the end of phase 2.
Vignette 1 (lung cancer) was the only vignette that did not show any statistically significant
correlations. In this vignette, the estimated positive predictive value (PPV) for lung cancer for the
symptoms presented at phase one was 0.9% (although this was not explicitly presented in the
vignette) and yet the range of respondents opting to investigate at this phase between jurisdictions
was 40% to 80% (Table 1). The estimated PPV for lung cancer in phase one of vignette 2 was higher
at 3.6% and yet the range of respondents opting to investigate at this phase was 4% to 52%.
The lung and ovarian cancer vignettes were usually completed by the use of a test (chest X-Ray for
lung cancer, ultrasound for ovarian cancer) rather than by specialist referral. In contrast, more than
half of the colorectal vignettes were completed by referral.
Consistent with the correlation results, statistically significant associations were found using
weighted regression between the one year survival and readiness to investigate at phase one for
vignettes 2, 3, 4 (after Denmark was excluded) and 5. For the sensitivity analysis based on the
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conditional 5 year survival, this association was found at phase one for vignettes 2, 3, and 4 (after
Denmark was excluded) (Table 1).
Logistic Regression analysis
No factors (PCP characteristics, access to tests or length of time from ordering test to receiving
results) showed a consistent association with the readiness to investigate. The only two PCP
characteristics associated with the outcome were that doctors who trained outside their jurisdiction
were more likely to refer or investigate cases earlier in vignettes 3 and 4 (both colorectal) and older
doctors were more likely to refer or investigate cases earlier in vignette 4. The former association
was investigated further using data from Manitoba (the only jurisdiction to have more doctors
trained outside of the jurisdiction); within this dataset there was no association found between
place of training and readiness to investigate. The latter association was no longer statistically
significant when excluding Denmark as part of the sensitivity analysis; while training outside was still
significant (data not shown).
Similarly, adjusting for rural/urban split amongst Australian PCPs did not significantly affect the
results.
Direct questions – access to diagnostics and secondary care advice
Similarities and differences in primary care system factors are reported between jurisdictions.
Reported direct access, to blood tests for cancer diagnosis, plain X-rays and ultrasound was greater
than 70% across all jurisdictions (Table 3). Access to other tests was variable. Direct access to
endoscopy was less common in Canada. The United Kingdom and Denmark had comparatively low
levels of direct access to CT and MRI scanning.
With the exception of plain X-rays, the total wait from request to receipt of report for imaging or
endoscopy was reported to be over four weeks in most jurisdictions and over 12 weeks in some.
Total wait between a referral for a suspected cancer and a patient’s first specialist appointment was
between two and three weeks for all jurisdictions (Table 4). Most PCPs reported they could expedite
access to tests if cancer was suspected. With the exception of the United Kingdom, most PCPs
reported ready access to secondary care advice about investigation or referral of suspected cancer
from a specialist (Table 5).
While there was variation across jurisdictions in terms of access to diagnostics and secondary care
advice, none of these factors were associated with PCP readiness to act.
DISCUSSION
Principal findings
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Using an online survey in 11 jurisdictions, we have demonstrated a correlation which suggests a
relationship between the readiness of PCPs to investigate or refer for suspected cancer and cancer
survival in each jurisdiction. This is the first time that readiness to investigate for cancer – either
directly or by referral to secondary care – has been shown to correlate with cancer survival. Evidence
suggests that variations between health care systems have an impact on health outcomes[24].
There is significant variation between jurisdictions in the access that PCPs have to diagnostic tests.
Whether greater access to tests improves outcomes depends on the sensitivity of the test and how
the waiting time for test results compares with the waiting time if a referral is made. PCPs may not
be aware of the fastest way to diagnose cancer: referral or primary care investigation. Our data
indicate significantly long waits in some jurisdictions for the results of tests undertaken in primary
care. However access to tests was not associated with readiness to investigate or refer. Further
research is required in this complex area.
Strengths and weaknesses
This was a novel, large, logistically complex survey using a validated tool in 11 jurisdictions with
primary care based health systems. Once a respondent engaged in the online survey the proportion
who went on to complete it was high. The vignettes had face validity; they directly reflected clinical
practice and were universally applicable[17]. Moreover, since the study was completed, the
vignettes have been adopted as part of a GP education programme in the UK in light of their
applicability to primary care. There is evidence that using vignettes in a survey correlates well to
clinical practice[25]. Vignettes have also been used recently in a similar context[26]. While surveys
using hypothetical vignettes are not ideal we chose vignette based surveys as a cost effective way to
maintain consistency across all jurisdictions.
The readiness of PCPs to act consists of personal attributes (for example knowledge and attitudes
about cancer as well as perceptions about the role of PCPs) and system features (for example
guidelines, availability of tests/referral and waiting time for results). A multiple regression analysis
did not find a significant association with any of these factors.
This study used an ecologic outcome which makes the risk of an ecologic fallacy important. We do
not know whether the correlation with readiness and survival is causal or simply an indicator of
other factors. Therefore, this study raises the potential of an interaction between the PCP’s
readiness and the system in which they act. These results add to the science pointing towards this
important implication.
The poor response rates in some jurisdictions and the lack of representativeness of the respondents
in several jurisdictions (based on demographic data) are weaknesses. It is difficult to assess whether
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and by how much these two factors would affect the interpretation of the results. Two jurisdictions
achieved a response rate over 25%; in other jurisdictions response rates ranged from 5.5% to 18.7%.
A significant obstacle to achieving better response rates in some jurisdictions was limited availability
of comprehensive and up to date email addresses for PCPs. The response rates achieved are broadly
in line with lower response rates for online surveys generally[27]. Furthermore, response rates in
physician surveys have been declining in recent years[28].
Those responding were not wholly representative of their local PCP population, but the differences
in gender and country of qualification were bidirectional. Evidence from Australia suggests that
while respondents had more positive views about cancer compared to non-responders, the
magnitude of this difference is the same irrespective of incentives (conditional or otherwise) [29]. In
addition, respondents were aware the survey was part of a study linked to cancer for ethical
reasons; responses might have been different in a blinded study. Taken together, these biases tend
to underestimate the possible variation and our results are thus minimum estimates of the
correlation between readiness to investigate and survival. In jurisdictions where respondents were
less representative of the local PCP population, respondents were in general more likely to be
women, to have qualified in that country and to be younger. Although training outside the country
was associated with opting to act earlier in the colorectal vignettes, sensitivity analysis using
Manitoba data suggested this is unlikely to have substantially affected overall results. A systematic
review of studies of primary care referrals suggested that less than 10% of the observed variation in
referral rates could be accounted for by practice and GP characteristics[30]. It is therefore unlikely
that the minor unrepresentativeness of some samples has materially altered the findings. Other
hidden confounders may have influenced the results, but they are unlikely to have been major.
Earlier diagnosis could lead to perceived better outcomes through two mechanisms: earlier stage at
diagnosis or lead time bias. Our correlations were significant for both one year and conditional five
year survival, suggesting that lead time bias is less of an issue.
The vignettes all described hypothetical patients with symptoms which have been shown to be
significantly associated with the given cancer.
The survey was conducted in 2012/13 and therefore reflects clinical practice at this time. The latest
comparative survival data for the three cancers in participating jurisdictions is from 2007. The
jurisdictions had no major changes to cancer diagnostic pathways during this time, with the
exception of Denmark, which in 2009 introduced significant reforms to improve diagnostic access for
PCPs. Consequently, Denmark was often an outlier in the analyses: sensitivity analyses including and
excluding Denmark strengthened our findings.
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Comparison with other research
An analysis of the health systems in the ICBP jurisdictions showed few significant differences[15].
Poorer outcomes have been correlated with the strength of the ‘gatekeeping’ role of PCPs in
different health systems[13]: our findings broadly support this. Denmark has deliberately
reorganised cancer diagnostic services to reduce the gatekeeping role by enabling PCPs to undertake
timely investigation of patients with alarm well as vague symptoms[23]. Our results suggest that
Danish PCPs now behave more like PCPs in jurisdictions with better cancer outcomes. Gatekeeping
may encourage PCPs to over-use other diagnostic strategies, such as the ‘test of time’ which could
contribute to longer diagnostic intervals[31]. Other possible reasons to account for our results
include PCPs’ knowledge and PCPs’ relationships with specialists.
Implications
In this study PCPs opted to investigate at low levels of risk, possibly reflecting bias because this was a
survey relating to cancer. However, recent work suggests that patients prefer to be investigated
when cancer is a possibility, even at low risk levels[25]. If risk thresholds at which symptoms are
investigated were to be lowered, health economic considerations would need to be taken into
account. The use of risk prediction tools[32,33] may aid PCPs in this respect. Our findings also
suggested that PCPs were not necessarily aware of the positive predictive values of groups of
symptoms. Across all jurisdictions, the speed of referral was inversely related to the PPV for lung
cancer in the two lung vignettes. However, these counterintuitive responses are consistent with
referral guidelines in some of the jurisdictions. Variation in readiness to investigate or refer to
secondary care by PCPs for patients with a differential diagnosis of cancer might explain some of the
variation in cancer survival between ICBP jurisdictions. It is unlikely that a single solution to this
variation will work across all jurisdictions. However, solutions are likely to include initiatives that
empower PCPs toward earlier investigation of cancer and to reduce the barriers that inhibit
specialist referral. Such changes are likely to require changes in local policy leading to increased
access to investigations and diagnostics, more efficient referral pathways and the re-drafting of local
referral guidelines to facilitate referral at risk levels below those currently mandated.
Future research
The study supports the ecologic findings that there is a correlation between the health care system
and the way PCPs perform clinical diagnosis. Therefore, it seems appropriate to perform studies to
assess which factors affect the readiness of a PCP to investigate or refer, for example changed access
to investigations, the nature and recommendations of clinical guidelines, access to rapid diagnostics
and referral and the nature of relationships between primary and secondary care. Further studies on
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using alternate outcome measures such as stage distribution and cohort studies on survival and
mortality could provide additional insights into these factors.
Author Contribution Statement: All authors contributed to the manuscript. Peter Rose wrote the
original manuscript. All authors contributed to the study design, data collection, data interpretation,
review process; reading and considering the analysis, being involved in discussion and contributing
variously to the iterative writing and commenting process. Every author takes responsibility for the
entire content of the manuscript.
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APPENDIX A: MODULE 3 WORKING GROUP
Andriana Barisic, Research Associate, Department of Prevention and Cancer Control, Cancer Care
Ontario, 620 University Avenue, Toronto, Ontario, M5G 2L7, Canada
Martin Dawes, Head, Department of Family Practice, David Strangway Building, University of British
Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3, Canada
Diana Dawes, Research Associate, Department of Family Practice, David Strangway Building,
University of British Columbia, 5950 University Boulevard, Vancouver, British Columbia, V6T 1Z3,
Canada
Mark Elwood, Vice-President, Family and Community Oncology, BC Cancer Agency; Clinical
Professor, School of Population and Public Health, UBC; Honorary Professor, Department of
Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
Kirsty Forsdike, Senior Research Assistant, Department of General Practice, 200 Berkeley Street,
Carlton Victoria 3053, Australia
Eva Grunfeld, Director, Knowledge Translation Research Network Health Services Research Program,
Ontario Institute for Cancer Research; Professor and Vice Chair Research Department of Family and
Community Medicine, University of Toronto, 500 University Avenue, Toronto, Ontario, M5G 1V7,
Canada
Nigel Hart, Clinical Senior Lecturer, School of Medicine, Dentistry and Biomedical Sciences - Centre
for Public Health, Queen's University Belfast 2013, University Road Belfast, BT7 1NN, United
Kingdom
Breann Hawryluk, Project Planning Coordinator, Department of Patient Navigation, Cancer Care
Manitoba, 675 McDermot Street, Winnipeg, Manitoba, Canada
Gerald Konrad, Associate Professor, Department of Family Medicine, University of Manitoba 5-400
Tache Avenue, Winnipeg, Manitoba, Canada
Anne Kari Knudsen, Administrative leader, Department of Cancer Research and Molecular Medicine,
Norwegian University of Science and Technology, 7489 Trondheim
Magdalena Lagerlund, Department of Learning, Informatics, Management and Ethics, Karolinska
Institute, Berzelius väg 3, Stockholm 171 77, Sweden
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Claire McAulay, Research Officer, Public Health, School of Public Health, D02-QE11 Research
Institute for Mothers and Infants, University of Sydney NSW 2006 Australia
Jin Mou, Postdoctoral Fellow, Department of Family Practice, Research Office, Department of Family
Practice, David Strangway Building, University of British Columbia, 5950 University Boulevard,
Vancouver, British Columbia, V6T 1Z3, Canada
Richard D Neal, Professor of Primary Care Medicine and Director, North Wales Centre for Primary
Care Research, Bangor University, Gwenfro Units 4-8, Wrexham Technology Park, Wrexham, LL13
7YP, United Kingdom
Marie Pirotta, Primary Health Care Research Evaluation and Development Senior Research Fellow,
Department of General Practice, 200 Berkeley Street, Carlton Victoria 3053, Australia
Jeffrey Sisler, Associate Dean, Division of Continuing Professional Development and Professor,
Department of Family Medicine, University of Manitoba, 727 McDermot Avenue, Winnipeg,
Manitoba, R3E 3P5, Canada
Berit Skjødeberg Toftegaard, PhD Research Fellow, Research Unit for General Practice, Department
of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C, Denmark
Hans Thulesius, Associate Professor, Lund University, Box 117, SE-221 00 Lund, Sweden
Peter Vedsted, Professor, Research Unit for General Practice, Department of Public Health, Aarhus
University, Bartholins Allé 2, 8000 Aarhus C, Denmark
David Weller, James Mackenzie Professor of General Practice, Centre for Population Health Sciences,
University of Edinburgh, Doorway 1, Medical Quad Teviot Place, Edinburgh, EH8 9DX, United
Kingdom
Jane Young, Professor in Cancer Epidemiology, Public Health, School of Public Health, D02-QE11
Research Institute for Mothers and Infants, The University of Sydney, 2006, Australia
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ACKNOWLEDGEMENTS
Kate Aldersey, Martine Bomb and Catherine Foot of Cancer Research UK for managing the ICBP
programme, along with Brad Groves and Samantha Harrison who have been key to bringing about
the development of this paper. John Archibald at Sigmer Technologies Ltd for hosting the online
survey. Alice Fuller for help with data management. We would also like to acknowledge and thank
our ICBP clinical committee members and working group members in each jurisdiction who were not
part of the central team, but who contributed to the review of our results and this paper.
Programme Board: Ole Andersen (Danish Health and Medicines Authority, Copenhagen, Denmark),
Søren Brostrøm (Danish Health and Medicines Authority, Copenhagen, Denmark), Heather Bryant
(Canadian Partnership Against Cancer, Toronto, Canada), David Currow (Cancer Institute New South
Wales, Sydney, Australia), Dhali Dhaliwal (Cancer Care Manitoba, Winnipeg, Canada), Anna Gavin
(Northern Ireland Cancer Registry, Queens University, Belfast, UK), Gunilla Gunnarsson (Swedish
Association of Local Authorities and Regions, Stockholm, Sweden), Jane Hanson (Welsh Cancer
National Specialist Advisory Group, Public Health Wales, Cardiff, UK), Todd Harper (Cancer Council
Victoria, Carlton, Australia), Stein Kaasa (University Hospital of Trondheim, Trondheim, Norway),
Nicola Quin (Cancer Council Victoria, Carlton, Australia), Linda Rabeneck (Cancer Care Ontario,
Toronto, Canada), Michael A Richards (Care Quality Commission, London, UK), Michael Sherar
(Cancer Care Ontario, Toronto, Canada), Robert Thomas (Department of Health Victoria, Melbourne,
Australia).
Academic Reference Group:
Jon Emery, Professor of Primary Care Cancer Research, University of Melbourne and Clinical
Professor of General Practice, University of Western Australia, Australia
Niek de Wit, Professor of General Practice, Julius Centre for Health Sciences and Primary Care,
University Medical Centre, Utrecht, Netherlands
Roger Jones, Editor, British Journal of General Practice and Emeritus Professor of General Practice,
King's College, London, United Kingdom
Jean Muris, Associate Professor in Family Medicine, Maastricht University, Netherlands
Frede Olesen, Professor, Research Unit for General Practice, Department of Public Health, University
of Aarhus, Denmark
Funding: This work was supported by Canadian Partnership Against Cancer; Cancer Care Manitoba;
Cancer Care Ontario; Cancer Council Victoria; Cancer Institute New South Wales; Danish Health and
Medicines Authority; Danish Cancer Society; Department of Health, England; Department of Health,
Victoria; Northern Ireland Cancer Registry; The Public Health Agency, Northern Ireland; Norwegian
Directorate of Health; South Wales Cancer Network; Swedish Association for Local Authorities and
Regions; Tenovus; British Columbia Cancer Agency; Public Health Wales and the Welsh Government
Competing Interests: WH is the clinical lead for the ongoing revision of the NICE 2005 guidance on
investigation of possible cancer, CG27. His contribution to this article is in a personal capacity, and is
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not to be interpreted as representing the view of the Guideline Development Group, or of NICE
itself. The authors declared no conflicts of interest.
Contributorship
PWR, GR, RPS, SSA, AB, MD, EG, NH, RDN, MP, JS, GK, BST, HT, JY, WH and the ICBP Module 3
Working Group contributed to the manuscript. PWR wrote the original manuscript. PWR, GR, RPS,
SSA, AB, MD, EG, NH, RDN, MP, JS, GK, BST, HT, JY, WH and the ICBP Module 3 Working Group
contributed to the study design, data collection, data interpretation, review process; reading and
considering the analysis, being involved in discussion and contributing variously to the iterative
writing and commenting process. Every author takes responsibility for the entire content of the
manuscript.
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pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
ay 2015. Dow
nloaded from
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27. Nicholls K, Chapman K, Shaw T, et al. Enhancing Response Rates in Physician Surveys: The
Limited Utility of Electronic Options. Health Service Research 2011; 46(5): 1675-82
DOI:10.1111/j.1475-6773.2011.01261
28. Wiebe ER, Kaczorowski J, MacKay J. Why are response rates in clinician surveys declining?
Canadian Fam Physician 2012; 58(4): 225-8
29. Young JM, O’Halloran A, McAulay C, et al. Unconditional and conditional incentives
differentially improved general practitioners’ participation in an online survey: randomized
controlled trial. Journal of Clinical Epidemiology 2014; 19 October
DOI:10.1016/j.jclinepi.2014.09.013
30. O’Donnell CA. Variation in GP referral rates: what can we learn from the literature? Family
Practice 2000; 17: 462-471
31. Almond SC and Summerton N. Test of time. BMJ 2009; 338: 1878
32. Hamilton W, Green T, Martins T, Elliott K, Rubin G, Macleod U. Evaluation of risk assessment
tools for suspected cancer in general practice: a cohort study. Br J Gen Pract 2013; 63(606):
30-6. DOI:10.3399/bjgp13X660751
33. Hippisley-Cox J and Coupland C. Symptoms and risk factors to identify men with suspected
cancer in primary care: derivation and validation of an algorithm. Br J Gen Pract 2013;
63(606): e1-10. DOI:10.3399/bjgp13X660724
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ay 2015. Dow
nloaded from
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pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
ay 2015. Dow
nloaded from
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Table 1: Summary of the vignettes
Vignette
Cancer
Patient details
Management options Phase 1 Phase 2 Correlation between survival
and referral or test at phase 1
(weighted regression analysis)
Definitive
actions
Non-definitive actions PPV Refer /
Test (%) *
PPV Refer /
Test (%)*
1 year
survival
P value
Conditional 5 year
survival
P value
1 Lung Phase 1 68-year old female, ex-smoker with persistent cough for 3
weeks but no other symptoms, taking ramipril for
hypertension. Ear, throat and chest exams were normal.
Secondary care
referral
Chest x-ray
Chest CT
• Antibiotics
• Oral steroids
• Anti-tussive medicines
• Stop ramipril
• Advise visit to pharmacy to
try remedies there
• Tell her that no action is
needed at this stage
0.9 40-80 3·9 95-100 0.654 0.647
Phase 2 Patient returns after another 3 weeks, saying cough has
persisted and now there are streaks of blood in the sputum.
No weight loss, but a chest examination reveals some
crepitations at the left base. Any tests previously undertaken
were normal.
0.357
(excluding
Denmark)
0.911
(excluding
Denmark)
Phase 3 Patient returns with ongoing symptoms and you decide to
order a chest X-ray. The report says there is mild
cardiomegaly but the lung fields are clear.
2 Lung Phase 1 62 years old man with COPD, a heavy smoker for over 40
years. He presented with respiratory symptoms.
Secondary care
referral
Chest x-ray
Chest CT
• Advise increased use of
salbutamol inhaler
• Antibiotics
• Oral steroids
• Antibiotics and add new
inhaler- steroid or
salmeterol
• Anti-tussive medicines
• Advise visit to pharmacy to
try remedies there
• Tell him that no action is
needed at this stage
3.6 5-50 >10·0 87-100 <0.001 <0.001
Phase 2 Patient returns in 3 weeks, complains of constant ache in left
shoulder. Patient attributes pain to persistent cough; he is
also producing grey coloured sputum in larger quantities
than usual, but no other chest symptoms. No weight loss. On
exam he has still has a bilateral upper lobe wheeze and some
crepitations at the left base. Examination of his shoulder is
normal.
<0.001
(excluding
Denmark)
<0.001
(excluding
Denmark)
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Vignette
Cancer
Patient details
Management options Phase 1 Phase 2 Correlation between survival
and referral or test at phase 1
(weighted regression analysis)
Definitive
actions
Non-definitive actions PPV Refer /
Test (%) *
PPV Refer /
Test (%)*
1 year
survival
P value
Conditional 5 year
survival
P value
3 Colorectal Phase 1 43 year old woman with IBS for more than 10 years, but the
IBS has got worse recently. She has abdominal pain every
day, unchanged bowel habit and no other symptoms. She
has no family history of cancer.
Secondary care
referral
Colonoscopy
Abdominal CT
• Prescribe medication for
IBS
• Give dietary advice
• Offer psychological
therapies (counselling and
CBT)
• Tell her that no action is
needed at this stage
0.7 5-45 1.2 48-89 0.014
0.025
Phase 2 The patient returns to see you. Her recent blood test has
returned a haemoglobin level of 10.5g/dl.
0.003
(excluding
Denmark)
0.002
(excluding
Denmark)
4** Colorectal Phase 1 68 year old man with no relevant medical history. He has
experienced loose stools twice a day, most days for over 4
weeks. He has no other symptoms. Examination incl. rectal
exam was normal.
Secondary care
referral
Colonoscopy
Abdominal CT
• Offer medication e.g.
loperamide, antispasmodic,
analgesia.
• Advice on diet
• Tell him that no action is
needed at this stage
0.9 20-40 1.9 77-89 0.071
0.093
Phase 2 Any tests selected are negative. Patient returns 2 weeks
later, describing that the diarrhoea remains much the same
but he now also has intermittent sharp abdominal pain.
Abdominal and PR examinations are normal.
0.004
(excluding
Denmark)
0.001
(excluding
Denmark)
Phase 3 All tests are negative. A further two weeks later patient
describes two brief episodes of rectal bleeding (bright red)
two days apart.
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Vignette
Cancer
Patient details
Management options Phase 1 Phase 2 Correlation between survival
and referral or test at phase 1
(weighted regression analysis)
Definitive
actions
Non-definitive actions PPV Refer /
Test (%) *
PPV Refer /
Test (%)*
1 year
survival
P value
Conditional 5 year
survival
P value
5** Ovarian Phase 1 53 year old woman whose last period was 6 months ago. She
had experienced abdominal pain for the last 3 weeks. She
has had no other symptoms and the same sexual partner for
20 years.
Secondary care
referral
Abdominal
ultrasound
Pelvic CT
• Prescribe analgesia
• Prescribe anti-spasmodic
• Undertake investigations
now
• Tell her that no action is
needed at this stage
0.3 40-75 0.7 68-90 0·007
0.610
Phase 2 All investigations to date have been normal. The patient
presents one month later with urinary frequency. She says
the abdominal pain is still present but comes less often.
Abdominal examination is normal. A urine dipstick for blood,
protein, nitrite, white cells and sugar is negative.
0.009
(excluding
Denmark)
0.744
(excluding
Denmark)
Phase 3 Patient returns 6 weeks later saying pain is worse, she is
passing urine every 3 hours, day and night and has noticed
that her abdomen seems swollen. You examine her abdomen
and it does looks distended but you cannot feel any other
abnormality.
* Range of respondent who completed the vignette at this stage by referral or undertaking a definitive diagnostic test.
** Stage 3 results not reported as nearly 100% of respondents referred or undertook definitive test by this stage
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Table 2: Representativeness of samples: comparison of respondent characteristics with whole jurisdiction data
Sub-categories ENG WA NI VIC NSW SWE NO DK ONT MAN BC
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al*
Su
rve
y
p v
alu
e
Na
tion
al*
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
Na
tion
al
Su
rve
y
p v
alu
e
N 35527 251 2015 218 1178 130 20360 189 20360 256 5467 199 5373 230 3590 255 12296 610 1323 228 5833 229
(%)
(%) (%) (%) (%) (%) (%) (%) (%) (%) (%)
Male 52.9 41.8
0.1
98
56.0 61.0 0.1
98
0
55.0 56.0 0.8
01
8
61.0 53.0 0.0
03
4
61.0 56.0 0.0
83
9
54.0 53.0 0.8
38
4
58.3 66.5 0.0
13
2
56.4 57.3 0.7
90
2
57.6 51.6 0.0
03
8
62.6 59.2 0.3
32
8
60.6
45.0
<0
.00
01
Female 47.1 58.2 44.0 39.0 45.0 44.0 39.0 47.0 39.0 44.0 46.0 47.0 41.7 33.5 43.6 42.7 42.4 48.4 37.4 40.8 39.4
55.0
Place of
Qualification
Within
jurisdiction
≠77.4 91.2
0.0
00
4
82.0 89.0
0.0
09
6
≠77.4 100.0
<0
.00
01
66.0 74.0
0.0
02
9
66.0 74.0
0.0
08
6
2010:
77.0
89.0
<0
.00
01
61.6 74.8
<0
.00
01
not
available
98.4
74.6 90.1 <
0.0
00
1
53.1 48.7
<0
.00
01
not
available
72.9
Outside
jurisdiction
≠22.6
8.8
18.0 11.0
≠22.6
0.0
34.0
26.0
34.0 26.0
2010:
23.0
11.0
38.4 25.2
1.6
24.7 9.9
46.9 51.3
27.1
Age Bands Under 30 1.0 0.4
0.0
13
1.0 0.0
0.1
27
7
0.1 0.80
0.4
72
<35:
7.0
6.0
0.0
86
4
<35:
7.0
10.0
0.0
46
9
<40®:
7.0
33.0
<0
.00
01
4.6 0.0
<0
.00
01
<34:
0.11
0.4
0.6
52
5
1.7 14.0
<0
.00
01
4.7 7.9
<0
.00
01
<30
1.2 17.9
<0
.00
01
30-44 42.0 14.7 39.0 39.9 40.0 36.9 35-
44®:
20.0
24.0 35-44®:
20.0
24.0 35-
44®:
10.0
9.0 43.3 30.9 35-44:
20.1
18.8 32.2 26.1 31-45®:
33.2
37.3 30-39®:
18.9
21.0
45-54 34.4 13.2 37.0 39.4 35.0 39.2 31.0 36.0 31.0 28.0 28.0 25.0 21.2 19.6 29.2 29.0 28.0 27.8 46-55®:
30.1
33.8 40-49®:
24.4 21.8
55-64 18.4 12.4 20.0 20.2 23.0 20.8 55+:
42.0
34.0 55+®:
42.0
38.0 43.0 26.0 25.5 40.9 40.8 40.4 24.7 23.6 56-64®:
20.6
17.1 50-59®:
29.9 26.6
65+ 4.0 17.9 3.0 0.5 1.9 2.30 12.0 8.0 5.5 8.7 9.6 11.4 13.4 8.5 9.4 3.95 60-69®:
20.7 10.5
unknown 0.1 17.9
70-79®:
4.4 1.3
80+®:
0.6 0.9
Key
®Where age groups sub-groups differ they are marked in bold and italic
*using Australian National statistics
≠ UK na\onal figures used
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Table 3: Direct access* to investigations (%)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
Cancer diagnosis blood tests #
Blood tests 98.0 99.5 81.7 69.3 80.7 89.8 70.9 75.8 94.0 89.0 75.7
95%CI 95.2 to 99.3 96.6 to 100 75.9 to 86.3 62.8 to 75.1 77.2 to 83.7 85.3 to 93.1 64.5 to 76.6 69.1 to 81.4 90.1 to 96.5 81.2 to 93.9 69.3 to 81.1
Endoscopy
Upper GI endoscopy 26.0 66.1 7.4 13.7 19.5 56.5 18.0 46.2 68.1 68.5 66.1
95%CI 20.8 to 31.9 58.9 to 72.8 4.5 to 11.8 9.6 to 18.9 16.4 to 22.9 50.1 to 62.6 13.2 to 23.5 38.9 to 53.2 61.9 to 73.8 59.1 to 77.2 59.3 to 72.2
Flexi sig 17.7 34.9 13.1 13.2 17.7 54.9 16.2 34.2 40.6 14.8 32.3
95%CI 13.3 to 23.1 28.2 to 42.2 9.2 to 18.3 9.2 to 18.4 14.7 to 21.0 48.6 to 61.1 11.7 to 21.6 27.8 to 41.5 34.6 to 47.0 8.9 to 23.0 26.1 to 38.8
Colonoscopy 26.4 61.9 7.9 13.2 22.4 52.5 17.1 45.2 33.1 19.8 22.0
95%CI 21.1 to 32.3 54.5 to 68.8 4.9 to 12.3 9.2 to 18.4 19.1 to 26.0 46.2 to 58.8 12.5 to 22.6 37.9 to 52.2 27.4 to 39.3 13.3 to 29.2 16.8 to 28.2
Imaging
Xray Whole body^ 99.2 100.0 96.1 92.5 98.0 92.2 74.3 86.4 82.5 89.9 87.6
95%CI 96.9 to 99.9 97.5 to 100 92.4 to 98.1 88.1 to 95.5 96.4 to 98.9 88.0 to 95.0 68.1 to 79.8 80.6 to 90.7 77.1 to 86.9 82.3 to 94.6 82.3 to 91.5
CT Whole body 99.6 100.0 92.6 86·4 95.1 22.0 73.5 84.3 21.5 27.5 46.3
95%CI 97.5 to 100 97.5 to 100 88.2 to 95.5 81.1 to 90.4 93 to 96.7 17.1 to 27.7 67.2 to 79.0 78.4 to 89.0 16.7 to 27.2 19.6 to 37.0 39.6 to 53.2
MRI Whole body 44.9 54.0 62.0 74·6 91.6 16.9 70.4 68.2 19.9 11.0 31.2
95%CI 38.7 to 51.2 46.6 to 61.2 55.4 to 68.3 68.3 to 80.0 89 to 93.6 12.6 to 22.2 64.0 to 76.2 61.1 to 74.5 15.3 to 25.5 6.1 to 18.8 25.2 to 37.9
Ultrasound Whole body 98.0 98.9 93.0 84·2 95.4 78.2 70.9 82.3 78.1 79.8 71.1
95%CI 95.2 to 99.3 95.8 to 99.8 88.7 to 95.8 78.7 to 88.6 93.4 to 96.9 72.4 to 82.9 64.5 to 76.6 76.1 to 87.2 72.4 to 82.9 70.8 to 86.7 64.5 to 76.9
* Direct access: PCP can order the test without specific referral to secondary care
# Survey did not define which specific tests
^ Access to all individual body parts
Note: Exact 95%CI calculated for these figures
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Table 4: Average wait times for tests and results (weeks)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
X-ray
Test 0.56 0.57 0.56 0.55 0.54 0.95 1.37 1.43 0.79 0.91 0.82
Result 0.50 0.51 0.71 0.68 0.57 0.79 0.69 0.67 1.03 1.36 1.28
Total wait 1.06 1.08 1.27 1.23 1.11 1.74 2.06 2.10 1.82 2.27 2.10
95%CI 1.00 to 1.12 1.03 to 1.13 1.17 to 1.37 1.15 to 1.32 1.08 to 1.13 1.62 to 1.86 1.91 to 2.21 1.88 to 2.33 1.68 to 1.95 2.01 to 2.52 1.94 to 2.25
CT
Test 0.81 0.82 4·29 4·13 3·01 2.65 3.30 4.07 3.50 5.55 5.38
Result 0.52 0.52 1·02 0·96 0·78 0.98 0.85 1.02 1.39 1.77 1.44
Total wait 1.33 1.34 5·31 5·09 3·79 3.63 4.15 5.09 4.89 7.32 6.82
95%CI 1.24 to 1.42 1.24 to 1.44 4·87 to 5·75 4·69 to 5·49 3·59 to 3·68 3.33 to 3.93 3.88 to 4.43 4·60 to 5.57 4.60 to 5.18 6.57 to 8.07 6.35 to 7.29
MRI
Test 2.39 2.76 12.36 9.10 6.05 5.06 6·13 6.16 4.73 9.04 8.37
Result 0.60 0.56 1.39 1.36 0.88 1.12 1·05 1.24 1.52 2.55 1.56
Total wait 2.99 3.32 13.75 10.46 6.93 6.18 7·18 7.40 6.25 11.60 9.93
95%CI 2.64 to 3.34 2.84 to 3.80 13.12 to 14.38 9.82 to 11.09 6.61 to 7.25 5.66 to 6.69 6·72 to 7·63 6·73 to 8·06 5.90 to 6.60 10.63 to 12.57 8.32 to 30.55
Ultrasound
Test 1.11 1.26 4.30 5.88 1.80 2.71 3.99 3.76 3.73 6.38 6.08
Result 0.52 0.53 0.88 1.04 0.65 0.84 0.78 0.93 1.19 1.62 1.31
Total wait 1.63 1.79 5.18 6.92 2.46 3.55 4.77 4.69 4.93 8.00 7.39
95%CI 1.50 to 1.76 1.56 to 2.02 4.71 to 5.66 6.36 to 7.48 2.32 to 2.59 3.23 to 3.88 4.39 to 5.14 4.25 to 5·13 4.64 to 5.21 7.35 to 8.66 6.90 to 7.88
Upper GI endoscopy
Test 5.56 5·11 9.05 9·35 6·01 2·45 5.95 4.71 3.99 8.37 8.17
Result 1.38 0·83 1.49 1·82 1·36 0·77 0.95 1.46 1.35 1.58 1.67
Total wait 6.94 5·94 10.54 11·17 7·37 3·22 6.90 6.17 5.34 9.95 9.84
95%CI 6.35 to 7.53 5.24 to 6.64 9.85 to 11.72 10.49 to 11.84 1.03 to 7.72 2.97 to 3.47 6.45 to 7.35 5.63 to 6.72 5.02 to 5.66 9.16 to 10.74 9.18 to 10.50
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Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
Flexi sigmoidoscopy
Test 5.26 5.06 9.19 9.01 5.79 2.39 6·28 5·55 4·15 8·21 8.20
Result 1.38 0.87 1.55 1.91 1.34 0.76 0·94 1·54 1·46 2·04 1.66
Total wait 6.64 5.93 10.74 10.91 7.14 3.15 7·22 7·09 5·61 10·25 9.86
95%CI 6.06 to 7.22 5.21 to 6.65 10.03 to 11.44 10.20 to 11.63 6.75 to 7.48 2.89 to 3.41 6·76 to 7·65 6·53 to 7·65 5·26 to 5·95 9·35 to 11·15 9.21 to 10.50
Colonoscopy
Test 5.78 5.36 10.48 10.16 6.70 2.51 6.69 6.25 4.15 8.69 9.06
Result 1.38 0.84 9.61 1.91 1.37 0.78 0.98 1.54 1.56 2.00 1.70
Total wait 7.16 6.20 20.09 12.07 8.08 3.29 7.67 7.79 5.71 10.69 10.76
95%CI 6.54 to 7.78 5.49 to 6.91 19.13 to 21.06 11.38 to 12.75 7.72 to 8.43 3.01 to 3.58 7.20 to 8.13 7.16 to 8.41 5.33 to 6.08 9.80 to 11.58 10.08 to 11.44
Average wait time between a referral and first specialist appointment (Days)
Not available Not available 15.44 19.21 15.05 4.90 13.70 14.50 10.09 13.53 18.05
95%CI Not available Not available 14.10 to 16.78 17.56 to 20.87 14.25 to 15.85 4.78 to 5.32 12.72 to 14.68 13.32 to 15.68 9.91 to 10.28 12.62 to 14.44 16.75 to 19.35
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Table 5: Access to advice and faster tests (%)
Australia Canada Denmark Norway Sweden United Kingdom
NSW Victoria
British
Columbia Manitoba Ontario England
Northern
Ireland Wales
% agree /
strongly
agree
Can get
specialist
advice within
48 hours
Investigations 67.4 61.1 67.7 47.8 51.1 80.4 81.8 84.4 31.8 27.6 28.4
95%CI 61.6 to 73.2 54.1 to 68.1 61.6 to 73.8 41.3 to 54.3 47.1 to 55.1 75.5 to 85.3 76.8 to 86.8 79.3 to 89.5 26.0 to 37.6 19.2 to 36.0 22.4 to 34.4
Referrals 59.5 64.3 62.5 45.2 44.2 80.7 73.9 79.8 35.8 27.5 25.7
95%CI 53.5 to 65.5 57.5 to 71.1 56.2 to 68.8 38.7 to 51.7 40.2 to 48.2 75.9 to 85.5 68.2 to 79.6 74.2 to 82.4 29.9 to 41.7 19.1 to 35.9 19.9 to 31.5
Can arrange
faster access
to tests, if
suspicious
87.4 84.7 53.3 64·5 75.5 92.5 82.6 78.8 66.2 70.7 56.0
95%CI 83.3 to 91.5 79.6 to 89.8 46.8 to 59.8 58.3 to 70.7 72.0 to 79.0 89.3 to 95.7 77.7 to 87.5 73.1 to 84.5 60.3 to 72.1 62.2 to 79.2 49.4 to 62.6
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Scatterplots of vignettes and multiple regression analysis 90x127mm (300 x 300 DPI)
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Supplementary Table 1: Overview of PCP sampling methods used in each jurisdiction
Country Jurisdiction Primary care physician sampling
Number of PCPs invited
Crude response rate (%)
Invitation format Incentives Reminders
Australia New South Wales
PCPs were sampled from a commercial list (AMPCo).
2,246 11.3 A primer letter was sent by post. Followed by an invitation sent by post with a link to the survey and login details.
1st arm: $75 voucher (unconditional) 2nd arm: $75 voucher (conditional) 3rd arm: No incentive
Three reminders sent at four, six and eight weeks after the primary invitation.
Victoria 2,400 7.9 1st arm: $50 voucher (unconditional) 2nd arm: $50 voucher (conditional) 3rd arm: No incentive
Three reminders sent at two, four and six weeks after the primary invitation.
Canada British Columbia
PCPs were sampled from lists held by the British Columbia College of Family Physicians and the University of British Columbia Department of Family Practice.
Over 4,200 5.5 Email invitations Entered into a draw for an iPad (3 to give away) on completion of the survey
n/a
Manitoba PCPs were sampled from a list held by the College of Physicians and Surgeons of Manitoba.
500 45.6 A primer letter was sent by post· Followed by an invitation sent by post with a link to the survey and login details.
$10 coffee voucher sent with the letter
Two weeks after the primary invitation.
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on March 23, 2020 by guest. P
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MJ O
pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
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For peer review only
Country Jurisdiction Primary care physician sampling
Number of PCPs invited
Crude response rate (%)
Invitation format Incentives Reminders
Ontario PCPs were sampled from a list held by the College of Physicians and Surgeons of Ontario.
3,175 18.7 Postal invitations None Two reminders were
sent in January 2013.
Denmark PCPs were sampled from the national PCP organisation which represents all practising PCPs in Denmark.
1,000 25.5 Postal invitations and emails reminders
125 Danish Kroner to PCP on completion of the survey
Two weeks after the primary invitation.
Norway PCPs were sampled from the national PCP organisation.
2,000 11.5 Postal invitations None Three reminders sent five, 10 and 17 weeks after the primary invitation.
Sweden Random selection from a public list of GPs in the Uppsala-Orebro and Stockholm regions where there are 2,700 practising PCPs.
2,000 9.9 Postal invitations None Two reminders were
sent, one September
and another in October
2012.
United Kingdom
England A first tranche were sampled from a list of contact details from a commercial provider. The second tranche were sampled from a commercial list of PCPs
4,584 5.5 Email invitations £25 to PCP or charity on completion of the survey
Two weeks after the primary invitation.
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on March 23, 2020 by guest. P
rotected by copyright.http://bm
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MJ O
pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
ay 2015. Dow
nloaded from
For peer review only
Country Jurisdiction Primary care physician sampling
Number of PCPs invited
Crude response rate (%)
Invitation format Incentives Reminders
who had attended a training course (GP Update).
Northern Ireland
The first tranche were
sampled by email
invitation addressed to
Practice Managers in
each of the 353
practices in Northern
Ireland.
The second tranche
were sampled by the
sending of invitations
via surface mail to
those on a publically
available list of all GPs
working within this
jurisdiction.
1,163 11.2 Email invitations Entered into a draw for
an iPad on completion of
the survey
Two weeks after the
primary invitation.
Wales All PCPs in Wales were sampled.
1,861 11.7 A primer letter was sent by post. Followed by an invitation sent by post with a link to the survey and login details.
£50 voucher to PCP or charity donation on completion of the survey
Two weeks after invitation, and for the third tranche of invitations a second reminder two weeks after the first.
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pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
ay 2015. Dow
nloaded from
For peer review only
Supplementary Table 2: Details of ethics approvals in all jurisdictions
The table below sets out the details of ethical approvals received in all participating ICBP
jurisdictions.
Jurisdiction Ethics Board Reference number
Denmark Not required
Not required
Sweden Regionala etikprovningsnamnden i Linkkoping
EPN 2011:495/31
Victoria Human Research Ethics Committee at the
University of Melbourne
1238452.1
NSW Sydney Local Health District Ethics Review
Committee (RPAH zone)
X12-0230 and
HREC/12/RPAH/364
Norway Norwegian Social Science Data Services (NSD) 32176
Manitoba University of Manitoba Health Research Ethics Board
H2012:108
CancerCare Manitoba Research Resource Impact Committee
RRIC #20-2012
Ontario University of Toronto Research Ethics Board
27880
British Columbia University of British Columbia Behavioural Research Ethics Board
H11-02708
England National Research Ethics Service Committee South Central
11/SC/0373
Northern Ireland
Wales
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pen: first published as 10.1136/bmjopen-2014-007212 on 27 M
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nloaded from
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Supplementary Table 3: Choice of variables with reason for selection
Variable Hypothesised Effect
PCP status PCPs in regular in-hours practice better than other status (i.e. locums, out of hours only)
Gender None
Time since qualification PCPs with 10-20 years of experience better than those with 0-10 or 20-30 years
Place of qualification
Within vs. outside jurisdiction
Within jurisdiction is better as PCPs are more familiar with the health system and referral
pathways
Sole PCP in practice Sole PCPs isolated, fewer resources and may not refer as often
More than half of registered patients rural Rurality creates increased barriers to investigation or referral
Consultation length Longer consultation length has a positive impact on referrals and investigations
Time spent on cancer education in the last year More time spent in cancer specific education is better
Access to advice on investigations Access to advice is better
Access to advice on referrals Access to advice is better
Wait for first appointment Shorter is better
Length of time from ordering test to getting result in PCP Shorter is better
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Variable Hypothesised Effect
Lung vignette: Access to CXR/CT lung Access to either is better
Colorectal vignette: access to colonoscopy or abdo CT Access to either is better
Ovary vignette: access to TVUS/ US abdo/ abdo CT/pelvis CT Access to any one is better
Faster access if cancer suspected Faster access better
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