Family Practice, 2015, Vol. 32, No. 5, 525–532
doi:10.1093/fampra/cmv047
Advance Access publication 18 June 2015
Health Service Research
GP trainees’ in-consultation informationseeking: associations with human, paper and
electronic sources
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Parker Magina,b,*, Simon Morganb, Susan Wearnec,d, Amanda Tapleyb,
Kim Hendersonb, Chris Oldmeadowe,f, Jean Balle, John Scottb, Neil Spikeg,h,
Lawrie McArthuri and Mieke van Drielj
a
Discipline of General Practice, University of Newcastle, Newbolds Building, University Drive, Callaghan, NSW 2308,
General Practice Training Valley to Coast, Corner of Gavey and Frith Streets, Mayfield NSW 2304, cAcademic Unit
of General Practice, Australian National University Medical School, Canberra, ACT 2606, dDepartment of Health,
Health Workforce Division, Woden Town Centre, Canberra, ACT 2606, eClinical Research Design IT and Statistical
Support Unit (CReDITSS), Hunter Medical Research Institute, Newcastle, fSchool of Medicine and Public Health,
University of Newcastle University Drive, Callaghan, NSW 2308, gVictorian Metropolitan Alliance General Practice
Training, 15 Cato Street, Hawthorn, VIC 3122, hDepartment of General Practice, University of Melbourne, 200 Berkeley
Street, Carlton, VIC 3053, iAdelaide to Outback General Practice Training, Lower Level, 183 Melbourne Street, North
Adelaide, SA 5006 and jDiscipline of General Practice, School of Medicine, The University of Queensland, L8 Health
Sciences Building, Royal Brisbane and Women’s Hospital, Brisbane, Australia.
b
*Correspondence to Parker Magin, Discipline of General Practice, University of Newcastle, Newbolds Building, University
Drive, Callaghan, NSW 2308, Australia; E-mail: parker.magin@newcastle.edu.au
Abstract
Background. Answering clinical questions arising from patient care can improve that care and
offers an opportunity for adult learning. It is also a vital component in practising evidence-based
medicine. GPs’ sources of in-consultation information can be human or non-human (either hard
copy or electronic).
Objectives. To establish the prevalence and associations of GP trainees’ in-consultation
information-seeking, and to establish the prevalence of use of different sources of information
(human, hard copy and electronic) and the associations of choosing particular sources.
Methods. A cross-sectional analysis of data (2010–13) from an ongoing cohort study of Australian
GP trainees’ consultations. Once each 6-month training term, trainees record detailed data of 60
consecutive consultations. The primary outcome was whether the trainee sought in-consultation
information for a problem/diagnosis. Secondary outcomes were whether information-seeking was
from a human (GP, other specialist or other health professional) or from a non-human source
(electronic or hard copy), and whether a non-human source was electronic or hard copy.
Results. Six hundred forty-five trainees (response rate 94.3%) contributed data for 84 723
consultations including 131 583 problems/diagnoses. In-consultation information was sought for
15.4% (95% confidence interval = 15.3–15.6) of problems/diagnoses. Sources were: GP in 6.9% of
problems/diagnoses, other specialists 0.9%, other health professionals 0.6%, electronic sources
6.5% and hard-copy sources 1.5%. Associations of information-seeking included younger patient
age, trainee full-time status and earlier training stage, longer consultation duration, referring the
patient, organizing follow-up and generating learning goals. Associations of choosing human
information sources (over non-human sources) were similar, but also included the trainee’s training
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Family Practice, 2015, Vol. 32, No. 5
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organization. Associations of electronic rather than hard-copy information-seeking included the
trainee being younger, the training organization and information-seeking for management rather
than diagnosis.
Conclusion. Trainee information-seeking is mainly from GP colleagues and electronic sources.
Human information-sources are preferentially sought for more complex problems, even by these
early-career GPs who have trained in the ‘internet era’.
Key words: Australia, evidence-based medicine, family practice, general practitioners, information seeking behaviour, internet,
internship and residency, primary health care.
Methods
Answering clinical questions arising from patient care can improve
that care and also offers an opportunity for learning (1,2). With
clinical information overload, generating and answering clinical
questions is increasingly important (2). The number of physicians’
clinical questions generated increased markedly during 2009–13 in
a US study (3). Answering clinical questions is particularly important for generalist clinicians, and GPs generate more patient-specific
questions than do other specialists (4).
In-consultation ‘real-time’ answering of questions during patient
encounters is practicable (5) (and acceptable to patients (6)). But
clinical questions generated in-consultation by GPs and GP trainees
may be more likely answered post-consultation than in-consultation
(7,8). One study of GP trainees, however, found most questions
were answered in-consultation (5). The frequency of in-consultation
information-seeking of GPs has varied markedly between studies
(7,9–11), but has been less than that of GP trainees (5,8).
GPs’ sources of information in answering in-consultation questions are of particular importance. Human resources (other specialists, GP peers and GP supervisors/trainers) have been preferred over
written formats by GPs (12), and the initial uptake of electronic
sources was poor (9,13). But during 2009–13 the use of technological formats to answer physicians’ clinical questions increased more
rapidly than traditional sources in the USA (3).
Evidence for the associations of GPs’ information-seeking is
sparse. A recent systematic review has identified a need to research
such associations to inform development of information-retrieval
systems personalized to the clinician’s characteristics (1). It also
identified evidence gaps regarding information-seeking behaviours
pertaining to patient subpopulations of interest such as complex and
aging patients (1).
The aim of this analysis was to establish the prevalence of information-seeking in general practice consultations. We also sought to
establish the sources of information accessed and the purpose of
that information-seeking (to inform diagnosis or management). In
response to identified evidence gaps, we aimed to establish clinician,
patient and practice associations of choice of information-source.
We have previously specifically examined GP trainees’ informationseeking from their supervisor (trainer/preceptor) (14). In the current
analysis we sought to establish the prevalence and associations of
trainees’ information-seeking from all sources. We also sought to
establish the prevalence and associations of use of different information-sources (human, electronic and hard copy).
Our analysis focusses on GP trainees, for whom ‘acquiring information’ is a key component of their vocational training in evidencebased-medicine (2). Furthermore, familiarity of use from training
and early clinical practice are dominant influences on later resource
use by established GPs (12).
This analysis took place within the Registrar Clinical Encounters in
Training (ReCEnT) project. ReCEnT is an ongoing multi-site cohort
study of GP registrars (trainees). Participants included in this analysis are GP trainees of four of Australia’s 17 GP Regional Training
Providers (RTPs) across four Australian states. RTPs are government-funded, not-for-profit, geographically-defined GP vocational
training organizations.
The methodology has been described elsewhere (15). GP trainees
collect data once during each 6-month general practice training term
(12 months for part-time trainees). This results in data collection on
three or four occasions during training.
Trainee demographics and characteristics of practices in which
they are working are recorded by each trainee, each term.
Trainees then record, each term, the details of 60 consecutive clinical consultations contemporaneously on a paper-based
encounter form.
Data collection is designed to reflect a ‘normal’ week of general
practice. Thus, consultations in a specialized clinic, e.g. vaccination
clinic are excluded. Only office-based (not home visits or nursing
home visits) consultations are included.
Outcome factors
The primary outcome factor was whether the trainee sought ‘realtime’ in-consultation information during the consultation.
This information was recorded as being sought from another
GP (including the trainee’s supervisor), a non-GP specialist, another
health professional, electronic sources or hard-copy sources.
Secondary outcomes were:
1. Whether information sought was from a human source (GP,
other specialist or other health professional) or from a nonhuman source (electronic or hard copy)
2. Whether a non-human source was electronic or hard copy
Whether in-consultation information was sought for diagnosis, for
management, or for both was also recorded as was the problem/
diagnosis for which information was sought. Problems/diagnoses
were coded according to the International Classification of Primary
Care, second edition (ICPC-2 plus) (16). ICPC-2plus classifies problems/diagnoses into 17 Chapters—16 body system/discipline-specific
Chapters and a ‘General and Unspecified’ Chapter.
Independent variables
Independent variables related to trainee, patient, practice and
consultation.
Trainee factors were age, gender, training term, place of medical qualification (Australia/international), full-time/part-time status,
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Introduction
527
GPs’ in-consultation information-seeking
Statistical analysis
This was a cross-sectional analysis of consultations from eight
rounds of the longitudinal ReCEnT study, 2010–13.
The unit of analysis was the individual problem/diagnosis rather
than the consultation, as it is for individual problems that information is sought.
The proportion of problems for which trainees sought in-consultation information was calculated with 95% confidence intervals
(CIs). The proportions of problems for which trainees sought in-consultation information from a supervisor, a non-GP specialist, another
health professional, an electronic source, or a hard-copy source were
calculated with 95% CIs.
Of those problems for which the trainee sought information, the
proportions for which information was for diagnosis, management,
or both diagnosis and management, were calculated with 95% CIs.
To test associations of trainees seeking in-consultation information, simple and multiple logistic regression were used within a
generalized estimating equations (GEE) framework to account for
clustering of patients within trainees. All variables with a P-value
less than 0.2 and relevant effect size in the univariate analysis were
included in the multiple regression models.
Further logistic regression models within GEEs were constructed
with the outcome factor ‘human or non-human source of information’ (for problems/diagnoses for which information was sought)
and with the outcome factor ‘electronic or hard-copy source of information’ (for problems/diagnoses for which information was sought
from non-human sources). Data for problems/diagnoses for which
information was sought from more than one category (human and
non-human, electronic and hard copy, respectively) were excluded
from these further analyses.
Statistical analyses used STATA 13.1 and SAS v9.4. P-values <
0.05 were considered statistically significant.
Results
A total of 645 trainees (response rate 94.3%) contributed data
for 1426 trainee-rounds, and 84 723 consultations including 131
583 problems/diagnoses. Table 1 displays trainee and practice
characteristics.
Prevalence and types of information-seeking
In-consultation information was sought for 20 328 [15.4% (95%
CI = 15.3–15.6)] problems/diagnoses [in 17 440 (20.6% (95%
Table 1. Characteristics of GP trainees and practices of four Regional Training Providers participating in ReCEnT study data collection,
2010–13
Variable
Trainee variables (n = 645)
Trainee gender
Qualified as a doctor in Australia
Trainee age (years)
Trainee-term or practice-term variables (n = 1426)
Trainee training term
Trainee works fulltime
Trainee worked at the practice previously
Does the practice routinely bulk bill
Number of GPs working at the practice
Rurality of practice
SEIFAa index (decile) of practice
a
Socio-economic Index for Area Relative Index of Disadvantage.
Class
n, % (95% CIs) or mean (SD)
Male
Female
No
Yes
Mean (SD)
220, 34.1% (30.4–37.8)
425, 65.9% (62.2–69.6)
155, 24.4% (21.1–27.8)
480, 75.6% (72.2–78.9)
32.8 (6.6)
Term 1
Term 2
Term 3
Term 4
No
Yes
No
Yes
No
Yes
1–5
≥6
Major city
Inner regional
Outer regional or remote
Mean (SD)
557, 39.1% (36.5–41.6)
488, 34.2% (31.8–36.7)
306, 21.5% (19.3–23.6)
75, 5.3% (4.1–6.4)
302, 21.7% (19.5–23.8)
1091, 78.3% (16.2–80.5)
994, 70.6% (68.3–73.0)
413, 29.4% (27.0–31.7)
1179, 83.4% (81.5–85.4)
234, 16.6% (14.6–18.5)
454, 32.5% (30.1–35.0)
941, 67.5% (65.0–69.9)
827, 58.0% (55.4–60.6)
424, 29.7% (27.4–32.1)
175, 12.3% (10.6–14.0)
5.4 (2.8)
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whether the trainee had previously worked at the practice or had
prior health qualifications or post-graduate qualifications, and the
trainee’s RTP.
Patient factors were age, gender, Aboriginal or Torres Strait
Islander status, non-English speaking background, whether the
patient was new to the practice, and new to the trainee.
Practice factors were rurality/urbanicity, practice size (fulltime equivalent GPs), if the practice had internet access at the
consultation desk, and if the practice routinely bulk-bills (that
is, there is no financial cost to the patient for the consultation).
Practice postcode was used to define the Australian Standard
Geographical Classification-Remoteness Area classification (the
degree of rurality) of the practice location (17) and to define the
practice location’s Socioeconomic Index for Area Relative Index
of Disadvantage (18).
Consultation factors were whether the problem/diagnosis
was a chronic disease (classified according to the methodology of
O’Halloran et al. (19)), whether the problem/diagnosis was new, and
the number of problems addressed in the consultation. Other consultation variables were consultation duration, whether imaging was
ordered, pathology was ordered, referrals were made, follow-up was
organized and learning goals were generated.
528
CIs = 20.3–20.8)) consultations]. The sources of information were:
GP in 6.9% (95% CI = 6.8–7.1) of problems/diagnoses, other specialists 0.9% (95% CI = 0.9–1.0), other health professionals 0.6%
(95% CI = 0.5–0.6), electronic sources 6.5% (95% CI = 6.4–6.6),
hard-copy sources 1.5% (95% CI = 1.4–1.5) and other sources
0.7% (95% CI = 0.7–0.8). It should be noted that trainees could
seek information from more than one source for a problem.
Information was sought in 9.9% (95% CI = 9.5–10.4) of
instances for diagnosis, in 61.3% (95% CI = 60.6–62.0) for management, and in 28.8% (95% CI = 28.1–29.5) for both diagnosis
and management.
The most common ICPC-2 chapters for which information
was sought were Skin (16.0%), General and Unspecified (12.7%),
Musculoskeletal (10.8%) and Respiratory (10.7%).
The relationships of information-seeking to independent variables
are presented in Table 2.
The logistic regression model with outcome factor ‘Sought any
in-consultation information’ is presented in Table 3. Significant
patient associations of information-seeking were younger age and
male gender, and not being new to the practice or new to the trainee.
Trainee associations were younger age, full-time status, and earlier
training stage. The practice-level association was not having internet at the desk. Consultation-level associations were the problem/
diagnosis being new, longer consultation duration (though a lesser
number of problems were dealt with), referring the patient, organizing follow-up and generating learning goals.
Associations of information-seeking: human versus
non-human sources
The logistic regression with outcome factor ‘Sought in-consultation
information from a human source’ (when information was sought)
is presented in Table 4. Significant patient associations of information-seeking from a human (rather than non-human) source were
age (younger or older age range than 15–34), male gender and the
patient not being new to the practice or new to the trainee. Trainee
associations were earlier stage of training and the RTP trained
with. Consultation associations included the problem/diagnosis not
being new, longer consultation duration (though a lesser number of
problems were dealt with in the consultation), referring the patient,
organizing follow-up, and generating learning goals. The information or advice being for diagnosis rather than management was also
associated with a human source of information.
Associations of information-seeking: electronic
versus hard-copy sources
The logistic regression with outcome factor ‘Sought in-consultation electronic information’ (when advice was sought from a non-human source)
is presented in Table 5. Significant associations of seeking electronic
information included the trainee being younger, the RTP trained with,
and information being sought for management rather than diagnosis.
Discussion
Main findings and comparison with previous
literature
Information-seeking was common in our study: for 15.4% of all
problems/diagnoses and in 20.6% of consultations. Comparisons
can be made with other studies that have elicited in-consultation
information-seeking contemporaneously. Our methodology is not
directly comparable, but it can be established from previous papers
that US and Australian GPs sought answers to questions at 6.8 to
16.2 answers per 100 consultations (9–11) but that Spanish GPs
sought only 1.7 answers per 100 consultations (7). In studies of US
family medicine trainees, 20.7 (8) and 113.7 answers (5) were sought
per 100 consultations. The variability in prevalence may reflect differences in practice context (for example, the comparatively short
Spanish consultation duration) (7) as well as differences in experience between trainees and established GPs.
The prevalence of information-seeking in our study was greater
than in studies of established GPs. This is consistent with the
relative clinical inexperience of our trainee participants and the
proposed central importance of information-seeking skills in GP
training (2).
In our study, information was sought in 9.9% of instances
for diagnosis, in 61.3% for management, and in 28.8% for both
diagnosis and management. In a Spanish study (with short consultation-time and few in-consultation questions), of GPs’ clinical
questions generated, 53% were for diagnosis and 33% were for
treatment or management (7). But in a more comparable study of
US GPs, 73% of questions were for treatment and 27% for diagnosis (9). The emphasis on management compared to diagnosis in
our study may reflect information-seeking on management often
being relatively straightforward (and thus easily addressed in-consultation) once a diagnosis is established. Information regarding
diagnosis, often a more complex cognitive task than selection of
treatment, may be less satisfactorily addressed in ‘real-time’, inconsultation. Out-of-consultation information-seeking (not measured in this study) may often be appropriate. It should also be
noted that we found generation of learning goals to be strongly
associated with in-consultation information-seeking—suggesting
a more complex learning process as well as utilitarian dealing with
a problem in the consultation.
Dermatology and musculoskeletal were the most common
ICPC-2 chapters for information-seeking. This may reflect the mismatch of limited hospital-based training exposure but high general
practice prevalence of dermatological and musculoskeletal problems in Australia. In Canadian GP training, these were only the fifth
and sixth most common disciplines prompting information-seeking
(20).
Regarding source of information, for 8.4% of problems/diagnoses it was a human source, for 6.5% an electronic source, and
for 1.5% a hard-copy source. A study of Canadian GP trainees (20)
found that in 65.5% of instances information-seeking was from
human sources (mostly the trainee’s supervisor), 20.7% from electronic sources and 14.0% from hard-copy sources. In a US study
of family medicine trainees 47.4% of questions were answered by
human sources, 25.9% by electronic sources and 22.9% by hardcopy sources (8). Human sources were also deemed to be of more
clinical utility than electronic or hard-copy sources in a Canadian
trainee study (20). There are no comparable studies of sources
of information of established GPs to provide context for these
seemingly high proportions of human sources. It should be noted
that trainees are inexperienced in in-consultation informationsearching as well as in clinical practice and will usually have ready
recourse to advice and information from a supervisor/trainer/preceptor. But in an Australian qualitative study, experienced GPs as
well as trainees highly valued human resources—though for GPs
it was non-GP specialist colleagues and for trainees it was their
supervisor (12).
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Associations of information-seeking: all sources
Family Practice, 2015, Vol. 32, No. 5
529
GPs’ in-consultation information-seeking
Table 2. Associations of seeking any in-consultation information with all independent variables
Sought assistance
Variable
Class
No (n = 111 255)
Yes (n = 20 328)
P
Patient age group
0–14
15–34
35–64
65+
Male
Female
No
Yes
No
Yes
Male
Female
Part time
Full time
Term1
Term2
Term3
Term4
No
Yes
No
Yes
No
Yes
No
Yes
Small (<6 GPs)
Large (>5 GPs)
No
Yes
Major city
Inner regional
Outer regional, remote and very remote
1
2
3
4
No
Yes
Patient known to trainee
New to trainee
New to Practice
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
Mean (SD)
Mean (SD)
Mean (SD)
Mean (SD)
14 254 (81%)
27 857 (84%)
45 607 (86%)
21 789 (86%)
40 240 (84%)
68 182 (85%)
104 390 (85%)
1205 (82%)
99 734 (85%)
6547 (82%)
37 630 (86%)
73 625 (84%)
24 058 (85%)
84 713 (84%)
41 759 (79%)
38 389 (87%)
25 000 (89%)
6107 (91%)
76 564 (83%)
33 236 (88%)
25 434 (81%)
84 092 (86%)
97 698 (85%)
12 320 (85%)
83 029 (85%)
27 381 (83%)
35 949 (84%)
72 896 (85%)
92 093 (85%)
18 234 (84%)
65 060 (85%)
32 201 (83%)
13 994 (86%)
40 420 (85%)
13 416 (87%)
10 930 (81%)
46 489 (84%)
2680 (87%)
108 575 (84%)
48 700 (85%)
52 200 (84%)
7200 (82%)
56 383 (86%)
54 872 (83%)
85 992 (85%)
24 900 (84%)
92 845 (85%)
18 410 (82%)
103 767 (85%)
7488 (77%)
64 313 (88%)
46 942 (80%)
101 309 (90%)
9946 (53%)
99 422 (86%)
11 833 (75%)
32.9 (6.7)
5.4 (2.8)
17.9 (9.4)
2.0 (1.0)
3372 (19%)
5248 (16%)
7685 (14%)
3625 (14%)
7675 (16%)
12 113 (15%)
19 145 (15%)
265 (18%)
18 081 (15%)
1423 (18%)
6264 (14%)
14 064 (16%)
4299 (15%)
15 552 (16%)
10 845 (21%)
5850 (13%)
3060 (11%)
573 (8.6%)
15 362 (17%)
4681 (12%)
6004 (19%)
13 968 (14%)
17 880 (15%)
2245 (15%)
14 570 (15%)
5491 (17%)
6733 (16%)
13 279 (15%)
16 650 (15%)
3537 (16%)
11 436 (15%)
6523 (17%)
2369 (14%)
7130 (15%)
2031 (13%)
2504 (19%)
8663 (16%)
410 (13%)
19 918 (16%)
8652 (15%)
9582 (16%)
1558 (18%)
8864 (14%)
11 464 (17%)
15 611 (15%)
4682 (16%)
16 308 (15%)
4020 (18%)
18 129 (15%)
2199 (23%)
8697 (12%)
11 631 (20%)
11 625 (10%)
8703 (47%)
16 310 (14%)
4018 (25%)
33.5 (6.9)
5.2 (2.8)
21.7 (10.9)
1.8 (0.9)
<0.0001
Patient gender
ATSI
NESB
Trainee full-time or part-time
Training term/post
Worked at practice previously
Qualified as doctor in Australia
Previous health qualifications
Post grad medical qualifications
Practice size
Practice routinely bulk bills
Rurality
RTP
Internet at desk
Patient/practice status
New problem
Chronic condition
Pathology ordered
Imaging ordered
Follow-up ordered
Learning goals generated
Referral ordered
Trainee age
SEIFA index
Consultation duration
Number of problems
0.2740
0.3332
0.0948
0.0198
<0.0001
<0.0001
0.0003
0.8453
0.3352
0.4464
0.2679
0.0063
0.0194
0.0918
0.0100
<0.0001
0.0306
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.0012
0.8322
<0.0001
<0.0001
SEIFA index, socio-economic index for area relative disadvantage; ATSI, Aboriginal and Torres Strait Islander; NESB, Non-English speaking background.
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Trainee gender
<0.0001
Family Practice, 2015, Vol. 32, No. 5
530
Table 3. Results of logistic regression with outcome ‘any in-consultation information sought’
Univariate
Adjusted
Class
OR (95% CI)
P
OR (95% CI)
P
Patient age group
Referent 15–34
0–14
35–64
65+
Female
Female
Part time
Term2
Term3
Term4
Yes
Yes
Inner regional
Outer regional/ remote/ very remote
2
3
4
Yes
New to practice
New to trainee
Yes
Yes
Yes
Yes
Yes
1.22 (1.16–1.29)
0.91 (0.87–0.94)
0.88 (0.83–0.94)
0.93 (0.90–0.96)
1.16 (0.97–1.38)
0.84 (0.72–0.97)
0.63 (0.58–0.69)
0.52 (0.46–0.59)
0.39 (0.30–0.51)
0.70 (0.65–0.77)
0.68 (0.55–0.84)
1.22 (1.07–1.39)
1.26 (1.02–1.55)
0.80 (0.62–1.03)
1.30 (1.00–1.70)
1.04 (0.87–1.25)
1.59 (0.93–2.72)
1.10 (1.02–1.19)
0.98 (0.94–1.03)
1.30 (1.25–1.35)
1.19 (1.14–1.24)
1.65 (1.57–1.72)
6.68 (6.11–7.31)
1.91 (1.81–2.02)
0.97 (0.95–0.99)
1.03 (1.03–1.04)
0.77 (0.75–0.80)
<0.0001
<0.0001
<0.0001
<0.0001
0.0948
0.0198
<0.0001
<0.0001
<0.0001
<0.0001
0.0003
0.0032
0.0344
0.0869
0.0519
0.6406
0.0918
0.0165
0.4374
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.0012
<0.0001
<0.0001
1.21 (1.14–1.29)
0.94 (0.90–0.99)
1.02 (0.95–1.08)
0.95 (0.92–0.99)
1.06 (0.89–1.26)
0.86 (0.75–0.98)
0.67 (0.60–0.75)
0.61 (0.53–0.70)
0.44 (0.35–0.56)
0.97 (0.87–1.09)
0.95 (0.76–1.19)
1.03 (0.92–1.17)
0.89 (0.70–1.14)
0.94 (0.69–1.28)
1.26 (0.95–1.68)
1.21 (1.00–1.47)
0.76 (0.62–0.94)
0.86 (0.79–0.94)
0.95 (0.91–1.00)
1.21 (1.17–1.26)
0.95 (0.90–1.00)
1.27 (1.20–1.34)
5.54 (5.07–6.05)
1.33 (1.25–1.41)
0.98 (0.97–1.00)
1.04 (1.04–1.04)
0.72 (0.69–0.75)
<0.0001
0.0146
0.6127
0.0112
0.4850
0.0223
<0.0001
<0.0001
<0.0001
0.6419
0.6646
0.5839
0.3578
0.6775
0.1071
0.0505
0.0093
0.0005
0.0296
<0.0001
0.0351
<0.0001
<0.0001
<0.0001
0.0179
<0.0001
<0.0001
Patient gender
Trainee gender
Trainee full time or part time
Training term/post
Referent term 1
Worked at practice previously
Qualified as doctor in Australia
Rurality
RTP
Referent RTP 1
Internet at desk
Patient/practice status
Referent patient known to trainee
New problem
Pathology ordered
Follow-up ordered
Learning goals
Referral ordered
Trainee age (years)
Consultation duration
Number of problems
OR, odds ratio.
Associations of information-seeking
Regarding associations of information-seeking, there is little literature with which to compare our results. Ely et al., however, contrary
to our results, found patient female gender and older age to be associated with information-seeking. Theirs’ was a study of established
US GPs’ and these associations were with question-asking rather
than information-seeking (10). While we found no association with
rurality, urban GPs sought more information than rural GPs in
another US study (9). Our finding that full-time status was associated with more in-consultation information-seeking may possibly
indicate more out-of-consultation information-seeking by part-time
trainees (who would possibly have more opportunity for this).
The association of information-seeking with not having internet
access at the consultation desk is surprising, but we also found that
having internet access isn’t significantly associated with use of electronic versus hard-copy resources. Most trainees had internet access,
so the clinical significance is limited. But these results may reflect many
electronic resources used by trainees being incorporated in their general practice-specific computer software rather than accessed online.
Associations with consultation duration, organizing follow-up,
making referrals and fewer other problems being dealt with in the
consultation likely reflect the intrinsic difficulty or complexity of the
problem (or the difficulty the particular trainee has with it). As also
does the generation of learning goals for further information-seeking
out-of-consultation.
We found that seeking information from a human rather than nonhuman source was associated with both younger and older patient agegroups (than the referent: 15–34 years). It may be that young adult
patients in general present less complex clinical challenges than paediatric or older adults and that these challenges can be simply addressed
via books or electronic sources rather than calling on the expertise of
supervisors or other specialists. Similarly, associations with consultation duration, organizing follow-up, making referrals, generating learning goals and fewer other problems being dealt with in the consultation
likely reflect the intrinsic difficulty or complexity of the problem. The
association of information-seeking from a person with the problem
involving diagnosis rather than treatment would, again, be consistent
with information-seeking for more complex clinical challenges being
directed to human rather than non-human sources. But as the trainee
becomes more senior, they are better able to cope with complex clinical scenarios. Consistent with this proposition, we found decreasing
reliance on human sources and increasing ‘self-directed’ informationseeking from books or electronic sources in the association of information-seeking from human sources with later stages of training.
Information-seeking from a human source being associated with
the problem being old and the patient known to the practice may
reflect preferential information-seeking from another GP in the practice who had been involved in the patient’s previous care and, so,
was familiar with the patient and their problems. The difference in
information-seeking from a human source that we found between
RTPs suggests structural differences in supervisory arrangements, or
differences in supervisory ‘culture’ between RTPs.
Regarding information-seeking from an electronic rather than
hard-copy source, the association with younger trainee age is
expected. The association with treatment rather than diagnosis may
reflect treatment being more likely to change with time (thus requiring more up-to-date electronic sources), with the principles of diagnosis being more stable and less rapidly changing than treatment.
The reason for the difference between RTP is not obvious, but may
reflect resourcing or training in use of electronic resources.
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Variable
531
GPs’ in-consultation information-seeking
Table 4. Results of logistic regression with outcome ‘information from a human source’ (when in-consultation information sought)
Univariate
Adjusted
Class
OR (95% CI)
P
OR (95% CI)
P
Patient age group
Referent 15–34
0–14
35–64
65+
Female
Yes
1.08 (0.99–1.19)
1.21 (1.13–1.30)
1.52 (1.37–1.69)
0.89 (0.84–0.95)
0.92 (0.81–1.04)
0.0901
<0.0001
<0.0001
0.0004
0.1946
1.24 (1.11–1.40)
1.15 (1.04–1.27)
1.57 (1.38–1.79)
0.88 (0.82–0.96)
0.91 (0.77–1.06)
0.0003
0.0046
<0.0001
0.0020
0.2300
Term2
Term3
Term4
Yes
0.73 (0.65–0.81)
0.51 (0.44–0.60)
0.47 (0.36–0.61)
0.77 (0.67–0.87)
<0.0001
<0.0001
<0.0001
<0.0001
0.69 (0.59–0.81)
0.55 (0.45–0.67)
0.38 (0.25–0.57)
0.98 (0.81–1.17)
<0.0001
<0.0001
<0.0001
0.7898
Yes
1.16 (0.95–1.42)
0.1462
1.19 (0.91–1.55)
0.2011
2
4
5
New to practice
New to trainee
1.50 (1.15–1.95)
1.18 (0.89–1.56)
1.60 (1.33–1.93)
0.87 (0.77–0.98)
0.78 (0.73–0.84)
0.0025
0.2419
<0.0001
0.0257
<0.0001
1.62 (1.14–2.30)
1.02 (0.74–1.39)
1.48 (1.16–1.88)
0.75 (0.65–0.88)
0.78 (0.72–0.85)
0.0070
0.9240
0.0013
0.0004
<0.0001
Yes
Yes
Yes
Yes
Yes
Diagnosis
0.84 (0.79–0.90)
1.80 (1.62–2.00)
1.15 (1.08–1.23)
1.55 (1.44–1.68)
2.39 (2.17–2.63)
1.75 (1.52–2.01)
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.81 (0.75–0.87)
1.46 (1.29–1.66)
1.05 (0.97–1.13)
1.28 (1.16–1.41)
2.02 (1.78–2.28)
1.99 (1.70–2.32)
<0.0001
<0.0001
0.2462
<0.0001
<0.0001
<0.0001
Diagnosis & management
2.11 (1.86–2.39)
0.97 (0.96–0.99)
1.04 (1.03–1.04)
0.96 (0.92–1.00)
<0.0001
0.0002
<0.0001
0.0538
2.10 (1.84–2.40)
1.00 (0.98–1.01)
1.04 (1.03–1.04)
0.85 (0.81–0.90)
<0.0001
0.6786
<0.0001
<0.0001
Patient gender
Non-English speaking
background
Training term/post
Referent term 1
Worked at practice
previously
Qualified as doctor in
Australia
RTP
Referent RTP 1
Patient/practice status
Referent patient
known to trainee
New problem
Imaging ordered
Follow-up ordered
Learning goals generated
Referral ordered
Sought help for
diagnosis/management
Referent management
Trainee age (years)
Consultation duration
Number of problems
OR, odds ratio.
Table 5. Results of logistic regression with outcome ‘information from an electronic source’ (when in-consultation information sought from
a non-human source)
Univariate
Adjusted
Variable
Class
OR (95% CI)
P
OR (95% CI)
P
Patient age group
Referent 15–34
0–14
35–64
65+
Yes
Yes
Inner regional
Outer regional/
remote/ very remote
2
3
4
Yes
Yes
Yes
Diagnosis
0.87 (0.73–1.04)
1.01 (0.88–1.16)
1.27 (1.05–1.53)
1.65 (1.19–2.30)
0.54 (0.35–0.84)
0.56 (0.37–0.84)
1.23 (0.26–5.78)
0.1369
0.9160
0.0150
0.0027
0.0062
0.0048
0.7965
0.83 (0.69–1.01)
0.98 (0.84–1.15)
1.15 (0.95–1.40)
1.17 (0.81–1.71)
0.55 (0.35–0.87)
0.85 (0.59–1.22)
2.02 (0.56–7.34)
0.0644
0.8404
0.1459
0.4052
0.0098
0.3744
0.2862
1.27 (0.80–2.04)
1.36 (0.86–2.15)
4.26 (3.02–6.00)
1.24 (1.07–1.44)
0.75 (0.61–0.92)
0.77 (0.59–1.01)
0.66 (0.52–0.84)
0.3131
0.1923
<.0001
0.0034
0.0069
0.0545
0.0006
0.84 (0.40–1.76)
1.05 (0.54–2.03)
2.70 (1.82–3.99)
1.14 (0.97–1.35)
0.73 (0.57–0.93)
0.84 (0.67–1.06)
0.65 (0.50–0.84)
0.6517
0.8956
<.0001
0.1126
0.0126
0.1367
0.0012
Diagnosis &
management
0.78 (0.63–0.97)
0.0223
0.80 (0.64–1.00)
0.0477
0.94 (0.92–0.96)
1.10 (1.01–1.20)
<.0001
0.0297
0.96 (0.94–0.99)
1.06 (0.96–1.17)
0.0026
0.2720
Qualified as doctor in Australia
Previous health qualifications
Rurality
Referent major city
RTP
Referent RTP1
Chronic condition
Imaging ordered
Learning goals
Sought help for diagnosis and/
or management
Referent management
Trainee age (years)
Number of problems
OR, odds ratio.
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Variable
Family Practice, 2015, Vol. 32, No. 5
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in-consultation question or contributed to patient care. Our large
sample size also raises the issue of clinical as opposed to statistical
significance, and the effect sizes of particular associations we have
found should be considered when assessing their impact.
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Conclusion
We found that trainee GPs access information within more than onefifth of consultations. They mainly seek information from GP colleagues and electronic sources. Human sources of information seem
to be preferentially sought for more complex problems, even by these
early-career GPs who have trained in the ‘internet era’. Implications
for practice structure and workload are in the time-demands on
the colleagues consulted and in provision of adequate and appropriate resources to meet information-seeking needs. More broadly,
the patterns and associations of information-seeking of these earlycareer GPs may indicate future resource needs in the evolving area
of GP information-seeking for patient care. For example, electronic
resources, especially those providing information on up-to-date therapy and information on particular topics (in Australia, for example,
perhaps especially dermatology and musculoskeletal medicine).
But even as the future composition of GP practitioners increasingly reflects the facility with information technology of our trainee
study population, the complexity of practice is likely to increase
(with, for example, greater complex multimorbidity). Our findings
suggest access to expert human information sources must still be
available for these complex problems, irrespective of technological
advances in electronic information-sources.
As our study was confined to GP trainees, future research including established GPs may explore the applicability of our findings to
a clinically more experienced (but possibly less information technology-literate) practitioner population.
Acknowledgements
SW’s views are not necessarily those of the Department of Health.
Declarations
Funding: 2014 General Practice Education and Training (GPET) research
grant (D14/11354). The participating educational organizations: General
Practice Training Valley to Coast, the Victorian Metropolitan Alliance, General
Practice Training Tasmania and Adelaide to Outback GP Training Program are
funded by the Australian Government.
Ethical approval: University of Newcastle Human Research Ethics Committee,
Reference H-2009-0323.
Conflict of interest: none.
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Strengths and limitations