Electronic Records for General Practice
Where we Are, Where we should Head to Improve Them
Federico Cabitza
1
, Francesco Del Zotti
2
and Paolo Misericordia
3
1
Dipartimento di Informatica (DISCo), Università degli Studi di Milano-Bicocca, V.le Sarca 336, Milano, Italy
2
NetAudit, Verona, Italy
3
Centro Studi FIMMG, Piazza Guglielmo Marconi 25, Roma, Italy
Keywords: Electronic Medical Records, General Practice, Quality Evaluation, Online Questionnaire, Attitude Survey.
Abstract: In this paper we present the findings of a country-wide survey that was aimed at getting a comprehensive
picture of the current level of adoption and appropriation of Electronic Medical Records (EMRs) by General
Practitioners (GPs). In this survey, which collected the responses from 800 Italian GPs coming from all over
the country and exhibiting different experience and ICT skills, we investigated the level of current
satisfaction of users with respect to two classes of functional and non-functional features of current EMRs,
namely “core” and “advanced” ones. We also tried to detect which of these features are valued most highly
by the current EMR users in order to inform prospective users, EMR vendors and policy makers in the
eHealth domain. We also focused on the impact that digitization has had so far on General Practice, as it is
perceived from the perspective of the front-line users (i.e., doctors). Finally we also addressed how the use
of ICT could change in the near future as a tool to facilitate doctor patient communication and collaboration.
1 MOTIVATIONS AND
BACKGROUND
General Practice is one of the professions that in the
last years have been affected more deeply by a
process of continuous digitization of its document-
and communication-related tasks (Benson, 2002;
Delaney, 2010; Dobrev et al., 2008; Purves, 1996).
The Electronic Medical Record (EMR) is the main
tool at the centre of this process of digitization, and
therefore it has so far received the interest of
hundreds of scholarly studies aimed at
understanding the nature of its role in changing
medical work, e.g., (Hassey, 2001; Hippisley-Cox,
2003; Porcheret et al., 2004; Treweek, 2003). For
this reason, we also aim our research to get a general
picture of how General Practitioners (GPs) perceive
their electronic records in 2013, that is in an age
when new widespread portable devices have rebuilt
the concept of mobility, the Web 2.0, and the Social
Media it helps spreading, have changed expectations
in patients and users in general, and data exchange
and interoperability have finally come of age,
showing unprecedented results and reliability. In this
context of new technologies in place and “old” ones
that have reached full maturity and convinced even
the so called “late majority” of potential users, we
want to assess: their level of adoption (i.e., use); the
perceived appropriation by their users (e.g., how
they fit their needs), and the satisfaction of the GPs.
In what follows we will then report on an attitude
user study that involved a vast sample of primary
care doctors and probed them on: satisfaction and
usefulness of both traditional and more advanced
aspects of their digitial media; the impact they
believe digitization has had on their medical
practice; what areas of improvement ICT designers
and developers should focus on to provide them with
better tools; the functionalities that they perceive as
most useful; and lastly, how they currently use ICT
to communicate and collaborate with their patients
and how they intend to use it in the near future.
We believe that iterating this kind of initiatives on a
periodic basis could allow ICT designers and policy
makers to better fit the real needs of the end users
involved and hence to affect quality of care, user
satisfaction and ICT appropriation positively.
2 METHODS
To address the research question mentioned above,
535
Cabitza F., Del Zotti F. and Misericordia P..
Electronic Records for General Practice - Where we Are, Where we should Head to Improve Them.
DOI: 10.5220/0004924805350542
In Proceedings of the International Conference on Health Informatics (HEALTHINF-2014), pages 535-542
ISBN: 978-989-758-010-9
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
we focused on three main dimensions of analysis:
1. the impact of EMRs on the work of the GPs,
2. the quality perceived by GPs in regard to their
EMR, and
3. the use of communication technology by GPs.
The perceived impact of EMRs on general
practice has been articulated in relation to typical
work dimensions, like productivity,
knowledgeability, collaboration, stress and
appropriateness; and also in terms of the extent ICT
supports typical phases (or “concerns”) of medical
work, like “prevention”, “examination”, “diagnosis”,
“treatment”, “follow-up” and “audit/evaluation”.
These latter items have been grouped in a specific
construct called “QSM”. The perceived quality of
EMRs has been analysed in regard to three aspects:
i) overall recommendability; ii) satisfaction, and iii)
perceived utility. Recommendability is considered in
terms of Net Promoter Score (Keiningham et al.,
2007). Satisfaction has been further articulated in
terms of two constructs (set of items): QSC, QSA.
The construct called “QSC” regards perceived
satisfaction for those aspects (i.e., functions and
attributes) that EMRs usually cover: namely “input
facilitation”, “personalization”, “reliability”,
“performance”, “usability”, “level of integration”,
“adequacy of the information model”.
The construct we call “QSA” regards more
“advanced” functionalities: namely “support of
mobility”, “multiple sharing capabilities”,
“automatic import”, “support of semi-automatic
audit”, “flexible back-up management”, “case- and
process-aware reminders”, “knowledge source
search and retrieval”, “full record annotation”.
The perceived utility of the “advanced” functions
of EMRs has been expressed by a set of items
encompassed by the “QUA” construct, whereas the
utility of the core functionalities were given for
granted. Finally, the role of ICT in mediating
communication and collaboration among GPs and
their patients is articulated in terms of both current
use and desired prospective use, in order to see how
ICT could affect the interaction between GPs and
their patients also in the near future.
In August 2013, we administered a questionnaire
reflecting the information model described above to
a selected sample of Italian GPs, whose addresses
were indexed in the mailing list of the “Federazione
Italiana Medici di Medicina Generale” (FIMMG).
The FIMMG is a trade union organization and
country-wide professional association that represents
almost 30,000 General Practitioners in Italy. With
the collaboration of the Study Center of this
association, we contacted 14,478 potential
respondents by sending them one single message of
invitation by e-mail. In this message we invited the
recipients to participate in the online survey on a
voluntary and anonymous basis, with no incentives
nor reminders, once the main aims of the research
had been outlined. Responses were collected for 5
weeks through an online questionnaire platform,
Limesurvey v. 2.0. We configured this platform to
have it display the questionnaire as a sequence of six
short Web pages that enabled a Computer-Assisted
Self Interview (CASI). In these pages, we kept the
number of mandatory fields to a minimum to only
allow for the conditional routing of items, so that the
overall interview could take a shorter time on the
basis of the responses provided in the process. The
platform also allowed for unique and restricted
access to the questionnaire, so that no multiple
responses were collected, and only invited subjects
could participate in the survey until we closed it.
The platform also enabled data persistence across
multiple user sessions to allow respondents to quit
the questionnaire anytime and resume it at a later
time. In doing so, we aimed to minimize the risk of
fatigue bias: nevertheless, the pilot sessions by
which we tested the survey with a small convenience
panel before the invitation had been dispatched took
between 8 and 12 minutes on average to complete.
3 RESULTS
At the end of the survey, we collected 800 complete
questionnaires. Respondents (77% men and 23%
women) were those who accepted to participate in
the interview mentioned above and filled in all the
items reported in the questionnaire. Partial
questionnaires were then discarded. The relatively
low response rate was also due to a technical
problem that occurred in the dispatch of the
invitation letter, which caused many letters be
erroneously categorized as spam by aggressive
filters, and to the fact that the survey was
administered when many practitioners were likely
on a summer vacation.
The average age of the respondents was 57 years
(sd: 6 yrs, range: 27 – 70 yrs, 95% c.i.: 56.5 – 57.3)
and 86% of the sample declared an age between 50
and 65 years. 91% of respondents claimed to have
more than 10 years of experience in the GP field,
and 73% more than 20 years. 85% of the sample
declared to assist more than 1000 patients (22%
even more than 1500; average number of patients:
1290 ± 340). These data make us confident to have
collected the opinions and attitudes of experts of
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great experience and deep knowledge of their
application domain.
Italian macro Regions were represented in the
sample with a slight preponderance of Northern
Regions with respect to actual distributions of Italian
GPs (North: 49% vs. 43%, Centre: 20% vs. 21%,
South: 32 vs. 36%). Thus, we weighted our sample
in order to make the sample representative at
geographical level. Margin of error is 3.4% at
National level (at a confidence level of 95%). The
detected margin is consistent with conservative
assumptions on response distribution, since the
research does not claim census-like aims, but rather
it aims to detect attitudes and trends in EMR use and
its perceived quality. This makes our study relevant
to build a picture of current EMR adoption and
satisfaction and to be considered by the scientific
community of IT researchers for the aims mentioned
in Section 1.
In regard to IT use, 98% claimed to be using an
Electronic Medical Record. This is consistent with
other similar recent surveys, e.g., (Cabitza, 2012)
(Misericordia, 2011). However, among the users that
claimed to be using an EMR, the proportion of those
who claimed to be exploiting their record only “for a
small part of its potential” and, anyway, “less than
actually felt necessary” is (still) high (see Figure 1,
topmost diagrams): in either cases, approximately 1
GP out of 4. This is in line with the concerns
discussed in (Cabitza, 2012) regarding the
phenomenon of “low use”(Simon et al., 2009), and
the related efforts to pay to improve user adoption
and appropriation (our model addresses these points
in two specific items, called PerceivedExploitation
and PerceivedFit). The 94% of the sample found
their EMR listed in the questionnaire, which
reported 15 applications from the Italian market.
Three applications were used by nearly the two
thirds of the sample: we will call them Application
A (used by 45% of respondents), B (12%) and C
(11,8%) for sake of confidentiality.
Figure 1 depicts other characteristics of the
respondent sample, in particular with regard to
declared familiarity with IT (Perceived Skills), and
to what kind of cooperative relationships GPs are
involved in their practice (Collaboration Type): this
latter information is relevant with respect to the
granularity of the “sharing” functionality discussed
in the QSA and QUA constructs of the model.
All of the aggregated constructs mentioned
above showed very high internal consistency in
terms of intraclass correlation: satisfaction in regard
to support of medical dimensions (QSM, Cronbah’s
alpha=0.89, c.i.= .88-.90, mean scale=18, sd=4.4);
Figure 1: Descriptive statistics of the respondent sample.
Figure 2: Inter-construct correlations.
satisfaction for common functions (QSC, Cronbah’s
alpha=0.84, c.i.=.82-.85, scale mean=16, sd=3.9);
satisfaction for advanced functions (QSA,
alpha=.92, c.i.=.87-.96, scale mean=40, sd=13);
perceived utility for advanced functions (QUA,
alpha=.98, c.i.=.96-.99, scale mean=49, sd=16),
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perceived impact on work dimensions (PIW,
alpha=.79, c.i.=.76-.81, mean=28, sd=4.2).
Canonical correlations between constructs were
significant between QSC and QSA (alpha=.94),
QSC and QUA (=.91), QSM and QSA (.86).
Correlations between QSM and QSC, and between
QSM and QUA are slightly below the conventional
significance threshold (.63 and .72 respectively).
Figure 2 shows these inter-construct correlations in
graphical form. In what follows we report the main
findings for each construct of analysis.
3.1 Recommendability
As anticipated above, in regard to overall
recommendability we adopted the Net promoter
Score (NPS). This is a convenient way to represent
satisfaction for a product as this score relates
satisfaction to the pragmatic behaviour of their users
and associated likelihood to recommend such a
product to colleagues and acquaintances. The overall
NPS of the EMRs was +13%; this means that
promoters, i.e., who would highly recommend her
application responding either “9” or “10” on a 1-to-
10 scale, were 13% more numerous than detractors,
i.e., who would not recommend her application (and
responded with a mark below “6”). Nevertheless,
situation differs according to the application actually
owned. Just to limit ourselves to the three most used
EMRs (A, B and C mentioned above), the NPS of A
was +35% (i.e., the proportion of potential
promoters was one third larger than the proportion
of potential detractors), C’s NPS was +11%, and B’s
one was -30% (i.e., the proportion of potential
detractors was one third larger than the proportion of
potential promoters). Moreover, if we assimilate the
NPS 10-point ordinal scale to an interval scale, we
could evaluate an “overall recommendability” score
of current Italian EMRs in terms of “average score”,
that is 7.6 (± 2). In regard to the most used EMRs,
the average score is 8.2 for A, 6.4 for B, and 7.6 for
C (the difference between the scores of A and B is
highly significant, t=2.9, P=.004). The Net Promoter
Score of the most widely adopted EMR (45%)
resulted to be highly affected by self-perceived IT
skills (P-value<.001, the higher the skills, the higher
the NPS), perceived level of exploitation (P-
value<.001, the higher the level, the higher the NPS)
and, notably, the number of patients (P=.001, the
higher the number of patients, the higher the NPS);
also geographic and collaboration-related
differences could have an impact (respectively,
P=.07 and P=.09) but this is not statistically
significant; other factors, like gender, age and years
of experience result not related to NP scores.
3.2 Satisfaction for Common Features
For sake of clarity, we report the results for the QSC
construct with the aid of Figure 3. There we depict
the response distribution for the question expressed
as follows: “in regard to each feature would you
please indicate the extent your current EMR should
be still improved to really please you”. Available
options ranged on an four item scale, encompassing
the labels “still a lot of room for improvement” (1),
“some room for improvement” (2), “already
adequate” (3), and “already optimal” (4). Boxplots
show the interquartile range for perceived
satisfaction: the dark green box indicates the upper
quartile; the light green box the lower quartile; thus,
the median is depicted as the border line between the
two quartile boxes (if visible); whiskers indicate the
variability outside the upper and lower quartiles (i.e.,
the min and max value respectively). Moreover, as a
merely illustrative addition, we also indicate the
response average with a small red dash, and the
mode (i.e., the response chosen by the majority of
respondents) with a blue dash.
Figure 3: Box plots showing the interquartile range for
QSC.
In the topmost part of Figure 3, we also show the
result of a Binomial test that we undertook to
understand whether the apparent tendency that can
be detected for each item visually is also “true” and
generalizable to the whole population of reference,
or it is not so because, e.g., that tendency is due to
chance. The little hand-shaped icons indicate
whether the respondents were sufficiently satisfied
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with the corresponding feature (i.e., responses
associated with at least an “adequate” level of
satisfaction) or not (i.e., responses either below or at
the threshold of satisfaction, that is 2). The number
of asterisks indicates how much “significant” the
indication is according to the Binomial test.
According to the results, then, the GPs indicated
clearly that current EMRs should be improved with
respect to:
1) their capability to make simple tasks more
automatic, like offering more precompiled
fields in form templates, the capability to
duplicate data between fields when applicable,
and more user-friendly import and export
functionalities.
2) their capability to be customized by end-users,
both in terms of user interface (appearance,
what fields and where to position them,
available formats) and functional
configurability.
3) their performance, both in terms of speed in
processing data and in reacting to user
commands and interactions.
4) their compatibility with data coming from
different applications and their interoperability
with other systems and services, also at
Regional level.
5) the adequacy of the information model by
which patient cases and illness trajectories are
represented in the electronic record (on this
problem, the interested reader can refer to
(Swinglehurst et al., 2012)).
Respondents also expressed the need to improve
the reliability of their EMR, in terms of either
absence of errors and failures. Quite surprisingly,
respondents claimed they are already satisfied with
the usability of the graphical interface and the
overall user experience, which conversely is a
common place of user dissatisfaction.
It is worthy of note the fact that both the
perceived fit of EMRs with the GPs’ needs and the
perceived level of exploitation seem strongly
correlated with the degree of satisfaction for several
functions. Other contextual aspects seem to play a
less important role as factors influencing
satisfaction, except the number of patients treated by
the single GP: the higher this number, the higher the
satisfaction with respect to usability and the
information model.
3.3 Perception of Advanced Features
Advanced features have been investigated both in
terms of actual satisfaction (QSA) and perceived
usefulness (QUA).
In regard to satisfaction for a specific feature,
this was assessed on an ordinal scale of 6 items,
from 1 (totally unsatisfied) to +6 (totally satisfied).
Quite surprisingly, the GPs involved in our study
expressed a generally higher appreciation for the
advanced features than for the core functionalities
(represented in the previous construct, QSC). It is as
if car drivers showed appreciation for the luxury
accessories of their cars (e.g., the leather-trimmed
interiors), but expressed discontent for the car’s
reliability and its low compatibility with regular
petrol stations. More seriously this could be related
to the high experience of the respondents involved,
probably aware of what can really produce value in
their professions (on which they are demanding in
reason) and what is fine but somehow superfluous.
Like in the case of the QSC construct, we
verified QSA trends performing a Binomial test for
each feature, by comparing the proportions of
responses that were either above or below the
satisfaction “threshold” (+3). Respondents claimed
to be already satisfied in regard to the support of
mobility, the content sharing with colleagues (other
GPs), the capability to execute audits on the basis of
their own patient data, to perform backup, to set
proactive reminders, and to annotate their records.
On the other hand, the data analysis could not detect
a clear satisfaction for the capability to share data
with patients, and to import data from other systems.
A clear unsatisfaction could not be proved
significant with respect to the capability to share
information with colleagues of the “continuous
assistance” program (CA, a sort of "out of hour"
medical services) and colleagues other than GPs
(e.g., specialists, hospital doctors). On the other
hand, significant unsatisfaction has been expressed
for the service by which to retrieve the latest
scientific sources (usually journal articles) from the
specialist literature that are pertinent to specific
patient cases.
As mentioned above, the construct called QUA
regards the perception of usefulness by the sample
and it is expressed in terms of items whose possible
answer options were represented on a six-value
ordinal scale, from 1 “useless at all” to 6 “very
useful”. We intend this construct as an informal but
consensus-based indication of what functionalities
should be addressed first by EMR vendors, and
therefore should be added to the portfolio of services
already available in modern EMRs. It is worth of
note the fact that while satisfaction for a feature was
an item that had been answered only by those that
had previously claimed to use an EMR already
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endowed with such a feature, the usefulness of a
feature was probed on the entire sample of
respondents, irrespective of the presence of such
feature in the respondent’s EMR.
Table 1: QUA ranking.
Rank Functionality Priority
1 Importing First ***
2 Backup First ***
3 Reminder First ***
4 Mobility First ***
5 SharingCA First ***
6 SharingGPs First ***
7 SharingColleagues First ***
8 Audit First ***
9 PubRetrieval First ***
10 Annotation First ***
11 SharingPatients First ***
As an aid to decision making and the process of
detecting risks and opportunities of either
developing from scratch or evolving specific
features, we also performed a ranking of the features
on the basis of the ordinal values collected in our
survey. Table 1 shows the result of this task that we
performed applying an original ranking method
purposely developed to infer what features are
valued most by the respondent sample. In this
method priority levels were assigned to single
features in the following manner: 1) we counted the
number of times each feature was ranked either first,
second or third (“first priority class”), or was ranked
in any other position ("second priority class"); and 2)
we assigned each feature to the priority level with
the highest number of occurrences. This assignment
was then tested with a Chi-squared test to check if
rankings could be due to chance and hence fail to
show a real difference in the frequency of
assignment to either the first or second class of
priority. As shown in Table 1, all features are to be
considered in the first priority class with a very high
confidence that this assignment is not due to chance.
However, the evaluations collected in our study
allows us to provide a ranking where data importing
capabilities, backup services and reminders are the
functions valued most highly, while the capabilities
of annotating any content in the EMR and to share it
with patients are those valued less.
3.4 Impact on Medical Work
Impact of ICT on medical work has been
investigated both in terms of quality of support of
specific steps of the medical process (QSM), and as
perceived change in known attributes of general
practice. Support quality was evaluated on a 5-value
ordinal scale, ranging from 1 (“very low quality of
support”) to 5 (“very high quality of support”).
Hence, for QSM the descriptive and inference
analyses are depicted in Figure 4. From this Figure,
it is clear that Diagnosis and Therapy are placed at
the opposite sides of the satisfaction spectrum: GPs
found “treatment” be managed properly by their
EMR, probably tapping in the vast amount of
research around order entry and drug prescription;
while they find support of diagnosis significantly
disappointing. Also the part of EMRs that covers
medical examinations and sign/symptom evaluation
is found to be an area that would benefit from efforts
towards improvement, e.g., like those envisioned in
(Cabitza et al., 2013).
In regard to the impact of EMR on GPs’ work,
this is clearly perceived as greatly more
documented, more informed, more documented,
more interesting and, most notably, much more
appropriate. This is the opinion of approximately 9
GPs out of 10, except for the dimension of
“interest”: in this case, 1 out of 6 GPs believes that
digitization has not changed the extent her work is
interesting; consequently, a lower number of GPs
deemed that their work has become more interesting
since the advent and diffusion of EMRs (76%).
Moreover, the majority of respondents indicated that
their work has become more stressful; however, this
finding is not associated with statistical significance
(43% more stressful, 41% less stressful; 17%
unvaried, Chi-squared=.62, df=1, P-value=.43, NS).
In regard to privacy concerns, the majority of the
respondents perceived their work as confidential as
it was before digitization (more confidential 39%,
vs. equal 43%, Chi-squared= .95, df=1, P-value=.33,
NS). This is an interesting finding especially in light
of the importance that usually IT researchers and
developers attach to the requirements of security,
privacy and confidentiality in the management of
health data. It would be interesting to investigate if
this perception of GPs is more related to a motivated
confidence in their tools, or rather to an actual
ignorance of the potential risks related to the
management and transmission of digital data.
3.5 Use of ICT to Communicate
In regard to the role of technology in mediating
doctor-patient communication, phone resulted the
communication means most frequently used: 95% of
the sample said to rely on phone to communicate
with patients at least “sometimes and with some
regularity” (79% said to do it often). Electronic mail
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Figure 4: Boxplots for the QSM items.
is the second tool in terms of frequency of use (52%
use it with some regularity, 19% often). Then SMS
(32% regularly, 9% often), fax (24% regularly, 4.9%
often); and finally (not surprisingly) Social Media.
This term was denoted in the questionnaire as any of
the following tools: Forum, Blogs, Chat and Social
Networks (like Facebook and LinkedIn);
interestingly, it resulted that these media are used
regularly by almost one tenth of the sample (9.8%,
2.8% often). In particular, 83% of the respondents
claimed to use emails to communicate with patients,
while almost 1 GP out of 5 (19%) claimed to use any
of the social media defined above. The frequency of
use of emails, social media and SMS resulted to be
correlated with statistical significance (Email with
SMS, large correlation: alpha=.53, P-value<.001;
Email with Social Media, moderate correlation:
a=.36, P-value<.001; Social media with SMS
moderate correlation: a=.39, P-value<.001). The use
of Social media and emails to interact with patients
was slightly correlated with claimed IT skills: the
higher the latter ones, the more frequently these
tools were used (for both items, Alpha=.18, P-
value<.001).
When we asked the respondents about how they
would like to communicate with patients in the
future (obviously besides face-to-face encounters),
the majority of the sample declared to be fine with
current use of phone, fax, SMS and social media
(more precisely, phone: 63%, P-value<.001; fax:
54%, P=0.016; SMS: 54%, P=.048; Social Media:
45%, P-values are for Chi squared tests, with 1
degree of freedom, two-tailed). However, almost one
third (31%) of the respondents wished they could
use phone less frequently, and similar results hold
also for fax (39%), SMS (28%) and, notably, also in
regard to a relatively novel means like social media
(38%), which has apparently disappointed some
expectations, at least as facilitator of doctor-patient
interaction. Interestingly, in regard to electronic mail
the results are opposite: only one respondent out of
10 expressed the wish to use emails less in the
future; indeed, the majority of respondents said they
would like to use emails more often in the future
(49%); the difference with respect to those who are
fine with current use (40%) is statistically significant
(Chi squared=7.2, df=1, P-value=.007). This finding
would suggest that doctors would prefer to move
from a distributed voice-based interaction with
patients to a message-based interaction, that is that
they dread interruptions and volatile indications
more than the work overload implied by having to
respond to more emails from their patients, probably
also in virtue of the famous proverb “spoken words
fly away, written words remain”.
In 2011 the same question was asked to a
representative random sample of Italian GPs in a
survey reported in (Cabitza, 2012). Comparing the
present survey and the previous one, we observe that
in 2013 a greater proportion of doctors claimed to
exchange emails with their patients to discuss
health-related problems “often and regularly” (11%
vs. 19%); this difference is statistically significant
(Chi-squared = 7.9, df = 1, P-value = 0.003). In this
two-year time span, also the use of Social Media
proved to have improved (14% vs. 19%, Chi-
squared= 2.7, df = 1, P-value = 0.0495). Also with
respect to prospective use, we detected statistically
significant increases in the proportions of GPs who
claim to want to use emails and social media more
often: in regard to emails we observed an increase
from the 30% of 2011 to the 49% of 2013 (Chi-
squared =27, df = 1, P-value < .001); and in regard
to social media from the 12% of 2011 to the 17% of
2013 (Chi-squared=3.1, df = 1, P-value = 0.038).
4 CONCLUSIONS
In this paper we have presented the findings of a
country-wide survey about the current and
prospective use by GPs of the ICTs (mostly EMRs)
that support their daily practice. The vast number of
GPs involved, the items considered and the analysis
of the responses collected in this study make this
research valuable for a number of aims. First to get a
picture of the level of adoption and appropriation of
EMRs in General Practice: the latter dimension was
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addressed by two specific items, PerceivedFit and
PerceivedExploitation, and their influence on
satisfaction was proved to be relevant. Second, to
begin considering analytically how multiple quality
dimensions and appropriation are intertwined, and
discover, for instance, how investments in IT
training and IT skill improvement for GPs could be
reflected in higher exploitation rates, better fit of
EMRs with the GPs’ needs and higher satisfaction.
Last but not least, to detect areas of improvement
(see Figure 4) and to assign priorities and rankings
to features in order to both increase overall user
satisfaction (see the NP score mentioned in Section
2.1) and decide where to focus on to make EMRs
better tools (see Table 1). Notably, our survey also
addresses how relatively new media could impact
practice: to this regard, attempts to include current
social media in medical practice by innovators and
early adopters (10% of the target population) seem
related to growing scepticism and disillusion.
However, GPs seem to still value written interaction
with their patients (cf. the increasing trends for email
actual usage and intention to use), and this could
hint at more communication-oriented models for the
next EMRs to come, as argued in (Cabitza and
Gesso, 2014)
In a period of fast and continuous innovation and
yet urgent spending limits to welfare and primary
healthcare, detecting the most value-adding features
of a class of applications for their reference key
users, and enabling the subsequent prioritization of
interventions to focus on could be a necessary move
to make ehealth a convincing driver for the feasible
progress of the medical profession.
REFERENCES
Benson, T., 2002. Why general practitioners use
computers and hospital doctors do not - Part 1:
Incentives. British Medical Journal 9, 1086-1089.
Cabitza, F., 2012. On the attitudes of GPs toward novel
features of their next EPRs. In: Quality of Life through
Quality of Information, Studies in Health Technology
and Informatics. pp. 911–916. Springer.
Cabitza, F., Simone, C., Colombo, G., 2013. ``Worth a
thousand fields’’. Arguing for a visual turn in
computer-supported general practice. In eHealth 2013:
Proceedings of the IADIS International Conference on
eHealth, 24-26 July, 2013 Prague, CZ, Computer
Science and Information Systems. IADIS Press, pp.
95-102.
Cabitza, F. and Gesso, I., 2014. Trying to fill the gap
between Persons and Health Records: the MedIcona
InterPersonal Health Record. In Healthinf 2014,
Proceedings of the BIOSTEC International conference
on Health Informatics.
Delaney, B., 2010. General practice at the cutting edge of
information technology, or failing to keep pace?
British Journal of General Practice 60, 239–240.
Dobrev, A., Haesner, M., Haesing, T., Korte, W.B.,
Meyer, I., 2008. Benchmarking ICT use among
General Practitioners in Europe. Gesellschaft fuer
Kommunikations- und Technologieforschung mbH.
Hassey, A., 2001. A survey of validity and utility of
electronic patient records in a general practice. British
Medical Journal 322, 1401–1405.
Hippisley-Cox, J., 2003. The electronic patient record in
primary care--regression or progression? A cross
sectional study. British Medical Journal 326, 1439–
1443.
Keiningham, T. L., Cooil, B., Andreassen, T.W., Aksoy,
L., 2007. A Longitudinal Examination of Net
Promoter and Firm Revenue Growth. Journal of
Marketing 71, pp. 39–51.
Misericordia, P., 2011. Indagine FIMMG sui modelli
organizzativi prevalenti negli ambulatori dei
generalisti d’Italia. Sanità - Sole 24 Ore 14, 14–15.
Porcheret, M., Hughes, R., Evans, D., Jordan, K.,
Whitehurst, T., Ogden, H., Croft, P., 2004. Data
Quality of General Practice Electronic Health Records:
The Impact of a Program of Assessments, Feedback,
and Training. Journal of the American Medical
Informatics Association 11, 78–86.
Purves, I. N., 1996. The paperless general practice. British
Medical Journal 312, 1112–1113.
Simon, S. R., Soran, C. S., Kaushal, R., Jenter, C. A.,
Volk, L. A., Burdick, E., Cleary, P. D., Orav, E. J.,
Poon, E. G., Bates, D. W., 2009. Physicians’ use of
key functions in electronic health records from 2005 to
2007: a statewide survey. Journal of the American
Medical Informatics Association 16, 465–470.
Swinglehurst, D., Greenhalgh, T., Roberts, C., 2012.
Computer templates in chronic disease management:
ethnographic case study in general practice. British
Medical Journal Open 2, e001754–e001754.
Treweek, S., 2003. The potential of electronic medical
record systems to support quality improvement work
and research in Norwegian general practice. BMC
Health Services Research 3.
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