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m-Health Adoption by Healthcare Professionals: A
Systematic Review
Marie-Pierre Gagnon,1,2§ Patrice Ngangue,1,2 Julie Payne-Gagnon2 and Marie Desmartis2
1 Faculty of Nursing, Université Laval, Quebec City, Canada 2 Public Health and Practice-Changing Research, CHU de Québec Research Center,
Quebec City, Canada
§ Corresponding author:
Marie-Pierre Gagnon, Ph.D.
CHU de Québec Research Center
10, rue de l'Espinay, D6-726
Québec (QC), Canada G1L 3L5
Tel. 1 418 525 4444 Ext. 53169
Fax. 1 418 525 4194
Keywords
m-health; healthcare provider; adoption; systematic review; mixed methods
Word count: 3709
2
ABSTRACT
Objective The aim of this systematic review was to synthesize current knowledge of the factors
influencing healthcare professional adoption of mobile health (m-health) applications.
Material and Methods Covering a period from 2000 to 2014, we conducted a systematic
literature search on four electronic databases (PubMed, EMBASE, CINAHL, PsychInfo). We
also consulted references from included studies. We included studies if they reported the
perceptions of healthcare professionals regarding barriers and facilitators to m-health utilization,
if they were published in English, Spanish or French and if they presented an empirical study
design (qualitative, quantitative, or mixed methods). Two authors independently assessed study
quality and performed content analysis using a validated extraction grid with pre-established
categorization of barriers and facilitators.
Results The search strategy led to a total of 4,223 potentially relevant papers, of which 33 met
the inclusion criteria. Main perceived adoption factors to m-health at the individual,
organizational and contextual levels were the following: perceived usefulness and ease of use,
design and technical concerns, cost, time, privacy and security issues, familiarity with the
technology, risk-benefit assessment, and interaction with others (colleagues, patients and
management).
Discussion While some of the barriers and facilitators to m-health adoption are similar to those
identified in systematic reviews about other ICT applications, this review has enabled us to
identify factors that are specific to m-health, such as patient empowerment and accessibility.
Conclusion This systematic review provides a set of key elements making it possible to
understand the challenges and opportunities for m-health utilization by healthcare providers.
3
BACKGROUND AND SIGNIFIANCE
The number of people in the world who own a mobile phone or other portable electronic
communication device has grown exponentially during the last decade. The recent advances
regarding mobile technologies have enabled mobile devices to perform functions previously not
possible with handheld devices.1 These innovative applications to address health issues have
evolved into a new field of eHealth, known as mobile health or m-health.
Although several definitions to m-health have been proposed, none seems to reach consensus in
the international literature. For instance, Mirza suggests that m-health “involves the use of
mobile technology to enhance health services. The mobile technology can be either a short-
distance or long-distance technology, or be device driven”.2 For its part, the Global Observatory
for eHealth (GOe) of the World Health Organization (WHO) defines m-health as medical and
public health practice supported by mobile devices, such as mobile phones, patient monitoring
devices, personal digital assistants (PDAs), and other wireless devices.3 Mobile technologies
include mobile phones, personal digital assistants (PDA) and PDA phones; smartphones;
enterprise digital assistants (EDA); portable media players, handheld video-game consoles and
handheld and ultra-portable computers such as tablet PCs. These devices have a range of
functions from mobile cellular communication using text messages (SMS), photos and videos
(MMS), telephone and internet access, to multimedia playback and software application support.
m-Health interventions are designed to improve healthcare service delivery processes by
providing support and services to healthcare providers (such as education, support in diagnosis
4
or patient management) or target communication between healthcare services and consumers
(such as appointment reminders and test result notification)4 and thus changing the traditional
modes of information sharing and dissemination.5 In 2012, there were approximately 40,000
mobile device applications (apps) related to health.6
m-Health is thus central to the concept of pervasive healthcare where information and resources
services can reach anyone, anytime, and anywhere, by removing geographical, time, and other
barriers.7 While there is limited scientific evidence supporting the effectiveness of m-health,4,8
governments and organizations in many jurisdictions have embraced it as the backbone of the
informed and empowered patient or “patient 2.0”.9,10 m-Health also constitutes an affordable
option to increase health promotion, disease prevention, provision of care and monitoring in
low-income countries, where pilot projects are rampant.11
As with other information and communication technologies (ICT) that have entered the
healthcare sphere in the past, such as telemedicine or electronic health records, the success of m-
health as a tool to support the delivery of healthcare is tributary to its adoption by healthcare
providers.12 While the factors influencing healthcare providers for adopting a new technology
such as m-health could be similar to those involved with other ICT applications, there are
specific features about m-health that should be considered. First, unlike previous ICT
applications in healthcare, m-health is mainly consumer-centered and consumer-driven.13
Second, m-health interventions can be seen as a patchwork of small-scale pilot projects11 and
most of these interventions work as black boxes with little use of theoretical foundations.14
Although mobile communication is now part of the everyday life of most human beings, the use
of m-health applications to provide health information and care is particularly challenging and
5
calls for specific strategies. The aim of this paper is to synthesize the scientific literature on the
factors that could facilitate or limit healthcare provider utilization of m-health in their work.
METHODS
Search strategy
We adhered to the to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis
(PRISMA) checklist.15 Covering a period from January, 1st 2000 to October 31st, 2014, we
conducted a systematic literature search on four electronic databases (PUBMED, EMBASE,
CINHAL, PsychInfo). We also searched the references of included publications to identify
additional relevant literature. The search strategy included three categories of keywords: m-
health, healthcare professionals and adoption. These keywords should appear in conjunction in
the title or abstract of the article. To refer to m-health, articles either had to include the term “m-
health” (and its alternative formulations), or include both the term “health” and one of the
following search terms or their variants: handheld computer, mobile phone, smartphone, mobile
application, mobile app, cellular phone, mobile device, mobile technology, SMS, or text
message. To refer to healthcare professionals, we used the following search terms or their
variants: professional, physician, practitioner, provider, resident, clinician, nurse, midwife,
health worker, specialist, dentist, pharmacist, dietician, physiotherapist, cardiologist, surgeon,
gynaecologist, ophthalmologist, psychiatrist, and optician. Finally, we searched the following
themes related to adoption: acceptance, acceptability, utilization or attitude.
Duplicate citations across databases were identified and excluded using Endnote and a manual
revision was done for verification. If a study was reported in more than one publication and
6
presented the same data, we only included the most recent publication. However, if new data
were presented in multiple publications describing the same study, all were included.
Inclusion and exclusion criteria
We included studies with an abstract in English, French or Spanish. The studies had to be based
on an empirical design, including qualitative, quantitative or mixed-methods. The articles should
clearly state data collection process as well as research methods and measurement tools used.
We excluded publications presenting editorials, comments, position papers, and unstructured
observations from this review. We included conference proceedings as long as they presented all
relevant data. Studies had to provide data on barriers and facilitators to m-health adoption by
healthcare professionals in their results or discussion sections to be included. These barriers or
facilitators could be related to one or several healthcare professional groups who were using m-
health. We excluded studies that focused only on m-health adoption by healthcare students and
studies in which there was no clear distinction between healthcare professionals and other
groups (e.g. patients, technology providers) regarding m-health adoption factors.
Screening and data extraction
One reviewer (PN) initially screened all titles and abstracts of references identified through the
search strategy and another reviewer (MPG) reviewed the titles and abstracts retained. Then, PN
and MPG independently reviewed the full text of preselected articles and agreed on their final
selection.
Two dyads (PN and MPG, MD and JPG) independently performed data extraction using a
validated data extraction grid, developed through previous research related to the classification
of barriers and facilitators to information and communication technology adoption by healthcare
7
professionals.12 This generic data extraction grid has been adapted and validated to classify
reported barriers and facilitators to the adoption of electronic health records and electronic
prescription.16,17 The grid was developed using both inductive and deductive methods, and
combines several relevant concepts from established theoretical frameworks, notably the
Technology Acceptance Model (TAM) and the Diffusion of Innovations Theory.18,19 Emergent
categories were also added during the review process. We populated the data extraction grid in
Microsoft Excel software 2010.
Data synthesis and analysis
The reviewers identified sections of the publications that presented a relevant barrier or
facilitator to adoption of m-health from the healthcare professionals’ perspective and coded them
according to the categories proposed in the grid. Then, we grouped the extracted data into four
main categories of adoption factors and each category was decomposed into specific factors. We
also extracted data regarding: year of publication, country, and study design (quantitative,
qualitative, or mixed-methods), theoretical framework (present or absent), type of participants,
care setting, technology used, objectives of the study, data collection methods, and main
findings. Quality of studies was not considered in these analyses.
RESULTS
Included studies
In total, we identified 4,223 references from the databases, of which we kept 48 publications for
a full-text review. We excluded 15 publications because they did not meet the inclusion criteria:
two were about m-health use by students;20,21 three did not clearly differentiate healthcare
8
professionals’ opinions from those of other groups involved in the study;2,22,23 two presented
opinions from professionals who were not using m-health;24,25 six were not about adoption
factors;26-31 and two did not describe the methodology used.5,32 Thus, 33 publications were
selected in the final review.1,7,33-63 The study selection flow diagram is presented in Figure 1.
[Insert Figure 1 about here]
Characteristics of included studies
The table summarizing the characteristics of included publications can be found in
Supplementary File 1. The included studies were published between 2005 and 2014.
Interestingly, more than half of them (57.6%) were published during the last three years.33-
36,41,42,44,47,49,51-53,56,58-63 Few theoretical frameworks were used in the studies. Indeed, only eight
(24.2%) publications mentioned the use of a theoretical framework: the TAM and its updated
version (TAM2),1,7,37,51,62 the Diffusion of Innovations Theory,1,51,61 the Information System
Success Model38,47 and the Technology Readiness Index (TRI).62
The studies about m-health adoption were conducted in various countries. More than half of the
studies took place in the Americas (n=18, 54.5%). Among these, ten were conducted in Canada,
7,43,44,53-59 seven in the United States1,40,41,46,48,51,63 and one in Guatemala.42 Six publications
(18.2%) were from European countries, including the United Kingdom,45,49,50 Ireland,39
Portugal46 and Finland.38 Five studies (15.2%) were from Asia (Taiwan,37,61,62 Japan47 and
India60), four (12.1%) were conducted in Africa, each representing a different country
(Ethiopia,33 South Africa,34 Botswana35 and Uganda36) and one was from Australia.52
9
The majority of studies used a quantitative research design (n= 19, 57.6%).1,7,33,37,39-43,46-49,51,57,60-
63 Six studies (18.2%)34,38,44,53,55,56 employed a qualitative design through the use of focus
groups,34,55 interviews38,44,53,56 and written reflections55 for data collection methods. A mixed
methods design was used in eight publications (24.2%).35,36,45,50,52,54,58,59
The types of m-health technology studied were the following: a smartphone or mobile phone
(n=15),1,34-36,38,39,42,44,48-51,56,57,59,60 a personal digital assistant (n=5),7,33,37,43,55 a remote
monitoring system (n=5), 45,47,52-54 a tablet computer (n=4),55,58,59,63 a mobile electronic medical
record system (n=2),61,62 text messaging (n=2)40-42 and mobile technologies in general (n=1).46
The healthcare professionals who participated in the included studies were physicians, residents,
nurses, health workers, pharmacists and other types of providers (such as social workers and
occupational therapists). Fewer than half of the studies (n=15, 45.5%) exclusively studied
physicians or residents,33,35,38-40,43,46-49,51,52,58,59,63 seven (21.2%) involved nurses
only1,7,37,45,55,61,62 and three (9.1%) concerned health workers exclusively.34,42,60 The other
publications (n=8, 24.2%) had various professionals participating in the study.36,41,44,50,53,54,56,57
Overview of m-health adoption factors
In total, 179 elements were identified as barriers to or facilitators for m-health adoption and were
classified in the different categories of factors from the extraction grid. 98 (54.7%) of these
elements were classified as facilitators for m-health adoption and 81 (45.3%), as barriers.
The complete list of factors can be found in Table 1. We also present an analysis of the factors
from studies conducted in developing countries at the end of the section.
10
Table 1. List of factors extracted from the literature (classified by barriers and facilitators)
Factor N of Barriers
N of Facilitators Total
1. Factors related to mHealth characteristics 33 40 73 1.1 Design and technical concerns 7 2 9 1.2.1 Perceived usefulness 3 18 21 1.2.2 Compatibility (with work process) 2 2 1.2.3 Perceived ease of use 3 7 10 1.2.5 Observability (observance, control, verification) 3 3 1.3 System reliability or dependability 1 1 1.4 Interoperability 1 4 5 1.5.1 Privacy and security concerns 5 5 1.5.2 Medicolegal issues 2 2 1.7.2 Satisfaction about content available (completeness) 1 1 1.7.3 Content appropriate for the users (relevance) 1 2 3 1.7.4 Accuracy (improved OR errors, omissions, update) 2 1 3 1.7.5 Quality standard 1 1 2 1.9 Cost issues 5 5 1.13 Cell phone accuracy 1 1 2. Individual factors: knowledge, attitude and socio-demographic characteristics 16 33 49
2.1.1 Awareness of the objectives and/or existence of mHealth 1 1
2.1.2 Familiarity, ability with mHealth 3 3 6 2.1.3 Familiarity with technologies in general 1 4 5 2.2.1 Risk-benefit assessment (perception) 1 6 7 2.2.3 Autonomy
2 2 2.2.4 Impact on clinical uncertainty
1 1 2.2.5 Time issues 3 7 10 2.2.6 Outcome expectancy (leads or not to desired outcome) 1 1 2 2.2.7 Agreement with mHealth (Welcoming/resistant) 4 5 9
2.2.8 Self-efficacy (belief in one’s competence to use mHealth) 1 2 3
2.2.9 Impact on professional security 1 1 2.2.10 Voluntary ownership 1 1 2.3.3 Experience 1 1
11
Factors related to m-health characteristics
A total of 73 elements (40.8%) pertain to the category “Factors related to the m-health
characteristics,” with 33 of them identified as barriers and 40 as facilitators. The most recurrent
adoption factor was perceived usefulness, with 21 extracted elements.1,7,33,34,36-39,42-46,49,51-
54,57,58,60 It was seen more often as a facilitator for m-health adoption (in 18 studies1,7,33,34,36-
39,42,44,45,49,51-54,58,60) than as a barrier (in 3 studies 43,46,57). Perceived usefulness is defined as an
3. External Factors : Human environment 12 7 19 3.1.1 Patients’ attitudes and preferences towards mHealth 2 1 3 3.1.2 Patient and health professional interaction 5 4 9 3.1.3 Applicability to the characteristics of patients 1 1 3.1.4 Other factors associated with patients 1 1 2 3.2.1 Attitude of colleagues about mHealth 1 1 3.2.2 Support and promotion of mHealth by colleagues 1 1 3.2.3 Other factors associated with peers 2 2 4. External Factors : Organizational Environment 20 18 38 4.1 Internal environment 2 2 4.1.1.4 Physician salary status and reimbursement 1 1 4.1.2.1 Lack of time and workload 3 3 4.1.2.2 Work flexibility 1 2 3 4.1.2.3 Relations among colleagues 3 3 6 4.1.2.5 Additional tasks 1 1 4.1.4.1 Resources available 2 2 4.1.4.2 Materials resources (access to mHealth) 1 1 4.1.4.3 Human resources (IT support, other) 3 3 4.1.5.1 Training 2 2 4 4.1.5.3 Management (strategic plan to implement mHealth) 2 2 4 4.1.5.4 Communication and collaboration effort 2 2 4.1.5.9 Readiness 1 1 2 4.1.5.10 Choice of the mHealth system 1 1 4.2 External environment 2 2 4.2.3 Health care policies and socio-political context 1 1
Grand total: 81 98 179
12
individual’s perception that the utilization of a particular mobile device will be advantageous in
an organizational setting over a current practice.19
Perceived ease of use was another frequently mentioned factor (n=10).7,37,43,53,54,56,58,60,61
Perceived ease of use is the perception by an individual that the utilization of a mobile
technology will be relatively painless and effortless.19 Therefore, it was important for the
professionals to perceive the usefulness and ease of use of the technology in their working
environment; otherwise there would be less incentive to use them. Design and technical concern
were also mentioned on 9 occasions,43,53,55,58,59 and were perceived mainly as barrier (seven as a
barrier43,55,58,59 and two as facilitator53,58). Main issues raised were limited features,43,58,59
size55,58,59 and complexity of using some features.58,59
Other factors related to m-health characteristics were interoperability (integration with other
systems),1,34,40,43,51 cost issues43,48-50,53 and privacy and security concerns36,42,48,55 (all of them
extracted five times). Both cost issues and privacy and security concerns were seen exclusively
as barriers to the adoption of m-health. Indeed, professionals were worried about the security and
confidentiality of the data contained in and transferred through these technologies, as well as
potential device theft. Additionally, cost of the mobile technology and smartphone applications
were perceived as barriers to m-health adoption. Other factors identified in this category were
compatibility with work process,38,61 observability (observance, control, verification),1,51,61
system reliability (ability to perform its functions),55 medico-legal issues,50,54 availability of the
content,38 appropriate content,45,58,60 accuracy of the data,52-54 quality standards36,48 and cell
phone accuracy.41
13
Individual factors: knowledge, attitude and socio-demographic characteristics
Individual factors represented 49 (27.4%) of the extracted elements. There were twice as many
facilitators as barriers in this category (32 and 16, respectively). The most common factor
identified was time issues (n=10).39,44,45,48,49,52,56,57,59 Generally, professionals thought that m-
health saved time by allowing quicker contact and communication than other
technologies.39,48,49,52,56,57 However, some pointed out that m-health may be time consuming by
being disruptive to their workflow.44,45,59 Agreement with the technology (n=9)37,40,42,43,46,60,62
was perceived either as a facilitator or a barrier, the agreement being dependent on other factors,
such as interest, motivation and comfort with the technology.
Risk-benefit assessment was also mentioned seven times.39,44,47,48,52,53 Even if one comment
underlined that m-health may make it difficult to communicate complex issues to their patients,44
professionals believed that m-health could improve patient care.39,44,47,48,52,53 Familiarity and
ability with m-health (n=6)40-43,51,59 and with technologies in general (n=5)33,46,50,62 were other
important factors of this category. Finally, professional autonomy,38,55 clinical uncertainty,53
outcome expectancy,50,56 self-efficacy,35,55 professional security,36 awareness of existence of m-
health,59 professional experience61 and voluntary ownership of m-health46 were other factors
identified in this category.
External factors: human environment
External factors related to the human environment represented 19 of the elements identified in
the review (10.6%). Twelve of the factors extracted were barriers and seven were facilitators.
Factors related to patients were underlined more often than factors related to colleagues. Indeed,
the two most recurrent factors of this category concern the patient-professional interaction
14
(n=9)38,48-50,52,63 and patients’ attitude and preferences towards m-health (n=3).34,42,49
Professionals believed that the use of m-health, especially in the case of smartphones, could be
disruptive during visits38,48-50,63 and could be misinterpreted as checking email or SMS.38,49
Others believed that it could facilitate the relationship with their patients by having a new means
of communication with them.38,42,50,52,63 Other factors related to patients were applicability to the
patients’ characteristics,54 patients’ perception of the professional,55 and professionals’ belief
that patients gained better knowledge of themselves.52 There were few mentions of factors
related to peers, such as the attitude of colleagues about m-health,49 their support and promotion
of m-health,35 and miscommunication while using m-health.56
External factors: organizational environment
The last category includes external factors found in the organizational environment and accounts
for 21.2% (n=38) of the elements extracted in this review. Barriers and facilitators were spread
equally, totalizing 20 and 18 factors, respectively. In this category, the most common factor was
relations among colleagues.44,55,57 One of the perceived barriers was that m-health technologies,
by allowing a more direct relay of the information among colleagues, also increased the potential
to be disturbed in their workflow. Management support was also seen as an important facilitator
in this category (n=4).1,44,46,51 In fact, good support from management may facilitate healthcare
professional adoption of m-health.1,51 However, professionals raised concerns about poor
management of information and the imposition of the devices upon professionals who may not
want to use them.44,46
Availability59,63 and access to material42 and human resources,41,43,54 as well as training35,43,45,63
were also seen as adoption factors related to the organization. In addition, some factors related to
15
healthcare professionals’ work environment could be seen as barriers or facilitators to m-health
adoption. In fact, issues related to time and workload,40,53,54 work flexibility (by the increased
mobility and management issue between work and home),55,57 additional tasks,36 reimbursement
of tasks related to m-health,54 and communication in the workplace34,36 were factors raised as
potential barriers to m-health adoption. Other factors mentioned were workplace readiness to
implement m-health,41,54 choice of the device used46 and healthcare system support.54 Finally,
some studies described factors only in terms of internal environment1,51 and external
environment,1,51 without providing more details.
Factors related to developing countries
We also analyzed extracted data related to the six studies that took place in developing countries
(Botswana,35 Ethiopia,33 Guatemala,42 India,60 South Africa34 and Uganda36). In total, 25 factors
were identified in these studies (20 facilitators and 5 barriers). The most recurrent factor
identified for the six studies was perceived usefulness with five elements (all
facilitators),33,34,36,42,60 which is comparable to the results from studies in developed countries.
However, these studies identified five factors that were not mentioned in other studies:
professional security,36 support and promotion of m-health by colleagues,35 additional tasks,36
material resources42 as well as communication and collaboration effort.34,36
Other factors identified from these studies related to functionalities of m-health (ease of use,60
interoperability,34 relevance60 and quality36), privacy and security issues,36,42 familiarity42 and
self-perceived competency35 with m-health, familiarity with technologies,33 agreement with m-
health,42,60 training,35 patients attitude toward m-health34,42 and their interaction with
professionals.35
16
DISCUSSION
This review aimed to summarize the literature on factors that could facilitate or restrain health
professional use of m-health in their work. These professionals, like many other people, possess
mobile phones or other portable electronic communication devices. However, this does not mean
that they use mobile devices for their work. Given the considerable attention that m-health
receives globally, it seemed important to identify the factors that could facilitate or limit its
adoption by healthcare professionals.
The main findings of this review highlight that several factors are associated with m-health
adoption at the individual, organizational and contextual levels. Usefulness and ease of use of
the technology were seen as two of the most important factors with respect to the adoption of m-
health in the included publications. Although those two TAM factors19 were included in the
extraction grid and are common in studies explicitly based on the TAM,1,7,37,51,62 they were also
frequently mentioned as being critical for healthcare professional adoption of m-health in
publications not explicitly using the TAM.
In contrast to a recent review suggesting that m-health could constitute an affordable option for
health promotion,49 our findings show that healthcare professionals think cost issues could limit
their adoption of m-health.43,48-50,53 In fact, all elements identified that were related to costs were
exclusively seen as barriers. More particularly, long-term costs of the technology as well as costs
of the device and applications were mentioned in the studies.
The role of m-health to support patient empowerment has been mentioned in the literature.38,48
This benefit was also perceived in the reviewed studies. In fact, healthcare professionals
believed that patients gained better knowledge of themselves52 and that their relationship with
17
them was improved with the use of m-health.38,42,50,52,63 Additionally, the results show that
healthcare providers agree that m-health could improve patient care,39,44,47,48,52,53 supporting the
idea of a consumer-centered approach promoted by the use of ICT applications.49
As such, m-health is perceived as a technology that can reach anyone, anytime and anywhere.
While the findings of our review support this general idea, it was not necessarily seen as a
benefit. Professionals in fact expressed the belief that m-health brought quicker contact and
communication39,48,49,52,56,57 and improved their access to colleagues,44,55,57 which could
constitute benefits. Conversely, the increased workload36,50,53-55 and the disturbed workflow by
colleagues55,57 were seen as barriers to their adoption of m-health.
Other important adoption factors that were highlighted in this review include
interoperability1,34,40,43,51 and familiarity with the technology.33,40-43,46,50,51,59 These two factors
were also identified in other reviews on ICT adoption among healthcare professionals.1,44,46
Additionally, support of the technology, through management,1,44,46,51 training,35,43,45,63 as well as
material and human resources41-43,54,59,63 were also identified in this review.
We also assessed the results regarding studies conducted in developing countries.33-36,42,60 While
usefulness was also identified as the main factor that may facilitate use of m-health by health
care providers, these studies were the only ones highlighting factors related to the interrelation
between colleagues (promotion of m-health and collaboration effort),34-36 job security,36
additional tasks that may arise while using m-health36 and the need of accessibility to phones and
electricity in order to use m-health.42
18
Limitations
While providing an exhaustive synthesis of the current knowledge on healthcare professional m-
health adoption factors, this review has some limitations. First, we used a generic grid of
adoption factors as the conceptual framework for classifying elements identified as barriers and
facilitators to m-health adoption from the studies included in this review. As such, we relabelled
some of the original factors in order for them to fit within our conceptual framework. We
acknowledge that the use of other theoretical frameworks or models could have uncovered other
dimensions of the adoption of m-health. However, we think that the framework used is
comprehensive and well suited to present adoption factors of m-health perceived by health
professionals as it is based on extensive theoretical and empirical research.
Second, this review only considered data that were presented in published studies, and no
additional contacts were made with the authors to receive additional information or to validate
our classification. Thus, it is likely that other m-health adoption factors could have been passed
over.
Third, we conducted a mixed-method systematic review and we combined data from qualitative
and quantitative studies indistinctively in our synthesis. The use of other synthesis approaches,
such as meta-narrative synthesis or realist review, could have brought a deeper analysis of m-
health adoption in healthcare. Future reviews using these approaches could be guided by the
RAMESES reporting standards.64
Finally, we only conducted literature searches in four bibliographic databases, but we carefully
checked references of included studies as well as articles citing those studies in order to identify
19
other potentially relevant publications. Grey literature searches could have enabled the
identification of other relevant studies.
CONCLUSION
The entire issue of m-health is attracting a great deal of attention worldwide because it presents a
unique way to provide information and resources to healthcare professionals and patients alike,
and may be a promising tool to support healthcare. The findings from this systematic review
provide a common ground, making it possible to better understand the challenges and
opportunities related to m-health utilization by healthcare providers. While some of the barriers
and facilitators to m-health adoption are similar to those identified in systematic reviews about
other ICT applications, this review has enabled us to identify factors that are specific to m-
health.
FUNDING STATEMENT
This research received no specific grant from any funding agency in the public, commercial or
not-for-profit sectors.
COMPETING INTERESTS STATEMENT
The authors have no competing interests to declare.
CONTRIBUTORSHIP STATEMENT
MPG designed the systematic review. PN screened titles and abstracts of references identified in
the databases and MPG reviewed the selection. MPG and PN reviewed the full text articles. All
20
authors contributed to data extraction and JPG synthetized the data. All authors participated to
the drafting of the manuscript and review of the content. All authors approved the final version
of the review.
21
REFERENCES
1. Putzer GJ, Park Y. The effects of innovation factors on smartphone adoption among
nurses in community hospitals. Perspect Health Inf Manag. 2010;7:1b.
2. Mirza F, Norris T. Opportunities and barriers for mobile health in New Zealand. Stud
Health Technol Inform. 2007;129(Pt1):102-106.
3. World Health Organization. mHealth: New horizons for health through mobile
technologies - Based on the findings of the second global survey on eHealth (Global
Observatory for eHealth series). Geneva, Switzerland; 2011.
4. Free C, Phillips G, Watson L, et al. The Effectiveness of Mobile-Health Technologies to
Improve Health Care Service Delivery Processes: A Systematic Review and Meta-
Analysis. PLoS Medicine. 2013;10(1):e1001363.
5. Elwood D, Diamond MC, Heckman J, et al. Mobile Health: Exploring Attitudes Among
Physical Medicine and Rehabilitation Physicians Toward this Emerging Element of
Health Delivery. PM&R. 2011;3(7):678-680.
6. Boulos MN, Brewer AC, Karimkhani C, et al. Mobile medical and health apps: state of
the art, concerns, regulatory control and certification. Online J Public Health Inform.
2014;5(3):e229.
7. Zhang H, Cocosila M, Archer N. Factors of adoption of mobile information technology
by homecare nurses: a technology acceptance model 2 approach. Comput Inform Nurs.
2010;28(1):49-56.
22
8. Aranda-Jan CB, Mohutsiwa-Dibe N, Loukanova S. Systematic review on what works,
what does not work and why of implementation of mobile health (mHealth) projects in
Africa. BMC Public Health. 2014;14(1):188.
9. Ricciardi L, Mostashari F, Murphy J, et al. A national action plan to support consumer
engagement via e-health. Health Aff (Millwood). 2013;32(2):376-384.
10. Bos L, Marsh A, Carroll D, et al. Patient 2.0 Empowerment. In: Arabnia HR, Marsh A,
eds. International Conference on Semantic Web & Web Services. Las Vegas, NV
2008:164-167.
11. Heerden AV, Tomlinson M, Swartz L. Point of care in your pocket : a research agenda
for the field of m-health. Bull World Health Organ. 2012;90(5):393-394.
12. Gagnon MP, Desmartis M, Labrecque M, et al. Systematic review of factors influencing
the adoption of information and communication technologies by healthcare professionals.
J Med Sys. 2012;36(1):241-277.
13. Akter S, Ray P. mHealth - an Ultimate Platform to Serve the Unserved. Yearb Med
Inform. 2010:94-100.
14. Tomlinson M, Rotheram-Borus MJ, Swartz L, et al. Scaling Up mHealth: Where Is the
Evidence? PLoS Med. 2013;10(2):e1001382.
15. Moher D, Liberati A, Tetzlaff J, et al. Preferred Reporting Items for Systematic Reviews
and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009;6(7):e1000097.
16. McGinn CA, Grenier S, Duplantie J, et al. Comparison of user groups' perspectives of
barriers and facilitators to implementing electronic health records: a systematic review.
BMC Med. 2011;9:46.
23
17. Gagnon MP, Nsangou ER, Payne-Gagnon J, Grenier S, Sicotte C. Barriers and
facilitators to implementing electronic prescription: A systematic review of user groups'
perceptions. J Am Med Inform Assoc. 2014;21(3):535-541.
18. Rogers EM. The Diffusion of Innovations. New York: The Free Press 1995
19. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of
information technology. MIS Q. 1989;13(3):319-340.
20. Wallace S, Clark M, White J. 'It's on my iPhone': Attitudes to the use of mobile
computing devices in medical education, a mixed-methods study. BMJ Open. 2012;2(4):
e001099.
21. Wittmann-Price RA, Kennedy LD, Godwin C. Use of Personal Phones by Senior
Nursing Students to Access Health Care Information During Clinical Education: Staff
Nurses' and Students' Perceptions. J Nurs Educ. 2012;51(11):642-646.
22. Cleland J, Caldow J, Ryan D. A qualitative study of the attitudes of patients and staff to
the use of mobile phone technology for recording and gathering asthma data. J Telemed
Telecare. 2007;13(2):85-89.
23. Pinnock H, Slack R, Pagliari C, et al. Understanding the potential role of mobile phone-
based monitoring on asthma self-management: qualitative study. Clin Exp Allergy.
2007;37(5):794-802.
24. Baranoski AS, Meuser E, Hardy H, et al. Patient and provider perspectives on cellular
phone-based technology to improve HIV treatment adherence. AIDS Care.
2014;26(1):26-32.
24
25. Bostock Y, Hanley J, McGown D, et al. The acceptability to patients and professionals of
remote blood pressure monitoring using mobile phones. Prim Health Care Res Dev.
2009;10(4):299-308.
26. Franko OI, Tirrell TF. Smartphone app use among medical providers in ACGME training
programs. J Med Syst. 2012;36(5):3135-3139.
27. Soni RK, Palevsky PM. The smartphone in nephrology: Preliminary survey on current
trends and perceived needs. Am J Kidney Dis. 2013;61(4):A91.
28. Tanaka PP, Hawrylyshyn K, Macario A. Use of tablet (iPad®) as a tool for teaching
anesthesiology in an orthopedic rotation. Rev Bras Anestesiol. 2012;62(2):214-222.
29. Handler SM, Boyce RD, Ligons FM, et al. Use and perceived benefits of mobile devices
by physicians in preventing adverse drug events in the nursing home. J Am Med Dir
Assoc. 2013;14(12):906-910.
30. Velez O, Okyere PB, Kanter AS, Bakken S. A usability study of a mobile health
application for rural Ghanaian midwives. J Midwifery Womens Health. 2014;59(2):184-
191.
31. Palazuelos D, Diallo AB, Palazuelos L, et al. User Perceptions of an mHealth Medicine
Dosing Tool for Community Health Workers. JMIR Mhealth Uhealth. 2013;1(1):e2.
32. Hensel BK, Fontelo P. Physician attitudes toward SMS/Text messaging in medicine.
AMIA Annu Symp Proc. 2008:965.
33. Ben-Yakov M, Hunchak C, Landes M. Personal digital assistant use by emergency
medicine residents in ethiopia: An educational pilot on behalf of the TAAAC(EM)
collaboration. Canadian Journal of Emergency Medicine. 2013;15:S77.
25
34. Chaiyachati KH, Loveday M, Lorenz S, et al. A pilot study of an mHealth application for
healthcare workers: poor uptake despite high reported acceptability at a rural South
African community-based MDR-TB treatment program. PLoS One. 2013;8(5):e64662.
35. Chang AY, Ghose S, Littman-Quinn R, et al. Use of mobile learning by resident
physicians in Botswana. Telemed J E Health. 2012;18(1):11-13.
36. Chang LW, Njie-Carr V, Kalenge S, et al. Perceptions and acceptability of mHealth
interventions for improving patient care at a community-based HIV/AIDS clinic in
Uganda: a mixed methods study. AIDS Care. 2013;25(7):874-880.
37. Chang P, Hsu CL, Lan CF. Is PDA good for complex documentation in healthcare? Stud
Health Technol Inform. 2009;146:115-120.
38. Harkke V. Impacts of physicians' usage of a mobile information system. Int J Electron
Healthc. 2006;2(4):345-361.
39. Haroon M, Yasin F, Eckel R, et al. Perceptions and attitudes of hospital staff toward
paging system and the use of mobile phones. Int J Technol Assess Health Care.
2010;26(4):377-381.
40. Hart T, Ahlers-Schmidt CR, Chesser A, et al. Physician impressions of using text
message technology to increase vaccination compliance. Telemed J E Health.
2011;17(6):427-430.
41. Hofstetter AM, Vargas CY, Kennedy A, et al. Parental and provider preferences and
concerns regarding text message reminder/recall for early childhood vaccinations. Prev
Med. 2013;57(2):75-80.
42. Irwin TE, Nordstrom SK, Pyra M. Acceptability of mobile phone technology for tracking
cervical cancer in rural Guatemala. Int J Gynaecol Obstet. 2012;119:S375-S376.
26
43. Lau F, Yang J, Pereira J, et al. A survey of PDA use by palliative medicine practitioners.
J Palliat Care. 2006;22(4):267-274.
44. Lo V, Wu RC, Morra D, et al. The use of smartphones in general and internal medicine
units: a boon or a bane to the promotion of interprofessional collaboration? J Interprof
Care. 2012;26(4):276-282.
45. Maguire R, McCann L, Miller M, et al. Nurse's perceptions and experiences of using of a
mobile-phone-based Advanced Symptom Management System (ASyMS) to monitor and
manage chemotherapy-related toxicity. Eur J Oncol Nurs. 2008;12(4):380-386.
46. Martins HM, Jones MR. What explains doctors' usage of Mobile Information and
Communication Technologies? A comparison of US and Portuguese hospitals. AMIA
Annu Symp Proc. 2005:495-499.
47. Okazaki S, Castaneda JA, Sanz S, et al. Factors affecting mobile diabetes monitoring
adoption among physicians: questionnaire study and path model. J Med Internet Res.
2012;14(6):e183.
48. Patel M, Dine J, Asch D. Resident use of smartphones while providing patient care. J
Gen Intern Med. 2011;26:S103-S104.
49. Payne KB, Wharrad H, Watts K. Smartphone and medical related App use among
medical students and junior doctors in the United Kingdom (UK): a regional survey.
BMC Med Inform Decis Mak. 2012;12:121.
50. Pinnock H, Slack R, Pagliari C, et al. Professional and patient attitudes to using mobile
phone technology to monitor asthma: questionnaire survey. Prim Care Respir J.
2006;15(4):237-245.
27
51. Putzer GJ, Park Y. Are physicians likely to adopt emerging mobile technologies?
Attitudes and innovation factors affecting smartphone use in the southeastern United
States. Perspect Health Inf Manag. 2012;9:1b.
52. Reid SC, Kauer SD, Khor AS, et al. Using a mobile phone application in youth mental
health: An evaluation study. Australian Family Physician. 2012;41(9):711-714.
53. Seto E, Leonard KJ, Cafazzo JA, et al. Perceptions and experiences of heart failure
patients and clinicians on the use of mobile phone-based telemonitoring. J Med Internet
Res. 2012;14(1):180-189.
54. Seto E, Leonard KJ, Masino C, et al. Attitudes of heart failure patients and health care
providers towards mobile phone-based remote monitoring. J Med Internet Res.
2010;12(4):e55.
55. Valaitis RK, O'Mara LM. Public health nurses' perceptions of mobile computing in a
school program. Comput Inform Nurs. 2005;23(3):153-160.
56. Wilson C, Wu R, Lo V, et al. Effects of smartphones on pharmacist-physician clinical
communication. J Pharm Technol. 2012;28(6):234-242.
57. Wu RC, Morra D, Quan S, et al. The use of smartphones for clinical communication on
internal medicine wards. J Hosp Med. 2010;5(9):553-559.
58. Archibald D, Macdonald CJ, Plante J, et al. Residents' and preceptors' perceptions of the
use of the iPad for clinical teaching in a family medicine residency program. BMC Med
Educ. 2014;14:174.
59. Boruff JT, Storie D. Mobile devices in medicine: a survey of how medical students,
residents, and faculty use smartphones and other mobile devices to find information. J
Med Libr Assoc. 2014;102(1):22-30.
28
60. Gautham M, Iyengar MS, Johnson CW. Mobile phone-based clinical guidance for rural
health providers in India. Health Informatics J. 2014;March(online first).
61. Hsu SC, Liu CF, Weng RH, et al. Factors influencing nurses' intentions toward the use of
mobile electronic medical records. Comput Inform Nurs. 2013;31(3):124-132.
62. Kuo KM, Liu CF, Ma CC. An investigation of the effect of nurses' technology readiness
on the acceptance of mobile electronic medical record systems. BMC Med Inform Decis
Mak. 2013;13:88.
63. Sclafani J, Tirrell TF, Franko OI. Mobile tablet use among academic physicians and
trainees. J Med Syst. 2013;37(1):9903.
64. Wong G, Greenhalgh T, Westhorp G, et al. RAMESES publication standards: meta-
narrative reviews. BMC Med. 2013;11:20.
29
FIGURES
Figure 1 – Study selection flow diagram
SUPPLEMENTARY FILES
Supplementary File 1 – Characteristics of the included publications
30
Figure 1 Study selection flow diagram
4216%Publica(ons,iden(fied,and,
publica(on,abstracts,evaluated,
n%=%33%publica0ons%
48%Full5text,publica(ons,evaluated,
Not,mhealth:,4158, Not,B&F:,8, Not,health,professionals,:,9,,Total,excluded:,4168,
Not,B&F:,6,, No,methodology:,2,, Not,using,mhealth:,2, Difficulty,in,differen(a(ng,users:,3,
About,students:,2,,Total,excluded:,15,
removed,
removed,
31
Supplementary File 1 – Characteristics of the included publications
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
bald 4)57 Canada Mixed Tablet
computer
Pembroke Regional Hospital (Ontario)
Residents and
perceptors from the Family
Medicine Program
4 residents and 13 perceptors
Survey; Focus group
To identify how preceptors and
residents use tablet computers to
implement and adopt a new family medicine
curriculum and to evaluate how they
access applications (apps) through their tablet in an effort to
support and enhance effective teaching and
learning.
Most participants agreed on the importance of accessing curriculum
resources through the iPad but recognized that these required
enhancements to facilitate use. The iPad was considered to be more useful
for activities involving output of information than for input. Participants’ responses regarding the ease of use of mobile technology were heterogeneous
due to the diversity of computer proficiency across users. Residents had
a slightly more favorable opinion regarding the iPad’s contribution to
teaching/learning compared to preceptors.
68% 41% None
n-ov 3)32
Ethiopia Quantitative
Personal digital
assistant (PDA)
Addis Ababa University
(AAU) EM
residents 5 EM residents Questionnaire
To assess the feasibility of
incorporating PDAs into the AAU EM
residency program.
All felt comfortable with computer use in general. PDAs were used regularly both
on and off duty in the ED and were perceived to help with most aspects of patient care. PDAs were of particular
value in referencing the bedside management of patients presenting with infrequently encountered conditions. No
major technical difficulties were reported, although the numbers are too small to draw specific estimates from.
100% N/A None
uff 4)58 Canada Mixed
Smartphone;
Tablet computer
Four Canadian
universities
Medical students, residents, and faculty members
1,210 respondents Survey
To investigate the extent to which
students, residents, and faculty members in Canadian medical faculties use mobile devices to answer
clinical questions and find medical information.
The survey indicated widespread use of smartphones and tablets in clinical settings in 4 Canadian universities.
Third- and fourth-year undergraduate students (i.e., those in their clinical clerkships) and medical residents,
compared to other graduate students and faculty, used their mobile devices more often, used them for a broader
range of activities, and purchased more resources for their devices.
6 to 8% 47.5% None
ach
3)33 South Africa
Qualitative
Mobile phone
Umzinyathi District of
KZN
Health community
workers (HCW)
5 health workers
Focus group
To assess the acceptability and feasibility of using
Mobilize to record and submit adverse events
forms weekly during the intensive phase of MDR-TB therapy and evaluate mobile HCW
perceptions throughout the pilot period.
Mobile HCWs submitted nine of 33 (27%) expected adverse events forms,
conflicting with qualitative results in which mobile HCWs stated that
Mobilize improved adverse events communication, helped their daily
workflow, and could be successfully expanded to other health interventions.
When presented with the conflict between their expressed views and actual practice, mobile HCWs cited forgetfulness and believed patients
should take more responsibility for their own care.
N/A N/A None
ng 9)36 Taiwan Quantit
ative
Personal digital
assistant (PDA)
Veteran Medical Care
system Nurses 60 nurses Questionn
aire
To evaluate nurses’ perception of the ease of use and usefulness
of PDA application, designed with
customerized design principles.
Although the study participants were from convenience samples, the evaluation results show the high
perceived ease to use, usefulness, and willingness-to-use of an interface- enhanced PDA system involving
complex documentation.
N/A N/A Technology Acceptance
Model (TAM)
32
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
ng 2)34
Botswana Mixed Smartph
one
Public referral
hospital in Gaborone
Residents (physicians
in specialty training
7 residents Questionnaire
To explore the role of smartphone- based
mLearning with resident (physicians in
specialty training) education.
Residents reported gaining familiarity through the initial training session, help from other residents, and spending time alone with the phone. While six out of seven residents initially surveyed were unfamiliar with smartphones, these six felt comfortable with the phone after 8
weeks of use.
One resident did not
complete follow- up surveys
N/A None
ng 3)35 Uganda Mixed Smartph
one
Reach out (a community-based HIV
care organization in Kampala)
Community health
workers (CHW),
clinic staff
Interviews: 6 CHWs, 4 clinic
staff; Focus group: 3
CHWs/clinic staff, 7/8
participants per group;
Survey: 7CHWs and clinic staff
In-depth interviews;
Focus groups; Survey
To accomplish study objectives of exploring
intervention acceptability,
feasibility, and design considerations. An
intervention to improve HIV/AIDS care would involve CHWs using a
smartphone application to improve
communication, streamline data
collection, improve clinical decisions, and
receive alerts.
Qualitative results included themes on significant current care challenges,
multiple perceived mHealth benefits, and general intervention acceptability.
Quantitative results from 27 staff participants found that 26 (96%) did not have internet access at home, yet only 2 did not own a mobile phone. Likert
scale survey responses indicated general agreement that smartphones would improve efficiency and patient care but might be harmful to patient
confidentiality (3.88) and training was needed (4.63). Qualitative and
quantitative results were generally consistent, and, overall, there was
enthusiasm for mHealth technology. However, a number of potential
inhibiting factors were also discovered.
N/A N/A None
ham 4)59 India Quantit
ative
Mobile phone–based clinical
guidance system
Two rural/tribal
sites in Tamil Nadu,
Southern India
Two rural/tribal
sites in Tamil Nadu,
Southern India
16 rural health providers and 128 patients
Training programm
e; Field
testing; Questionn
aire
To use a randomized control design to
measure changes in protocol compliance
(PC) by health workers in their everyday work settings, to assess the
usability and acceptability of the
mobile application with health workers in the experimental group and to obtain patient feedback on health workers’ use of the
mobile system during treatment.
Linear mixed-model analyses showed statistically significant improvements in protocol compliance in the experimental
group. Usability and acceptability among patients and rural health
providers were very high. The results indicate that mobile phone–based,
media-rich procedural guidance applications have significant potential
for achieving consistently standardized quality of care by diverse frontline rural
health providers, with patient acceptance.
N/A N/A None
kke 6)37 Finland Qualitati
ve Smartph
one Turku Health
District Physicians 24 general
practitioners, 6 specialists
Interviews
To describe and explain the possible and real impacts on
the work processes of physicians caused by introducing a mobile
information system to their work
The impact on the work routines of the users was rather limited, despite the
generally positive attitude towards the system. The actual usage patterns and the settings in which the system is used
vary, and along with these the perceived impacts of the system on the
work habits and the routine of the users.
N/A N/A
DeLone and McLean
Information System (IS)
Success Model
33
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
on 0)38 Ireland Quantit
ative Mobile phone
Regional Hospital
(537-bed, secondary-care referral
Centre)
Medical junior
doctors
60 medical junior doctors
Questionnaire
To document the pattern of mobile phone usage by medical staff in a
hospital setting, and to explore any perceived
benefits associated with mobile phones.
All participants used mobile phones while at work. For 98.3 % the mobile
phone was their main mode of communication while in the hospital.
Sixty-two percent (n = 37) made 6–10 calls daily purely for work-related
business.. For 98 percent of participants, most phone calls were work-related. Regarding reasons for
using mobile phones, all reported that using mobile phone is quicker for
communication. Mobile phone usage is regarded as a more efficient means of
communication for mobile staff than the hospital paging system.
100% 100% None
rt 1)39 USA Quantit
ative
Text messagin
g reminder system
Single metropolitan
statistical area
(Sedgwick County, Kansas)
Physicians
149 family physicians and pediatricians who provide
immunizations
Questionnaire
To evaluate the feasibility of a text
messaging reminder system (for childhood vaccination) from the
physician’s perspective
The vast majority of physicians who inform parents of children’s vaccine
schedules are comfortable with technology, but there is still hesitancy (neutral or unwilling) to implement a text-message reminder system for
childhood vaccine schedules. This may be due to the lack of empirical evidence supporting the use of this technology for
health reminders or the lack of willingness to implement another
system.
68.5%
None (0%)
currently use text or
email to generat
e reminde
rs to parents
None
etter 3)40 USA Quantit
ative
Text messagin
g reminder system
Four academically-
affiliated pediatric
clinics in New York City.
Parents, providers
and medical
staff
200 parents, 26 providers (physicians (16), nurses
(10)) and 20 medical staff
Questionnaire
To assess parental, provider, and medical staff opinions about
text message reminder/recall for
early childhood vaccination.
Providers were supportive of vaccine-related text messages. Most of them
were supportive of using text messaging to remind parents to
schedule a vaccine appointment (88%), keep an existing appointment (92%),
and return for missed vaccines (88%). Their biggest concerns were correct cell
phone numbers, appointment availability, and increased call volume.
35/52 (67%) of
those approache
d. 26/35 (81%)
agreed to participate
N/A None
u 3)60 Taiwan Quantit
ative
Mobile electronic medical record system
Large-scale hospital
located in southern Taiwan
Clinical nurses
720 clinical nurses
Questionnaire
To empirically test the factors affecting
nurses’ use intention of MEMR based on the Theory of Diffusion of
Innovations (DOI) proposed by Rogers
Multiple regression analysis of the responses identified three innovative
characteristics, compatibility, complexity, and observability, as significantly influencing nurses’
intentions toward adopting mobile electronic medical records, whereas relative advantage and trialability did
not. In addition, nursing seniority affected nurses’ intentions significantly
toward adopting mobile electronic medical records.
82% N/A Diffusion of Innovations
(DOI)
34
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
n 2)41
Guatemala
Quantitative
Mobile phone
and Text messaging system
Cervical cancer
screening and
treatment program in rural San Cristobal
Mid-level practitioner
s
33 government health workers
Questionnaire
To examine health workers' opinions
about the acceptability of using cell phone
technology and SMS texting to report cases
of cervical cancer.
Access to cell phones and electricity for charging phones, as well as familiarity with texting was nearly universal in this
group of rural Guatemalan health workers. The vast majority of
respondents felt that cell phone technology would be acceptable for
sending patient data to a confidential cervical cancer registry. Concerns of
the minority of respondents about using cell phones for this purpose should not be ignored. Patient confidentiality is of paramount importance and must be
protected as we work to increase cervical cancer data collection.
N/A
Not for that use. But 91%
report daily
access to a cell phone
and 85% have used their
phone to send
and receive
text messag
es.
None
o 3)61 Taiwan Quantit
ative
Mobile electronic medical record system
Hospital nursing
department of a 1300-
bed Taiwanese
hospital
Registered nurses
in wards during
December 2010
665 nurses Questionnaire
To investigate nurses’ personality traits in
regard to technology readiness toward Mobile electronic
medical record system (MEMR) acceptance.
Of the four personality traits of the technology readiness, the results posit that nurses are optimistic, innovative,
secure but uncomfortable about technology. Furthermore, these four personality traits were all proven to
have a significant impact on the perceived ease of use of MEMR while
the perceived usefulness of MEMR was significantly influenced by the optimism trait only. The results also confirmed the
relationships between the perceived components of ease of use, usefulness,
and behavioral intention in the Technology Acceptance Model toward
MEMR usage.
75.7% N/A
Technology Acceptance
Model (TAM) and
Technology Readiness Index (TRI)
u 6)42 Canada Quantit
ative
Personal digital
assistant (PDA)
Palliative services in
different settings across
Canada
Physicians
72/200 physicians who
are involved with the
delivery of palliative services
Survey (with open questions)
To understand better the current patterns of
PDA use among physicians who are
involved with the delivery of palliative
services across Canada, factors that
encourage PDA adoption by non-users,
and how PDAs can further enhance palliative care
practices
58,3 % (42) of respondents currently use PDAs on a daily basis, and almost
half of the 30 non-users planning to adopt PDA within the year. Use of PDA
is mainly to organize practice and to look up medical references. Some use their PDAs to store patient information
ant to access a central EPR. In palliative medicine, six thematic areas
are suggested: medical references, EPR, staying connected, personal productivity, clinical research, and
issues/concerns. Most PDA use is self-motivated in nature, with little to no
guidance, training, or support available at the organizational level.
36% 58.3% None
35
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
o 2)43 Canada Qualitati
ve Smartph
one
General Internal
Medicine (GIM) unit at two teaching hospitals in a
large Canadian city
where the Smartphones
technology have been
implemented
Clinicians: Nurses,
physicians, social
workers, pharmacist
s, occupational therapist
31 clinicians: 15 nurses, 8 physicians (including 4 residents), 4
social workers, 3 pharmacists
and 1 occupational
therapist
Semi-structured interviews
To examine clinicians' perceptions of the
usage of Smartphone devices and the Web
paging system in General Internal
Medicine (GIM) unit
Study participants described positive perceptions of Smartphone usage on
the GIM wards where the email or telephone function was perceived to be
valuable for particular contexts. Specifically, healthcare professionals
valued the use of emails when communicating nonurgent issues and the availability of the phone function
that enabled access to clinicians especially in urgent situations. Dissatisfaction, however, was
expressed over the suitability of these smartphone features in different
communication contexts as well as discrepancies between clinicians over
the appropriate use of the communication modes.
N/A N/A None
uire 8)44
UK (Scotland mainly)
Mixed
Advanced
Symptom Manage
ment System
(ASyMS)
Home-care setting for
patients with lung, breast
and colorectal
cancer
Nurses
Questionnaire: 35 nurses from
6 study sites who had used The ASyMS;
Interviews: 10 nurses
Questionnaire;
Interviews
To explore the perceptions of nurses who participated in the
RCT and who used ASyMS to manage
chemotherapy-related toxicity in clinical
practice
These results demonstrate that overall nurses who used ASyMS had positive
perceptions of its use in clinical practice to monitor and manage chemotherapy-related toxicity. They felt that ASyMS
resulted in improvements in the management of symptoms and
therefore the delivery of care to this patient group.
Pre-study questionna
ire: 28 (80% );
Post-study questionna
ire: 22 (63%)
100% (was an inclusio
n criteria)
None
ins 5)45
Portugal and USA
Quantitative
Mobile Information and
Communication
technologies
(MICT) devices
2 Portuguese hospitals and
2 US hospitals
Physicians 267 physicians Questionnaire
To present evidence on ownership and usage of several
Mobile Information and Communication
technologies (MICT) devices by doctors in two Portuguese and
two US hospitals, considering both
devices owned by individuals and those
supplied by the hospital
69 % of doctors reported they used MICT devices. The main tasks for these
devices were being used were to access medical reference information,
the Internet and drug reference applications. Ownership is not clearly
related to either usage pattern of frequency of use. Providing handheld computers also did not lead to higher number of users, higher frequency of use or significant differences in tasks
carried out.
40 % to 90%
according to the setting
183/267 (69 %) None
aki 2)46 Japan Quantit
ative
Mobile diabetes monitoring system
47 prefectures
across Japan Physicians
471/590 physicians of
whom 134 were
specialized in internal and
gastrointestinal medicine
Questionnaire
To evaluate the perceptions and user acceptance of mobile diabetes monitoring among Japanese
physicians.
Physicians consider perceived value and net benefits as the most important
motivators to use mobile diabetes monitoring. Overall quality assessment
does affect their intention to use this technology, but only indirectly through perceived value. Net benefits seem to be a strong driver in both a direct and
indirect manner, implying that physicians may perceive health
improvement with ubiquitous control as a true utility by enhancing cost-effective
monitoring, and simultaneously recognize it as a way to create value for
their clinical practices.
79.8% N/A
Updated DeLone and
McLean Information System (IS)
Success Model
36
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
el 1)47 USA Quantit
ative Smartph
one
Internal medicine at
three academic medical centers
(Brigham and Women's
Hospital, the Hospital of
the University of
Pennsylvania and the
University of California, San Diego)
Internal medicine residents
125 residents
Questionnaire (with
open questions)
To determine the percentage of internal
medicine residents using smartphones in
clinical settings, to assess how the
devices were being used, and to evaluate
perceptions of the impact of smartphone use on patient care.
A significant proportion of residents are using smartphones as a tool for providing patient care. These
smartphones may play an important role on improving physician efficiency,
patient outcomes and health care quality.
N/A 79 (63.2%) None
ne 2)48 UK Quantit
ative Smartph
one
One United Kingdom
healthcare region
Medical students
and Junior doctors
257 medical students and
131 junior doctors
Questionnaire (with
open questions)
To identify the extent to which junior doctors and medical students own smartphones and use them to enhance their clinical activities;
and how often they use apps for education
and clinical professional
development.
This study found a high level of smartphone ownership and usage among medical students and junior doctors. Both groups endorse the
development of more apps to support their education and clinical practice.
15% (students);
21,8% (junior
doctors)
79% (student
s); 74,8% (junior
doctors)
None
ock 6)49 UK Mixed Mobile
phone
Lothian (Central
Scotland) and Kent
(South East England).
Include both city and rural environments
General practitioners, asthma
nurses and people with
asthma
66/150 GPs, 64/150 nurses and 202/389
patients
Questionnaire
To explore the attitudes of patients
and primary care professionals to using mobile technology in
order to monitor asthma and to assess the potential impact on
their asthma management
The low completion rate probably reflects the current status of mobile phone-facilitated care as a minority
interest for 'early adopters' of technology. Even for the enthusiastic
minority, mobile phone technology raised questions of clinical benefit, impact of self-management, and
concerns about workload and cost, which will need to be addressed prior to
wider acceptance.
44% (GPs); 42%
(nurses); 52%
patients
N/A None
zer 0)1 USA Quantit
ative Smartph
one
Two community hospitals in
the southesatern United States
Nurses 80/200 nurses Survey
To investigate the decision to adopt a smartphone among
healthcare professionals,
specifically nurses. The study examines the constructs that
affect an individual’s decision to adopt a
smartphone by employing innovation attributes leading to perceived attitude.
The study provided empirical support for five of the hypotheses. The
innovation characteristics of observability, compatibility, job
relevance, internal environment, and external environment were found to
influence a user’s attitude toward using a smartphone.
40% N/A
Technology Acceptance
Model (TAM) and Diffusion
of Innovations
(DOI)
37
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
zer 2)50 USA Quantit
ative Smartph
one
Community hospitals and
academic medical
centers in the southeastern United States
Physicians 103/400 physicians
Questionnaire
To investigate the innovation factors that
affect a physician's decision to adopt an
emerging mobile technological device such a smartphone
This study provided empirical support for seven of our eight hypotheses. The relationship of attitude toward using a
smartphone and behavioral intention to use a smartphone was found to be
statistically significant. We examined innovation characteristics and found that observability, compatibility, job relevance, personal experience, the
internal environment, and the external environment had an influence on a
user’s attitude toward using a smartphone.
26% N/A
Technology Acceptance
Model (TAM) and Diffusion
of Innovations
(DOI)
d 2)51 Australia Mixed
Mobile Tracking Young
People's Experien
ces (mobilety
pe) program
General adolescent outpatient
health clinic of the Royal Children's Hospital (RCH) in
Melbourne, Victoria
Physicians (paediatricians) and
14-24 years old
adolescents
6 paediatricians
and 47 adolescents
Completion of
mobiletype entries;
Questionnaire;
Structured interviews
To evaluate the utility, usability and feasibility
of the mobiletype program in clinical
settings with adolescents and
adolescent paediatricians.
Paediatricians found the program helpful for 92% of the participants and
understood 88% of their patients' functioning better. Participants reported
the data reflected their actual experiences (88%) and was accurate
(85%), helpful (65%) and assisted their paediatrician to understand them better
(77%). Qualitative results supported these findings.
N/A N/A None
ani 3)62 USA Quantit
ative Tablet
computer
Medical centers
recognized by the
Accreditation Council for Graduate Medical
Education
Academic physicians
and resident trainees
1,457/2,942 resident trainees;
513/2,942 fellowship level
trainees; 972/2,942
attending level physicians
Survey
To perform a prospective,
nationwide email survey evaluating the
use of tablet computers, their
applications, and their challenges among
physicians at medical centers recognized by
the Accreditation Council for Graduate Medical Education.
Increased level of training was associated with decreased support for mobile computing improving physician capabilities and patient interactions.
There was strong and consistent desire for institutional support of mobile
computing and integration of mobile computing technology into medical
education. While many physicians are currently purchasing mobile devices,
often without institutional support, successful integration of these devices
into the clinical setting is still developing.
47.9% 40% None
o 0)53 Canada Mixed
Mobile Phone-based Heart
Failure Remote
Monitoring System
Heart Function Clinic in a
large urban teaching hospital
(University Health
Network in Toronto)
Heart failure
patients and their
health care providers
(physicians and nurse practitioner
s)
Questionnaire: 94/100
patients; Interviews: 20
patients and 16 clinicians
Questionnaire;
Semi-structured interviews
To assess the attitudes of heart
failure patients and their health care
providers from a heart function clinic in a
large urban teaching hospital toward the
use of mobile phone-based remote
monitoring.
Patients and clinicians want to use mobile phone-based remote monitoring and believe that they would be able to
use the technology. However, they have several reservations, such as
potential increased clinical workload, medicolegal issues, and difficulty of use for some patients due to lack of visual
acuity or manual dexterity.
Questionnaire: 94% N/A None
o 2)52 Canada Qualitati
ve
Mobile Phone-based Heart
Failure Remote
Monitoring System
Heart Function Clinic in a
large urban teaching hospital
(University Health
Network in Toronto)
Heart failure
patients and
clinicians (cardiologis
ts and nurse
practitioners)
22 heart failure patients and 5
clinicians
Semi-structured interviews
To provide in-depth insight into the effects of telemonitoring on selfcare and clinical management, and to
determine the features that enable successful
heart failure telemonitoring.
Mobile phone-based telemonitoring enabled patients to positively change
their lifestyle behaviors and to improve their quality of life, including reducing
anxiety. The telemonitoring system also improved clinical management, by providing real-time physiological
information and alerts. The in-depth qualitative analysis revealed several
system characteristics that contributed to improved heart failure management, such as (1) having immediate self-care and clinical feedback, (2) being easy and quick to use, and (3) providing
tangible benefits to the end-users (ie, the patients).
N/A N/A None
38
dy Country Design Mobile device Setting Population Sample Data
collection Aim of the study Main findings Response rate
Rate of use
Theoretical framework
tis 5)54 Canada Qualitati
ve
Tablet computer
; Personal
digital assistant
(PDA)
Public Health and
Community Services
Department
Nurses 8 public health nurses
Focus groups; Written
reflections
To investigate the perceptions of PHNs in
a school health program about their
experiences with using in order to discover
factors that enable and constrain the use of
MC, examine nurses’ perceptions of the
impact of MC on PHN practice, and explore changes in nurses’ perceptions of MC
over time.
Users experienced a period of adaptation to MC and needed
consistent support from information technology staff during this time. Public
health nurses perceived that MC increased efficiency and flexibility in
their day-to-day work, thereby enabling more client-focused care. Public health
nurses felt more professional and valued, having been given innovative technological tools to do their work. At the same time, this technology created a social gap between themselves and their clients. Public health nurses felt
more connected to their employer online, while feeling more “visible” and “trackable”; simultaneously, they felt more connected to, yet isolated from,
their team members.
N/A N/A None
on 2)55 Canada Qualitati
ve Smartph
one 1 tertiary-
care hospital Pharmacist
s and physicians
10 professionals
(3 pharmacists, 3 physicians, 4 residents)
Interviews
To prospectively determine whether the
use of smartphone devices
by medical residents improved pharmacist
efficiency by decreasing the total time to resolution of pharmacists’ clinical
interventions compared to traditional
modes of communication.
Most respondents believed that the smartphone improved communication.
It decreased wait times and allowed triaging and prioritizing issues, It was
also useful to arrange face to face meetings. The problems perceived by
users were that possible misinterpretation of the message and
the lack of user friendliness of the smartphone.
N/A N/A None
u 0)56 Canada Quantit
ative Smartph
one
Toronto General Hospital
Residents and nurses
91 residents; Presurvey: 27 of 48 nurses;
Postsurvey: 35 of 54 nurses
Survey
To evaluate the use of smartphones
to improve communication on internal medicine
wards
In this pilot study of using smartphones and e-mail, residents perceived that it significantly improved their efficiency. Nurses perceived a reduction in the
time spent trying to communicate with clinicians
Presurvey: 65%
(resident), 56%
(nurses); Postsurvey
: 71%
(resident), 65%
(nurses)
N/A None
ng 0)7 Canada Quantit
ative
Personal digital
assistant (PDA)
Community Care Access
Centre (CCAC)
Home healthcare
nurses
91 home healthcare
nurses Survey
to analyze the main factors of adoption of
mobile information technology by
homecare nurses and support personnel,
through an empirical study involving 91 homecare nursing personnel using
wireless PDAs in their current activities for 1
month.
This study found, in concordance with many IS studies that perceived
usefulness and perceived ease of use are reasons explaining a significant portion of the intention to use the
wireless mobile system by homecare nursing personnel.
Of the 91 responses,
seven were
incomplete and
excluded from the
data analysis,
leaving 84 valid
responses.
N/A
Technology Acceptance
Model 2 (TAM2)