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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

[email protected]

Keywords

m-health; healthcare provider; adoption; systematic review; mixed methods

Word count: 3709

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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.

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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

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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

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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

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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

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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

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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

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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.

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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

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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

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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

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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

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(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

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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

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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

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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

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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

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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

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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.

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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



Rate of use


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



Rate of use


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



Rate of use


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



Rate of use


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



Rate of use


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


Model (TAM) and Diffusion

of Innovations

(DOI)

37



Rate of use


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


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;


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


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



Rate of use


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


Model 2 (TAM2)

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