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Mobile Health: Four Emerging Themes of Research
Upkar Varshney
PII: S0167-9236(14)00175-4DOI: doi: 10.1016/j.dss.2014.06.001Reference: DECSUP 12501
To appear in: Decision Support Systems
Received date: 16 July 2013Revised date: 22 April 2014Accepted date: 1 June 2014
Please cite this article as: Upkar Varshney, Mobile Health: Four Emerging Themes ofResearch, Decision Support Systems (2014), doi: 10.1016/j.dss.2014.06.001
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Mobile Health: Four Emerging Themes of Research
Upkar Varshney
Department of Computer Information Systems
Georgia State University
Atlanta, Georgia 30302-4015
E-mail: [email protected]
ABSTRACT
Mobile health has been receiving a lot of attention from patients, healthcare professionals,
applications developers, network service providers and researchers. Mobile health is more than just some
healthcare applications on a mobile phone and it can involve sensors and wireless networks in monitoring
various conditions, mobile devices to access numerous healthcare services, healthcare professionals to
make decisions and provide emergency care, and for the elderly to manage their daily activities in
independent living. More specifically, m-health can result in major advances in (a) expanding healthcare
coverage, (b) improving decision making, (c) managing chronic conditions and (d) providing suitable
healthcare in emergencies. To help realize these advances, there are major research challenges that need
to be addressed. We classify these challenges in four categories of (a) patients related, (b) healthcare
professionals related, (c) IT related and (d) applications related challenges. Within each category, we
identify several research problems, and we present some high-level and preliminary solutions along with
an agenda for future research. The paper may provide a platform for future research and decision-making
related to patients, healthcare professionals, applications, and infrastructure. These decisions will
significantly impact how future mobile health services will be designed, developed, evaluated, and
adopted globally.
Keywords: Mobile health, information technologies, decision making, emergencies, applications
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1. Introduction
Mobile health is broadly defined as “healthcare to anyone, anytime, and anywhere by removing
locational and temporal constraints while increasing both the coverage and the quality of healthcare” [59].
Mobile health is much more than just accessing healthcare applications on a mobile phone as m-health
can involve sensors and wireless networks in remote monitoring various conditions, mobile devices to
access a variety of healthcare services, healthcare professionals to make decisions and provide emergency
care, elderly to manage their daily activities for independent living among other things. Thus mobile
health can include numerous sophisticated applications that deal with disease prevention & wellness [61],
monitoring and remote care [47], mobile decision making [1], and emergency interventions [59]. In
addition, several applications on horizon include highly personalized health monitoring [42], mobile
healthcare data access [23], and sophisticated mobile telemedicine [65].
We do not claim that m-health can fix all the healthcare problems, but it can improve the reach of
healthcare, decision making, management of chronic conditions and emergencies. Mobile health can truly
change the way healthcare services are delivered: from the current healthcare professionals-controlled to
healthcare professionals-managed. One of the major effects of m-health is empowering patients with
information to help them make suitable healthcare decisions, follow advice and medical regimen, and in
general have better control of their healthcare. The availability of numerous m-health applications, more
than 100,000 at the time of writing this paper, is a major step towards such empowerment of patients.
Some other areas of improvement include reduction in cost, more efficient processes, and meeting some
of the workload needs of healthcare professionals. Certainly much more work is needed to evaluate the
effectiveness of mobile health in terms of quality of decision making, quality of care, efficiencies of
healthcare processes, outcomes of patients, and reduction of overall cost.
1.1 Related Advances
Several advances in sensing devices, miniaturization of low-power electronics, and wireless networks
[5] are fueling the emergence of mobile health. The wireless technologies can be effectively utilized by
matching infrastructure capabilities to healthcare needs. These include the use of location tracking,
intelligent devices, user interfaces, body sensors, and short-range wireless communications for health
monitoring; the use of instant, flexible and universal wireless access to increase the accessibility of
healthcare providers; and reliable communication among medical devices, patients, health-care
professionals, and vehicles for effective emergency management.
The recent FCC spectrum allocation for mobile medical telemetry can improve both the quality and
quantity of medical data that can be transmitted from patients to healthcare professionals [23]. The
interoperability among various systems is being addressed by the development of medical standards,
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industry alliances, and consortiums, such as the IEEE 802.15.6 wireless body area networks (WBANs),
Continua Alliance and the European Telecommunications Standards Institute’s eHEALTH [23].
One of the major advances fueling the growth of m-health is the worldwide availability of mobile
technologies, such as mobile phones of 3rd
and 4th generation (3G and 4G), that are usable almost
anywhere anytime. The decline in price of access, improved portability and comfort of people in using
mobile technologies have all helped m-health moving forward at a rapid pace.
1.2 The Role of M-Health
M-health can play many different roles based on the patients’ conditions, their needs and availability
of healthcare services. The roles include providing necessary healthcare information anytime anywhere,
providing remote and expanded care, access to healthcare professionals anytime anywhere via mobile
devices, integrated and real-time information to healthcare professionals for decision making, and the
broadcasting of information in cases of disasters.
M-health can reach to places where there is little or no healthcare is available such as rural areas
especially in developing countries and can also allow people in urban areas and developed countries to
access some healthcare services while being mobile/away from their places. M-health is likely to be
incremental in the developed countries as it plays an adjunct role to what is already supported by e-health.
M-health is likely to be revolutionary in developing countries, where little infrastructure is available and
presence of mobile phones can lead to rapid adoption of mobile health, especially in rural and remote
areas. M-health in developing countries will play a major role in health interventions [8], prevention of
communicable diseases [61] and in improving health literacy [33]. A comparison of m-health in
developed and developing countries is shown in Table 1 and different scenarios are presented in Figure 1.
Table 1. M-health Comparison in Developed and Developing Countries
Attributes Developed Countries Developing Countries Comments
Infrastructure Well developed Somewhat developed and
access/reliability challenges
The Interoperability of infrastructure
still need to be addressed
Most suitable
applications
Mobile apps for health
management
Information on diseases,
reminders for care, remote
care
Revolutionary (primary) in
developing countries, evolutionary
(secondary) in developed countries
Barriers A lack of clear policy,
cost of access, security
& reliability challenges
Lack of infrastructure,
cultural and social barriers,
lack of education, role of
alternate medicine
Numerous barriers can be studied in
adoption of m-health in developing
and developed countries
Regulatory
Environments
Evolving Evolving One of the biggest challenges
Future of
M-health
Secondary but important
healthcare role
Potential for primary
healthcare role in
underserved/rural areas
Many challenges need to be
overcome
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Cellular NetworksSensor Network
The Internet/PSTN
Home or Hospital
(a) Mobile Health in Developed countries with 3G/4G Wireless Networks
Satellites
Cellular NetworksHome or Common Area
(b) Mobile Health in Developing countries with 2G/3G Wireless Networks
Figure 1. M-health in Developed and Developing Countries
M-health will also change the way healthcare services are delivered. With mobile devices being
integrated in various healthcare processes, many sub-processes will be automated while rest can be
efficiently supported by healthcare professionals. For example, m-health can enable highly personalized
healthcare in general and suitable interventions for patients to managing their chronic conditions in
particular. Highly sophisticated interventions can be designed, developed and offered to patients to
manage their complex regimen of medications to improve medication adherence, avoid adverse drug
events (ADE) and communicate with healthcare patients as and when necessary in real-time.
1.3 The Limitations
M-health cannot solve all problems of healthcare as it is highly dependent on sensors, mobile devices
and wireless infrastructure. In places where there is no wireless coverage or when mobile devices have
battery or access problems, mobile health is simply not possible.
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M-health cannot, and should not, completely automate the delivery of healthcare services. There are
many m-health applications that must have human involvement due to their potential for damage or injury
to the patient's health. FDA has offered some guidelines on what mobile health applications can do and
what they cannot and who is liable if a patient is injured due to mobile health applications. In general, if
an application is providing healthcare information and is not connected to any healthcare delivery device,
the FDA rules will not apply to such applications.
Mobile health is not likely to play a primary role in cities in developed countries, where both
"wireline" network infrastructure as well healthcare facilities are readily available. Certainly much more
work is needed to evaluate most suitable m-health services in developed as well as developing countries.
One of the goals of this paper is to integrate advances and various challenges for mobile health and
identify many important research problems. Towards this goal, we first envision what mobile health can
do by focusing on (a) extending the reach of healthcare, (b) improving the healthcare decision making
processes and their outcomes, (c) better management of chronic healthcare conditions and (d) managing
emergencies in section 2. We then present a framework for mobile health based on four categories of
research problems based on patients, healthcare professionals, IT and m-health applications in section 3.
Then, in section 4, we present research problems and some preliminary solutions for four categories that
can be expanded by other researchers. Then we make some concluding remarks in section 5.
2. Applications and Benefits of Mobile Health
We focus on what mobile health can do by addressing its ability in (a) extending the reach of
healthcare services, (b) improving decision making, (c) preventing and managing chronic conditions and
(d) providing faster emergency care. We next discuss these categories one by one.
2.1 Extending the Reach of Healthcare
2.1.1 Removal of Constraints & Improved Access
Mobile health can remove locational constraints as there is no need for patient and healthcare
professionals to be in the same location or to be stationary. Support for mobility is one of the most
exciting features of mobile health. The temporal constraints could be removed for some cases, termed
asynchronous version such as an expert reading the patient's records and sending the diagnosis to the
primary care physician and patient at a different time. For synchronous version, the patient and healthcare
professionals are using mobile health system at the same time, possibly in different locations. Some
mobile health applications could exist in both versions such as Mobile Health Monitoring [32, 53, 54]
where monitoring of vital signs for certain events is synchronous while monitoring of weight loss, sleep,
and daily activity is asynchronous [40].
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2.1.2 Implementation & Focus
Mobile health can be implemented in two variations: automated and human-assisted to support the
informational and direct healthcare applications, respectively. Further, the focus can be user-centric vs
provider-centric. There are numerous examples among the 100,000 health applications for smart phones
[23] including medical reference applications [31]. A 2x2 classification is shown in Figure 2. It should be
noted that not all mobile health applications can be classified by such simple method. One of the
challenges is to classify numerous mobile health applications to help patients decide which applications
are similar and which ones are different in what ways. This would also help in developing new
applications as identified by the classification scheme [75].
Automated Human-assisted
User Centric
Provider Centric
Mobile Personal Health
Record
Mobile Decision
Making
Mobile Health
Monitoring
Mobile Medical
Reference
Figure 2. A 2x2 Classification of M-health Applications
2.1.3 The Role
In places where healthcare services are readily available, m-health will play a supportive role such as
accessing health information or services while being mobile. In rural and remote areas in both developing
and developed countries, it will play a primary role. The examples are behavioral healthcare in rural areas
using cell phones, adherence reporting and appointment reminders [34], behavioral interventions to
reduce cardiovascular risk factors [8], vaccine delivery in sub-Saharan Africa [61], and improving health
literacy [33].
2.1.4 Delivery Model
The healthcare delivery model will evolve from the current healthcare professional-controlled care to
healthcare professional-managed care. For some cases, such as for patients in poor conditions, the
healthcare professionals will still play a major role, while patients in better conditions would benefit more
from the healthcare professional-managed model of care. As more and more patients start using mobile
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health applications such as mobile PHR, medical databases, and healthcare informational services, the
need for care will change and will move towards the healthcare professional-managed model.
2.2 Improving Healthcare Processes and Decision Making
One of the major goals of m-health is to make healthcare processes more efficient and improve the quality
of outcomes. Many healthcare processes are very complex and involve people, technologies and rules.
Good understanding of healthcare processes and how people interact with technologies in unpredictable
situations, how physicians use technologies, how medical decisions are made, how people take
medications, and how elderly live alone will help towards achieving this goal. By improving various
healthcare processes, mobile technologies can also improve the outcomes of various healthcare activities.
2.2.1 Healthcare Processes
Access to patient's most recent information could reduce the need for "duplicated" tests. Also, access to
current medical knowledge can improve the quality of decision making [37]. Mobile technologies can
lead to efficiency improvements such as decreased time for task completion and accessing history [1]. By
collecting and delivering vital information at the point of care, hospitals can improve efficiency and safety
[1]. It has been shown that the use of mobile systems reduced the task completion time significantly [38].
The average time on monitoring patients was reduced about 40%, while the total time on indirect tasks
was reduced about 30% [11].
2.2.2 Decision Making
Healthcare professionals are trained to perform these decisions under extreme circumstances with little or
no advance notice sometimes. Healthcare professionals consider symptoms, medical history, lab results
and diagnostic tests among others in reaching to medical decisions. Many times, additional alternatives or
choices become available as the decision making process moves forward. Mobile technologies can play a
very important, but assistive, role in decision making by supporting the needed information anytime
anywhere to anyone authorized. This could include mobile access to expert systems and evidence-based
medicine tools [10].
2.2.3 Speed of Decision Making
Mobile technologies can support faster access to healthcare professionals and health information and that
could lead to faster decision making [37] such as those needed for emergency cases. The speed vs
accuracy of decision making should be studied in different scenarios of preventive care, urgent care,
emergency care, home health, and long-term care. Although, mobile technologies can lead to
improvements in some steps of decision making, certainly more work is needed towards evaluating the
impact on overall decision making.
2.2.4 Correctness of Decision Making
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Many medical errors occur due to the lack of correct and complete information at the location and time it
is needed, potentially resulting in wrong diagnosis and drug interaction problems [58, 20]. Mobile
technologies, by improving information access and tracking of patients, supplies and medications, can
help to reduce information-related medical errors. More work is needed to evaluate the impact of mobile
technologies on other errors, including process errors and knowledge/skill errors [36], such as wrong
treatment with right diagnosis.
2.3 Preventing and Managing Chronic Conditions
Chronic diseases, such as heart disease, stroke, cancer, diabetes, and arthritis, are among the most
common, costly, and preventable of all health problems in the U.S. and heart disease, cancer and stroke
lead to 50% of all deaths [7]. Mobile technologies can help in preventing and/or managing chronic
diseases by monitoring physical and behavioral health, medications, and activities of daily living (ADL),
and by providing mobile-enabled interventions and changing these as needed with time. A model for
prevention and management of chronic conditions is shown in Figure 3.
Live
Data
Healthcare Services
Patient Healthcare
Professional
Health
Database
Mobile
Device
Delivery
Systems
Live
Information
Decisions
Live
Information
Stored
Information
Figure 3. A Model for Prevention and Management of Chronic Conditions
2.3.1 Prevention
The prevention involves mobile health monitoring dealing with activities [54], exercises, health
promotion tools and messages [17, 35], and caloric and dietary monitoring [66]. These could be
implemented in multiple forms such as wearable monitoring systems and sensors in shoes [45] to classify
daily activities, Internet-aware exercise machines, cell-phone based applications [57], musical feedback
and exercise [41], electronic wellness diary, and social networking-based systems [35]. Other prevention
tools include fall detection system [12], wrist-worn integrated health monitoring device [24], guidance
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system for the elderly [52], stray prevention system for the elderly with dementia (GIS) [28], and,
monitoring system analyzing deviations from daily rhythms to predict health changes [17].
2.3.2 Management
To manage chronic conditions, mobile technologies can support interventions for medication adherence
by using reminders to patients and remote monitoring of adherence. Mobile technologies can support
effective management of chronic diseases by faster communications and feedback from healthcare
professionals. This can motivate patients, especially younger people, to take better control of their life
style. Management of diabetes can be well supported by mobile health [2]. For dietary monitoring, a
mobile application can track caloric information, store the food and activities, and keep daily calorie data
[56] and can work with swallowing detection using neck sensors [3].
The monitoring of bipolar disorders using mobile device can reduce the possibility of an episode [47]
and can support the behavioral healthcare needs in remote areas. To manage Parkinson Disease, a sensor
system can monitor the coordination between respiration and locomotion as part of rehabilitation [64]. To
help reduce chronic back pain, a smart system can detect and inform a person sitting with incorrect
posture [16].
2.4 Helping in Emergencies
2.4.1 Emergency Healthcare Processes
The goal is to find what the problem is and fix it quickly to avoid immediate risks to the patients. The
emergency processes include (a) incidence detection, (b) transportation to healthcare facilities, (c) getting
patient's information, and (d) making suitable decisions and (e) providing care. Mobile health can play a
very important role in emergencies as it can help in speeding up some the above processes (Figure 4). The
solid lines indicate the sequence in the current emergency care, while dashed lines indicate the steps due
to m-health. More specifically, the sequence in the current emergency care is 1, 2, 3, 4 and 5. M-health
can improve this to 1, 2, and 5 or 1, 2, 4, and 5, or 1, 3, 2, and 5 or 1, 3, 2, 4, and 5. This can be used in
making suitable decisions on how m-health can be utilized in emergency care.
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Detecting
Incidence (1)
Transporting
Patient (2)
Collecting
Patient
Information (3)
Making
Decisions (4)
Providing
Care (5)
Figure 4. Emergency Care and M-Health Enhancements
2.4.2 Improving and Speeding Existing Processes
Incidence detection and transportation involves finding out location and extent of the emergencies related
to healthcare and then managing it to meet the healthcare needs of the people involved. One solution to
this is to design and implement intelligent emergency response using the information from mobile and
wireless networks. The information could include locations of emergencies derived from location tracking
of enhanced 911 calls. The information from wireless networks can also be used to find the best routes
and allowing inter-vehicular communication for traffic routing. This could be combined with finding the
closest hospital(s) with the needed care and also to check the availability of hospital space.
2.4.3 Access to Information in Emergencies
The access to information depends on the condition of the patient. One solution is to store the patient
information on cell phones, or in implanted or wearable RFID chips that patients can carry. There are
important issues of reliability, access, identity theft, limited access, limited storage and what should be
stored, and, benefits vs privacy trade-off that should be addressed. Other solutions include information on
how to access personal health records. The devices can also store health history and known medical
conditions as abbreviated electronic health record. A possibility is to provide access to EMR via person’s
cell phone as many emergency medical services now utilize a person’s cell phone for identification.
Fragmented health information was the main cause of preventable medical errors responsible of a number
of deaths each year [58]. No patient should die because the system blocked access to vital data and any
such access can show as a violation with a log of who accessed what information [39]. The information
from multiple sources can be integrated and adapted to mobile devices of healthcare professionals [44].
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3. A Framework for Mobile Health
3.1 Structured Survey of M-health Literature
As part of the development of m-health framework, we realized that there should be some dimensions in
the framework. To derive the dimensions, we performed a comprehensive literature survey of mobile-
health. We considered literature in three related areas of Health Informatics, Biomedical Informatics,
and Information Systems (Table 2).
Table 2. The List of Journals Included in the Survey
Health Informatics (4) Biomedical Informatics (5) Information Systems (8) International Journal of Medical
Informatics (IJMI)
Journal of American Medical
Health Affairs (HA)
Informatics Association (JAMIA)
Health Services Research (HSR)
IEEE Transactions on IT in BioMedicine
(TITB)*
IEEE Journal on Selected Areas in
Communications (JSAC)
IEEE Sensors Journal
IEEE Reviews in Biomedical Engineering
Mobile Networks and Applications
(MONET)
MIS Quarterly (MISQ)
Information Systems Research (ISR)
Journal of MIS (JMIS)
Decision Support Systems (DSS)
European Journal of IS (EJIS)
Information Systems Journal (ISJ)
Journal of AIS (JAIS)
Communications of the ACM (CACM)
*: now known as IEEE Journal of Biomedical and Health Informatics (JBHI)
We conducted a literature survey of journals in Information Systems, Healthcare Informatics, and
Biomedical Informatics for m-health research published between Jan. 2000 and Dec. 2012. The search
involved title, abstract, and keywords for "mobile OR wireless OR pervasive" AND "health". While
studying the literature, some unrelated articles were removed such as those on use of mobile devices
causing health problems. The survey yielded 102 articles in above journals. Overall, the trends showed
nearly doubling of articles every four years with 15 articles during 2001-2004, 26 during 2005-2008, and
60 during 2009-2012. A closer examination of the contents of the articles reveals several categories in
terms of patients, healthcare professionals, IT and applications. Several articles have more than one
category and are thus classified (Table 3).
Table 3. Analysis of Published Articles on M-health
Articles from: total The Four Identified Categories of Research Patients Healthcare
Professionals
IT Applications
IS Journals: 16 2 (13%) 10 (63%) 6 (38%) 2 (13%)
HI Journals: 53 20 (38%) 17 (32%) 14 (26%) 4 (8%)
BMI (IEEE)
Journals: 33
18 (55%)
7 (21%)
26 (79%)
5 (15%)
Total Journals: 102 40 (39%) 34 (33%) 46 (45%) 11 (11%)
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IS Conferences: 27 10 (37%) 12 (44%) 10 (37%) 2 (7%)
Note: As some articles could fit in more than one category, the total percentage in all categories could exceed 100%.
As shown in Table 3, the number of m-health articles in Information Systems includes 16 in journals
(1 in EJIS, 10 in DSS, 5 in CACM) and 27 in major IS conferences including ICIS, AMCIS, ECIS and
HICSS. Many other IS journals do not have any m-health articles yet. Information Systems is the only
area with majority of articles on healthcare professionals. Biomedical Informatics primarily focuses on IT
with 79% of its articles fitting in that category of research.
For all m-health literature, IT is the most common research category with 45% articles relying on IT
to address the healthcare challenges. About 11% of the articles focus on the design, development and
testing of m-health applications. This is expected to increase as more applications are becoming available
for mobile devices and are being tested in various clinical and non-clinical situations. Biomedical
Informatics has the highest percentage of articles (15%) addressing applications issues. Many of the
proposed systems would be tested using a variety of methods including those based on theories. A
classification of m-health research and potential outlets is included in appendix (Figure A1).
We acknowledge that there are several other categories that are highly important area of research and
should be included in a comprehensive framework for mobile health. These categories are (a) legal and
regulatory environment including security and (b) adoption and related theories among others. Due to the
length restriction, we had to limit the scope of the proposed framework to the above four categories. It is
our sincere hope that others will expand the proposed framework to include the additional categories and
research problems in m-health that are not included in this paper.
3.2 Development of M-health Framework
In addition to the support from the literature for a research framework for m-health, we reflected on
many related research frameworks that have been proposed for mobile applications in other areas. More
specifically, we studied several frameworks in future decision support systems [67], mobile commerce
[73], wireless networking [71], mobile health monitoring [68, 69], and the context-aware services [74].
Using the current m-health literature and research frameworks from mobile application in other areas and
our own understanding of what m-health is and what it can become in future, we derived the framework
as shown in Figure 5.
In the high-level view of m-health framework, patients can interact with mobile health applications,
which are supported by Information Technologies. Patients may receive care from healthcare
professionals directly or via m-health applications. Many such combinations are possible. Many m-health
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services can be provided to patients that do not rely on m-health applications, but use specialized
devices/sensors such as those for health monitoring. In the next few sub-sections, we discuss these four
categories. The details on research and preliminary/possible solutions are presented in section 4.
Information
Technologies
Applications
PatientsHealthcare
Professionals
Figure 5. A High-level View of M-health Framework
Our simple framework for m-health can be expanded in several different directions based on the
context of research. One such example of expansion in the context of m-health as a service is shown in
Figure 6. When m-health is considered as a service, there are some differences as m-health can be (a)
constrained due to regulatory and legal environment, (b) the patient may not completely understand the
implications even when signing the consent form, (c) some else may be paying for the service, while the
patient’s life and condition may be impacted directly. However, m-health will allow regular healthcare
care to be negotiated for lower cost, better quality, negotiated pricing by using applications/agents to
negotiate with some willing healthcare providers. However, the same cannot be said for emergency care,
which should not be negotiated and the focus of m-health service should be enable fastest care meeting
the needed threshold of quality at the closest location. It is likely that in future multiple healthcare
professionals will advertise their services for comparison shopping (middleware supported) based on
context, history and price (within regulatory framework). Although the healthcare human resources are
limited in US and in most countries, the IT can offer almost unlimited support for M-health services in
multiple ways by working with applications that are value-adding to healthcare. Intelligent agents as an
application can negotiate various attributes such as appointment time, cost, and can utilize past history of
care, outcomes, availability of care as multiple metrics for quality of service. These can the summary of
all possible choices to patients and even can act as recommender system. This service-oriented view of m-
health is shown in Figure 6.
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Information
Technologies
Applications
PatientsHealthcare
Professionals
User Infrastructure
Middleware/Intelligence
Network Infrastructure
BuyersSuppliers
Intermediary
Facilitator
HP: Limited and Regulated Supply Patients: Demand for M-health Services (both via applications and direct by healthcare professionals)
Applications: Providing unlimited services with and without human involvement
IT: Supporting unlimited access to mobile applications and other medical devices used in m-health
Figure 6. A Service-oriented View of M-health Framework
3.3 The Patients
Patients of different demography such as adolescents, adults, and the elderly living independently or
in assisted living/nursing homes would interact with mobile health very differently due to their health
conditions, attitudes towards care, and knowledge and comfort with mobile technologies and healthcare
applications. These differences should be included in the design, development and implementation of
mobile health applications and infrastructure. M-health will play a major role for the elderly and to some
extent for the adolescents; and somewhat limited role for active healthy adults with limited need for
healthcare services and easy access to other technologies for e-health.
3.4 Information Technologies
The most suited characteristics are support for mobility of patients and healthcare professionals, instant
access to information and the immediate attention to devices by everyone. The suitable technologies for
healthcare could be divided among four categories: implanted, wearable, portable, and environmental
[59]. The respective examples are RFID and sensors, Smart Shirts [26], handheld devices, and Smart
Homes [15, 54]. These technologies differ in terms of complexity, user interface, reliability, replacement
and battery requirements, and the cost.
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While each of these technologies can play a role in mobile health, more work is needed towards
selecting (and even replacing if needed) most suitable technology for the patient (Table 4). This decision
could have a major impact on if and how long patients would use mobile technologies. The limitations
that hinder acceptance of mobile and ubiquitous technologies include short battery life [1]. Also, varying
social contexts of individual use result in different social influences that affect the individual’s
perceptions of user satisfaction with the mobile technology [51].
Table 4. Suitable Wireless Technologies for Healthcare
Implanted Wearable Portable Environmental
Suited for Monitoring of internal
organs/compensating for
deficiency in operations
Monitoring of vital
signs
Interacting with
patients using mobile
apps
For independent
living for adults and
the elderly
Some Examples Pacemakers, Implanted
sensors and “ingestible”
RFID
Smart Shirts Smartphone with
sensors and mobile
health apps
Smart House
Limitations Potential for malfunction
Difficult to replace
Emerging technology
Usability for the
elderly not clear
Reliability of devices
and networks
Expensive and not
easily available yet
The Future Limited and specific use Potential for
widespread use
(especially among
young people as
fashion statement)
Most market due to
widespread use of
Smartphones with
built in sensors
Smart house may
become standard
house
Most likely used by People with specific
challenges where portable
and wearable technologies
are not useful
The young Everyone The adults and the
elderly in
Independent living
Comments/additio
nal insights
High cost of surgery and
(long-term) devices
High cost (not mass
produced yet)
Most cost
effective/wide
spread deployment
Most expensive (20-
30% on top of regular
building cost )
3.5 Applications
There are more than 100,000 mobile health applications available today for different mobile devices. The
current mobile health applications deal with healthcare information access, health and disease advice,
patient history, and decision support. M-health applications still have plenty of room to grow to take full
advantage of unique mobile platform features and truly fulfill their potential [31]. More advanced
applications can include personalized health monitoring [42], adaptable and context-aware applications,
and applications based on multi-dimensional interfaces. There is a need to study the effectiveness of
different mobile health applications for different conditions and patients. More work is also needed in
creating a detailed classification of these applications. Research is also needed to improve the security and
privacy aspects of these applications and make patients aware of these challenges (Figure 7).
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The access speed,
quality and details
Context-generation
And processing
Privacy
Restrictions
Patient’s
Health Condition Treatment and
Delivered Care
Patient
Information
Level of emergency Level of controls
The overall
Quality-of-care
Vital signs, activity
and conditions
Figure 7. Decision Making for Privacy and Benefits in M-health
3.6 Healthcare Professionals
Healthcare professionals will play a major role in mobile health as they would still make most of the
medical decisions related to direct care. Mobile health applications can be divided in two classes (a)
where a patient interacts with applications without the involvement of HP and (b) where a patient
interacts with applications with the involvement of HP. The applications can be one way or two ways. A
possible taxonomy is shown in Figure 8 below.
Healthcare Professionals
Not Involved
One-way
Two-ways
Involved
ApplicationsReminders/Messages
Mobile Telemedicine
Accessing Medical
Information
Interacting with M-health
Applications
Figure 8. A 2 x 2 Taxonomy of HP and Applications
In these scenarios, when HP is involved, he/she will certainly influence the adoption of mobile health,
while when HP is not involved, the adoption will be primarily influenced by applications and the
technology.
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We first discuss when HP is not involved. In this case, mobile applications should be personalized to
the patient based on his/her abilities, health conditions, and some incentives can be offered to patients to
adopt mobile health.
When HP is involved, the situation becomes much more complex. The portability, task structure,
spatial mobility, and system reliability influence the use of mobile technology by healthcare
professionals, their degree of satisfaction with the technology, and realization of the net benefits [9]. Their
acceptance and use of technology and applications is critical towards the success of mobile health [30].
Their familiarity with devices and applications affect the adoption of mobile applications [11, 38]. The
mobile technologies should be integrated in the workflow of healthcare professionals. The performance of
nurses has been shown to improve when they accessed information anytime anywhere [1]. The role of
incentives for healthcare professionals needs to be evaluated in mobile health adoption. The support from
insurance companies and the government agencies on payment guidelines on various m-health services
will clarify some uncertainty on what and how care provided would be compensated for mobile health.
4. Major Challenges and Research Problems
To describe major challenges and research problems, we utilize the key attributes of m-health, as
introduced in section 2. These are (a) overcoming locational constraints and support for mobility, (b)
supporting both synchronous and asynchronous versions of m-health, (c) moving from healthcare
professional-controlled to healthcare professional-managed care, (d) supporting both automated and
human assisted care, (e) supporting both user-centric and provider-centric m-health, (f) improving the
speed, quality and correctness of decision making, (g) improving processes and efficiency, (h) supporting
decision making by providing anytime anywhere access to information, (i) supporting effective
management of chronic conditions as well as emergency care, and, (j) improving the quality of health
outcomes.
The framework for mobile health presented in section 3 can be extended to a research agenda for
mobile health. The four dimensions, namely patients, applications, healthcare professionals and
information technologies, are included with more specific research problems (Figure 9). The IT
infrastructure can overcome locational constraints and provide support for mobility as part of overall
support for mobile health. It can also enable mobile health applications in providing synchronous and
asynchronous versions of m-health in developing as well as developed countries. IT, applications and
healthcare providers can lead to improved processes, better and faster decision making, and highly
personalized care. The empowered patients can lead to better management of their health by utilizing both
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automated and human-assisted care. Further, these all together can lead to much improved quality of
health outcomes while reducing the overall cost of care and improving the quality of life for patients.
Applications•Implementation (automated
vs human assisted)
•Focus (patient vs healthcare
professional)
•Role (primary vs secondary)
•Emergencies
•Chronic care
•Effectiveness
Patients• Access to HC Information
• Support for Wellness
•Independent Living
•Types (children, adults, elderly)
• Quality of care
•Chronic vs acute condition
•Monitoring (life-style,
medications, health, daily
activities)
•Physical vs behavioral
conditions
•Privacy
Healthcare
Professionals•Decision Making
•Access to Information
•Current Knowledge
(reference/databases)
•Suitable Interventions
•Extending the reach
•Delivery of care
•Speed vs optimality
•Tracking of patient’s status
•Quality of care
•Medical errors
•Payments
Information
Technologies•Reliability and Access
•Devices
•Network and Location
Management
•Autonomous
•Wireless Networks
Mobile
Health
Functionalize
Support
InfluenceAssists
Figure 9. Research Agenda for Mobile Health
4.1 Research related to Applications
Most of the current mobile healthcare applications, including over 100,000 available for mobile devices,
deal with healthcare information access, health and disease advice, patient history, and decision support
(Figure 10). This is not a complete listing, but the most common existing mobile health applications and
some emerging applications that can meet many goals of mobile health. Most of these applications are
user-centric, while some are provider centric such as mobile DSS and mobile medical reference. Some of
these applications could have synchronous and asynchronous versions. The choice of using one or the
other can be based on the context of care such as patient’s condition and/or network coverage and
connectivity in non-emergency situations. These applications will support better decision making by
providing anytime anywhere access to information and this in turn will lead to improved health outcomes.
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Mobile
Access to
Healthcare
Information
Mobile
Personal
Health
Record
Increased Personalization & Complexity
Mobile
Health &
Disease
Advice
Mobile
Healthcare
Delivery
Mobile
Activity
Monitoring
& Care
Wellness
Diary &
Pro-active
Health
Appointment
&
Medication
Reminders
Mobile
Telemedicine
& Remote
Care
Mobile
Access to
Healthcare
Professional
Mobile
Medical
Reference
Mobile
Access to
Drug
Information
Mobile
Healthcare
Supplies
Tracking
Mobile
Prenatal
Care
Mobile
Robotic
Surgery
Mobile
Decision
Support
Systems
Mobile
Diabetes
Management
Indirect Mobile Healthcare Direct Mobile Healthcare
Mobile
Cardiac
Management
Increasing Patient Empowerment
Figure 10. The Current and Emerging Mobile Health Applications
We need to evaluate the effectiveness of currently available applications as well as identify more
advanced applications for the future. The effectiveness of mobile health should include diverse set of
patients including adolescents, adults and the elderly. The effectiveness of mobile health applications can
be evaluated clinically, using design science approaches, as well as using theoretical models and user
requirements. There is also a need to classify the m-health applications to help everyone conceptualize the
differences and similarities, and also to identify the need for new applications. This can also help decision
makers in mobile health [75].
The advanced applications could be designed and developed for different populations and diseases,
chronic as well short-term. M-health applications still have plenty of room to grow to take full advantage
of unique mobile platform features and truly fulfill their potential. Also, the near-term introduction of
two- or three-dimensional visualization and context-awareness could further enhance m-health
applications' usability and utility [31]. More advanced applications can include games for healthy eating
and wellness. In one trial, children playing the game ate a healthy breakfast 52 percent of the time as
compared to 20 percent of children not playing this game [48]. New applications that can support
behavioral, technical, social and financial interventions for medication adherence, wellness, life-style, and
management of chronic conditions would be highly desirable.
An example of an advanced application is shown in Figure 11. This application monitors the
medication consumption and keeps track of when the patient took doses and also informs designated set
of people [77]. Such high-level solutions can be expanded, implemented and tested for usefulness,
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adoption and post-adoption studies as part of mobile health. This is an example of m-health where some
parts, such as medication reminders, can be automated and some parts where complex decisions have to
be made using clinical knowledge and experience, such as decision on changing medications based on
strange side effects, will need to be human-assisted.
Medication
Container
and
Processor
Notification/Alerts
to designated parties
Multi-network access
(both wireline and wireless)
Reminders/alarms
Reminder 1 Reminder 2 Reminder 3
Medication Time
Med ABC (1T)
Med XYZ (2T)
Medication Time
Med ABC (1T)
Med XYZ (2T)
Medication Time
Med ABC (1T)
Med XYZ (2T)
Dispensing of
medications
Monitoring of
medication use
& vital signs
Information on
Medications
Notifications
and displays
Medication
adherence goal
Figure 11. An Advanced Application for M-health
Another application is personalized health monitoring, where wearability, ease of use, affordability,
and interoperability must be addressed [21] and systems must be safe for both the patient and the operator
[13]. Many other applications will emerge from smart wearables, such as SmartShirts. The requirements
of smart health wearable are security, suitable user interface, and user acceptance [32] and effectiveness
of user interface for clinically meaningful representation to the healthcare professionals [18]. The use of
wearable sensors, ring sensors and watch sensors have been proposed, designed and tested for
effectiveness [4, 6, 43]. Ring sensors are effective for monitoring of heart rate, oxygen saturation, and
heart rate variability [6] while watch sensors, as "all-in-one" system [4] for blood pressure, skin
temperature, oxygen saturation, and ECG. Wearable sensors in health monitoring can be very effective
[42], however the accuracy of detection can be further improved [29] and more work is needed in
addressing adaptability [22]. A patient-focused algorithm for health monitoring is presented in [69] where
various health conditions, the current context of the patient and current values of numerous biomedical
parameters are included in decision making.
Additional Research Opportunities: What are the most suitable applications for mobile health? How to
design and evaluate applications for primary and secondary roles of mobile health in developing and
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developed countries? Can global applications be designed to adapt to changing roles in different places?
Considering the number of applications, how to create a classification of mobile health applications?
4. 2 Research related to Patients
More research needs to be done to address how to decide suitability of possible m-health implementation
as automated vs human assisted. To start with, patient’s condition and severity can be considered. More
indirect care with less chance of any harm to patients can be supported by automated mobile health, while
the direct healthcare, such as interventions for serious conditions, can be better supported by human
assisted m-health. Further, some steps of care for chronic conditions can be selectively automated, while
human assistance can be better utilized for more complex steps. As mentioned before, medication
reminders for patients can be automated, while to change medications and/or doses due to strange side
effects can be more safely performed by healthcare professional. The impact of either or both
implementations on chronic health conditions and quality of health outcomes for different set of patients
can be studied.
The patients include children, adolescents, adults, the elderly living independently or assisted living
or nursing homes would receive and use mobile health very differently. This is due to their health
conditions, attitude towards care, and knowledge and comfort with mobile technologies and healthcare
applications. One of the fastest growing segments of patients is the elderly, where about 40% of US
seniors, or people 65 years and older, experience one or more forms of physical and/or cognitive
disabilities. The elderly experience a higher degree of fragility, have lower levels of physical strength, and
may experience a degree of cognitive decline.
Both from the cost and quality of life perspectives (independent living), it is highly desirable that
elderly stay in independent homes as long as possible before moving to assisted living and then to nursing
homes. One of the Grand Challenges in healthcare is to delay the transition to assisted living by 5 years
[59]. To address this, more research is needed in monitoring and analyzing activities of daily living
(ADL), including hygiene, food, social needs, medications, sleep, chronic conditions, and safety. The five
major areas for research related to the elderly are (a) fall prevention, (b) support for mobility, (c) stray
prevention, (d) monitoring of dementia and (e) monitoring of daily activities. The cognitive decline for
the elderly and the need for support from mobile health are shown in Figure 12. The need for support
from m-health increases as the cognitive decline increases with elderly patients moving to assisted living
and then to nursing home. Decision makers will have to consider these limitations when selecting one of
several m-health options to support the elderly in independent living, assisted living and nursing homes.
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These constraints will also lead to utilization of mobile health which is more long-term, user-centric, and
highly intelligent to support the elderly as they experience cognitive and physical decline.
The Level of
Support Required
The State of Patients
Elderly
@NursingHome
Elderly
@AssistedLiving
Elderly
@Home
Active Adults
Patient’s
Cognitive
Capabilities
Level for Satisfactory Daily Living
*
*
*
*
Figure 12. Cognitive Capabilities and the Level of Support Required
A high-level system for mobile health monitoring, a highly personalized and sophisticated mobile
health application, is shown in Figure 13, where the elderly can be monitored at any location (independent
home, assisted living or nursing homes) using wearable (sensors or smart shirts) or environmental
technologies (such as SmartHome) [59]. Such systems can provide a combination of automated as well as
human-assisted care and can have synchronous and asynchronous operation based on the needs and
condition of patients. Mobile health monitoring is one of several examples (from Figure 11) where m-
health enables overall healthcare to move from HP-controlled to HP-managed. Many important decisions
can be made about their healthcare needs based on their current conditions and past history. Also, suitable
interventions can be offered such as those based on motivation and support, reminders for activities and
medications, support for declining cognitive abilities among others.
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Wireless Networks (4G, W-LAN)
Base Station
or Access point
Base Station
or Access point
Healthcare
Providers
Patient in hospital
(mobile or
Stationary)
Patient in nursing
home (mobile
or stationary)
Patient indoor
(mobile or
stationary in
independent
living)
Patient outdoor
(mobile or
Stationary in
independent
living)
Figure 13. The Mobile Health and the Elderly in Multiple Places
The use of mobile technology and the instant attention it receives can worsen the interaction between
patient and healthcare professional. More specifically, the quality and length of interaction may be
affected negatively. The increased automation of healthcare processes by mobile devices may affect some
patients who need more interactions with healthcare professionals, especially the elderly. Any difficulty
in use or delayed information due to infrastructure failures/malfunction may worsen the quality of care. In
some cases, an increased number of false positives could lead to wasting of resources or false negatives
missing the events needing certain care. The patient's comfort with various mobile technologies for
healthcare could negatively impact the success of many healthcare services. Many issues of trust, physical
and emotional comfort with wearable sensors and devices and embedded sensors and devices in beds,
bathroom, kitchen and appliances (Figure 14) should be studied in more details. From capabilities point of
view, such smart environments and infrastructure can lead to numerous advances in mobile health for
patients, however more efforts are necessary to evaluate suitability and usability of smart infrastructure
for mobile health environment.
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Memory Support System
Fall Prevention and Detection Systems
Smart Medication System
E
N
E
R
G
Y
A
W
A
R
E
S
Y
S
T
E
M
Daily Activity Support System (context-aware)
R
E
L
I
A
B
L
E
S
Y
S
T
E
M
Social Interaction/Entertainment System
A
L
E
R
T
&
M
O
N
I
T
O
R
I
N
G
ECG sensors
Oxygen saturation
sensor
Blood pressure sensor
Temperature sensors
Swallowing detection sensors
Breathing sensor
Posture detection
sensors
Figure 14. Sensors and Smart Infrastructure
Another major segment of patients that will play a major role in m-health are adolescents and young
adults. First these patients are not as sick as the elderly and are much more technology-aware and users.
These will play an important role in accessing information and acting as a care giver for their friends and
families using mobile technologies. Much more work is needed to address the needs and expectations of
the adolescents and young adults by mobile health.
Additional Research Opportunities: How to include the conditions of patients and their level of
technology literacy in designing suitable m-health applications and technologies? What are the most
suitable interventions for adherence with medications and treatment for different patient demography?
How can mobile health support independent living for the elderly for ten additional years and save $500K
per person? What are the most suitable applications for the adolescents and young adults? How to
facilitate the need of these to play the role of caregivers to their friends and family members?
4.3 Research related to Healthcare Professionals
Mobile health could also lead to several challenges due to its inherent nature, its reliance on mobile
technologies, and how healthcare professionals and people interact with mobile technologies. As m-health
enables healthcare services to move from HP-controlled to HP-managed, healthcare professionals will
need to make serious adjustments in their roles as m-health evolves. More research is needed to address
the changing roles of healthcare professionals in terms of what care can be automated and what care must
remain human-assisted, how healthcare professionals will deal with “empowered” patients with instant
and mobile access to latest healthcare knowledge, and both complexity and usability challenges of mobile
health. More work is also needed to address roles of healthcare professionals with mobile health in
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emergency care, such as those supported by RFID, sensors and mobile devices, and their abilities to
handle potential side and/or negative effects of mobile technologies. In some sense, m-health may further
increase the technology competence required for healthcare professionals.
With mobile health, one of the major challenges faced by healthcare professionals is the presence of
“empowered” patients. On one hand, such patients will not need to be educated about healthcare; however
their attitude and knowledge of healthcare may interact with the healthcare professionals’ decision
making. Many healthcare professionals may not enjoy these “empowered” patients. Certainly, much work
is needed to study the complexity and quality of healthcare in m-health environment. Also, some work is
needed to address the complexity in care provided to patients with differing backgrounds in m-health.
Healthcare decision making is complex in terms of number of parameters and variables, outcome
possibilities, and information that must be processed and healthcare professionals need to make these
complex decisions with no margins for errors. Mobile health will increase the frequency of interruptions
as the healthcare professionals can be interrupted using mobile devices. The use of mobile devices on top
of other medical technologies and tasks can increase the level of multitasking. Combining this with the
complexity of many healthcare processes and tasks, there is some chance for an increased cognitive load,
or even cognitive overload for healthcare professionals [63]. The frequent interruptions, multitasking and
increased cognitive load [25, 46] may result in some errors of attention and even attribution errors [55].
The situation could become more complex if the interface of mobile device is not suitable to fast reading
and writing, such as poor visibility or hard to read fonts. This may lead to incorrect reading or incorrect
entry of important information. Several steps can be taken to reduce cognitive load including (a) reduction
of information, (b) suitable and improved presentation of information, and (c) reduction in process
complexity. There are several ways to reduce the amount of information, but any such reduction is also
limited by the potential for loss of critical information which may affect the quality of needed care to the
patient. One of general techniques is context-awareness, where only the most relevant information along
with the context is utilized [14]. This process includes filtering of some information based on identified
relevancy, however, healthcare professionals could access such information if required for decision
making. As the reduction of information is directly related to the cognitive load [55], this appears to be
one promising method to reduce cognitive load of healthcare professional. As suggested by CLT [55],
among the components of cognitive load, intrinsic load is influenced by the inherent difficulty of the task.
Therefore, simplifying the overall process for healthcare professionals will lead to some reduction in
intrinsic load. The process simplification may be implemented in multiple ways including filtering of
information where decisions only involve most relevant information. Additionally, automation of several
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tasks in decisions for healthcare delivery could simplify the process. The prior training of healthcare
professionals could help reduce “perceived” complexity of the process.
A high-level solution for decision making in healthcare using mobile device is shown in Figure 15,
which implements some of the above enhancements to reduce cognitive load [76]. Better interfaces can be
developed that can adapt to cognitive capacity of decision makers or can be programmed to different
healthcare professionals as needed.
Minimize the Number of Screen Switching
Color
Coding
Most
Important
Items
Least
Important
Items
Screen 1 Screen 2 Screen N
Minimize the Number of Informational Items
Visual and Auditory Items
Figure 15. Cognitive Load and Healthcare Professionals in M-health
Additional Research Opportunities: What enhancements can be made in information representation,
display, and processing by mobile devices, both with small screen and not-so-small screens? Can
personalization of mobile devices improve the quality and speed of decision making? How most suitable
device-human interfaces can be designed and evaluated for different population segments? How to speed
up decision-making while improving the quality of decisions and resulting health outcomes? What
processes can be improved and how? How to study the effectiveness of these changes in processes? How
to identify any side effects of such changes?
4.4 Research in Information Technologies
As identified in section 2, m-health involves overcoming locational and temporal constraints and the
support for mobility for patients, healthcare professionals and medical devices involved in care delivery
among other things, IT and more specifically, mobile computing infrastructure must support these
requirements at different levels. These can range from small area mobility, such as a room, to wide-area
mobility, such as a country or even planet. The infrastructure should also support both synchronous and
asynchronous versions of mobile health based on needs and availability of mobile networking resources.
As mobile health will likely play a primary role in developing countries, minimal m-health requirements
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can be derived to ensure that network infrastructure can provide the necessary support for m-health.
Infrastructure can also play in providing the needed access to healthcare information anytime anywhere
and thus support the quality and speed of decision making in m-health. The infrastructure can also lead to
prioritized allocation of network resources to meet different requirements of regular and emergency m-
health services.
The capabilities and limitations of underlying wireless infrastructure would affect the overall experience
of patients and healthcare professionals with mobile health. More work is needed in addressing several
requirements of wireless infrastructure. One way is to define healthcare quality of service (H-QoS) for
integrated research in healthcare infrastructure as follows:
Reliability: It can affect the ability to access information when you really need it. A major challenge for
most wireless networks, it can be affected both by lack of network coverage as well as malfunctions of
devices and failures of infrastructure components [59]. Lack of interoperability with other systems and
interference can also affect the access to necessary information [23].
Access to Healthcare Data: To satisfy this key requirement of mobile health, the infrastructure should be
able to connect patients and healthcare professionals to applications and servers and allow quick access to
the desired data. This would need physical connectivity, sufficient bandwidth and real-time delivery or
low delays. There are many high-end mobile health applications, such as ultrasound images, that will
require significant bandwidth from the underlying wireless networks to meet the medical quality
requirements [19].
The current 3G/4G cellular wireless networks can provide physical connectivity based on the location
and network coverage of patients and healthcare professionals, but bandwidth limitations could affect
real-time access to healthcare data and applications [59]. Wireless LANs can provide bandwidth, but real-
time delivery or low delay access is a limitation. Infrastructure components can be strategically placed to
support mobile healthcare applications in terms of coverage and data capacity [49].
Support for Mobile Devices and Sensors: The mobile health environment is likely to involve
heterogeneous mobile devices and sensors. Work is needed in supporting a range of mobile devices with
their characteristics and limitations. More work is needed in improving medical usability of sensors and
mobile devices including how medical information can be best represented on mobile devices.
Additionally, research is needed to address level of discomfort in data collection and the design of user-
friendly interface for elderly [23].
Network and Location Management: Mobile health can be supported by multiple different networks
such as cellular networks, wireless LANs [65], satellites and ad hoc networks [60]. Further, several
wireless networks will need to work together as patient's information can be collected by sensors, then
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transmitted using Bluetooth network to a mobile device, which can then use a 3G/4G wireless network
[50]. Therefore, some research is also needed in creating integration of wireless solutions.
M-health systems can be designed and evaluated using the approach shown in Figure 16, where various
kernel theories, such as cognitive load theory and health promotion model, can be used to derive
requirements for m-health systems. These requirements can then be used in the design and evaluation of
m-health systems, which can then influence the kernel theories.
Cognitive
Load
Theory
Requirements
Generation
and Analysis
Health
Promotion
Model
Cognitive
Processes
and Adherence
Evaluation of
M-health
Systems
Design of
M-Health
Systems
Generation of Models
And Theories
Figure 16. Design and Evaluation of M-Health Systems
Additional Research Opportunities: How to enable and enhance the existing infrastructure for mobile
health? Are software, hardware and networking enhancements sufficient to provide reliable and quick
access to the information anywhere anytime? How to design smart mobile-health applications to
overcome varying limitations of infrastructure and provide the same experience to the patients and
healthcare professionals?
5. Conclusions
Mobile health is an emerging area of research and has attracted some attention from different
segments of healthcare, technology and management research. One of the goals of this paper is to
integrate many of these advances and also identify some important research problems. We presented a
framework for mobile health with four categories of patients, healthcare professionals, IT and m-health
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applications. Then we presented a research framework to discuss many important and emerging research
problems in m-health. As much as we are tempted, we do not label our framework as comprehensive and
the final word in mobile health which is still emerging area of research and can evolve in many different
directions. There are some limitations of the proposed framework including its limited focus on four
categories. A highly desirable extension of the framework could include additional categories of (a)
regulatory environment and security and (b) adoption of mobile health. We expect that other researchers
will expand the proposed framework to include these additional categories while identifying numerous
research problems.
Mobile health can further lead to many important advances in healthcare and information
technologies. These are proactive health and wellness management, where chronic conditions can be
detected and managed much before any major complications, design and use of medications that are most
suited to individual patients, healthcare systems that are context aware to provide necessary interventions
as needed for health and medications, smart technologies that can sense and support the needs of elderly
in independent living. Personalized and intelligent monitoring of patients can lead to better health
outcomes at lower healthcare cost. It is our hope that this paper leads to more research in identified areas
and, the proposed framework and high-level solutions are useful in furthering progress in this important
and emerging area.
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Appendix: Research Outlets, Impact of M-health
Mobile Health
Mobile Health
Engineering
Prototyping/Implementation
of Systems
IEEE Journal on Bio
and Health Informatics
Mobile Health
Computing
Design/Modeling
of Systems
Decision Support
Systems/IEEE/ACM
Journals
Sub Area
Typical
Research
Activity
Possible Outlets
Mobile
Health-IS
Theory-based
Study of M-health
Special issues of
IS/DS Journals
Mobile Health
Management
Analytical Modeling
of M-Health
DS Journals
Figure A1: Mobile Health Research Areas, Activities and Possible Outlets
Table A1. The Impact of M-health at Different Levels
The Level Impact (Issues & Challenges) Comments
Individual Level (Patient) Major impact (adherence, how the care
is received, information on healthcare)
A majority of work in m-
health is focusing on the
patients
Team Level (Care giver,
healthcare professionals)
Major impact (efficiency, quality and
speed of delivery of care, reduction in
cost)
Some work in m-health is
focusing on healthcare
professionals
Organizational Level (Healthcare Providers,
Employers, Insurance,
Government)
Some impact (security, billing, cost,
incentives, outcomes, wellness and
prevention, disaster care)
Little work is being done to
address organizational level
impact of m-health
Inter-Organizational
Level (e.g. Regulator to
Device Manufacturer)
Less impact (security and privacy of
communications and information
exchange, partnerships for m-health,
regulatory changes)
Little work is being done to
address inter-organizational
level impact of m-health
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Biographical Note
Upkar Varshney is currently Associate Professor of Computer Information Systems at Georgia
State University, Atlanta. His current interests include mobile health, pervasive computing, and
wireless networks. He has authored over 150 papers including 70 in national and international
journals. He is the author of Pervasive Healthcare, published by Springer in 2009 and 2010. He
is credited with several “first” papers in streams of mobile commerce and pervasive healthcare.
According to Scholar-Google, his papers are among the highly cited and have been cited more
than 4000 times.
He was the founding co-chair (with Prof. Imrich Chlamtac) of International Pervasive Health
Conference (http://www.pervasivehealth.org/previous/index.html) in 2006 and the steering
committee co-chair for 2008 conference (http://www.pervasivehealth.org). Upkar was the
program co-chair for Americas Conference on Information Systems (AMCIS-2009). Upkar has
presented over fifty tutorials, workshops, and a few keynotes at major wireless, computing, and
information systems conferences.
He has also received grants totaling $500K from several funding agencies including the National
Science Foundation. His teaching awards include Myron T. Greene Outstanding Teaching
Award (2004), RCB College Distinguished Teaching Award (2002), and Myron T. Greene
Outstanding Teaching Award (2000). He has served or is serving as an editor/guest editor for
several major journals including IEEE Transactions on IT in Biomedicine, IEEE Access,
ACM/Springer Mobile Networks (MONET), Decision Support Systems (DSS), and IEEE
Computer.
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Highlights
We present an integrated view of mobile health.
Mobile health can lead to many significant improvements in healthcare.
There are many important challenges in mobile health.
We classify mobile health challenges in four categories.
For each category, the challenges and possible solutions are discussed.
