eHEALTH
Transporting Information to Transform Health Care
Arkalgud Ramaprasad, Sridhar S. Papagari
University of Illinois at Chicago, Chicago, IL 60607, U.S.A.
Joy Keeler
The MITRE Corporation, McLean, VA 22102-7539, U.S.A.
Keywords: eHealth, Health care, Ontology, Ontological analysis.
Abstract: The ‘e’ in eBusiness, eCommerce, eGovernment, and eHealth represents the transformation of the
traditional domains by the current ability to transport information using information and communication
technologies. In this paper we present an ontological analysis of the transformation of health care by
eHealth. The five dimensions of the ontology are derived by parsing the definition of eHealth as
‘transporting information to transform health care’. They are: (a) information, (b) spatial transportation, (c)
temporal transportation, (d) semiotic transportation, and (e) health care. Each dimension is defined by a
taxonomy. Each sentence, formed by concatenating categories across the five dimensions using appropriate
conjunctive words and phrases, is a natural language descriptor of eHealth. The set of all such sentences is a
closed description of eHealth.
1 INTRODUCTION
Health care, at its core, is information intensive. For
example, the physician-patient encounter
(Ramaprasad and Johnson 2000), Magnetic
Resonance Imaging (MRI), modern genetic research
(Ambrose, Ramaprasad et al. 2003), and the
administration of health care benefits require rich
and voluminous information exchange. Not
surprisingly, information and communication
technologies have transformed health care and
continue to do so. They hold the promise of
transforming it even more radically in the near
future. eHealth is the application of these
technologies to transport information to transform
health care to make it more efficient and effective
(Eng, Maxfield et al. 1998; Weber 1999; Johnson,
Kumar et al. 2000; U.S. Department of Health and
Human Services 2000; Eng 2001; U.S. Department
of Commerce 2002; Ortiz and Clancy 2003; Boulos
2004; Oh, Rizo et al. 2005; Valenta, Brooks et al.
2007).
The research and practitioner literature on
eHealth is vast and growing rapidly (Oh, Rizo et al.
2005). Its size and the rate of growth attest to
eHealth’s importance. However, they also make it
difficult to systematically synthesize, interpret, and
apply it to the design and development of eHealth
systems. We address the complexity using an
ontology derived by parsing the definition of
eHealth as ‘transporting information to transform
health care.’ We synthesize (a) the extant academic
and practitioner literature on eHealth, and (b)
insights from an industry-university forum on the
topic conducted in 2005 over a six-month period,
using the ontology.
In the following we will first present the
ontology derived by parsing our definition of
eHealth. Then, we will discuss the topics
corresponding to the ontology in the following
sequence: (a) transporting personal, medical, and
business information; (b) transporting information
spatially, temporally, and semiotically; (c)
transforming health care outcomes, quality,
management, and knowledge use; and (d)
transporting information to transform health care.
344
Ramaprasad A., S. Papagari S. and Keeler J. (2009).
eHEALTH - Transporting Information to Transform Health Care.
In Proceedings of the International Conference on Health Informatics, pages 344-350
DOI: 10.5220/0001654103440350
Copyright
c
 SciTePress

2 ONTOLOGY
The ontology we use for the analysis of eHealth has
five dimensions, namely: (a) information, (b) spatial
transportation, (c) temporal transportation, (d)
semiotic transportation, and (e) health care. The
logic of the derivation of the dimensions from the
definition of ‘transporting information to transform
health care’ should be intuitively clear. We have
deconstructed transportation into three dimensions:
(a) spatial transportation, (b) temporal
transportation, and (c) semiotic transportation.
Information and health care have been retained as
such.
The five dimensions and their corresponding
taxonomies are shown in Figure 1 above and
discussed below. The alternative conjunctive words
to concatenate two adjacent columns are shown
between the columns. The right word makes the
concatenations across dimensions natural and
understandable. Five illustrative combinations are
shown at the bottom of the figure. The ontology as
presented can be expanded into 7*8*6*5*8 = 13,440
combinations. The above representation is a concise
way of representing them and analyzing them
systematically. A listing of all the combinations
would likely take more than 200 pages.
3 TRANSPORTING PERSONAL,
MEDICAL, AND BUSINESS
INFORMATION
In keeping with the actuality (Cicmil, Williams et al.
2006) of eHealth we have chosen a very simple and
practical two-level taxonomy of information. It has
three categories: (a) personal, (b) medical, and (c)
business information. Personal information is
categorized as health related and non-health related;
medical information as care related and research
related; and business information as financial,
administrative, and regulatory.
Personal information pertains to individuals
whose health care is the object of eHealth. It is
information possessed, owned, stored, and managed
by the individual. At a minimum it consists of
information to uniquely identify the individual; at
the maximum it is a complete personal health and
non-health record of the individual over his or her
lifetime.
The availability of timely, reliable, and valid
personal information can significantly affect health
care outcomes and quality. An eHealth system
should ideally help transport the right personal
information to the right place at the right time. An
eHealth system should ideally help transport the
right medical information to the right place at the
right time (Ambrose, Ramaprasad et al. 2003).
Medical care information, in contrast to personal
health information, can be defined as “the clinician’s
record of patient encounter-related information …
which is managed by the clinician and/or health care
institution.” (Tang, Ash et al. 2006, p. 122) Over
time there may be considerable overlap between the
two. Ideally with eHealth there should be “an
environment in which health information about an
individual can flow seamlessly among systems used
by authorized health professionals, caregivers, and
the patient, when the patient authorizes such
sharing.” (Tang, Ash et al. 2006, p.122)
Medical research information pertains to the
research relevant to the health of the person. The
rapid advances in medical research and the advent of
evidence-based medicine (Rosenberg and Donald
1995; Elstein 2004) make the transportation of
medical research critical for health care. “Evidence
based medicine is the process of systematically
finding, appraising, and using contemporaneous
research findings as the basis for clinical decisions.”
(Rosenberg and Donald 1995, p.1122) The
accessibility of medical research information to the
public through the internet (Weber 1999; Tufts
Managed Care Institute 2001; U.S. Department of
Commerce 2002) is also major motivator for
transporting such information. At the same time, in
the spirit of becoming informed patients (Detmer,
P.D.Singleton et al. 2003; Henwood, Wyatt et al.
2003), many people are informing themselves about
illnesses, their characteristics, causes, and cures
through publicly accessible information and
consequently changing the dynamics of the
interaction between the health care
receivers(patients, their family and friends, etc.) and
the health care providers (physicians, nurses, social
workers, etc.). The transportation of current research
information to health care providers in remote areas
without easy access to libraries is also playing an
important role in reducing the gap between the care
in rich and poor locations within a country and
among countries.
Business information includes financial,
regulatory, and administrative information related to
health care. These three categories of information
are particularly important for managing the revenues
and expenditures and the overall quality of care.
Examples of the three categories of information are:
(a) billing information, (b) Medicare/Medicaid
eHEALTH - Transporting Information to Transform Health Care
345

Information Spatial Temporal Semiotic Health Care
Personal Intra-enterprise Advance
[as]
Data Outcomes
Health Locally Real time Analysis Wellness
Non-health Regionally Encounter Interpretation Illness
Medical Nationally Post-encounter Conclusion Quality
Care Globally Personal lifetime Action Error-correction
Research Inter-enterprise Family lifetime Error-prevention
Business Locally Management
Financial Regionally Revenue
Administrative Nationally Expenditure
Regulatory Globally Knowledge
Application
Discovery
Illustrative combinations
Transporting personal health information intra-enterprise locally in real time as data to transform outcomes of wellness.
Transporting medical research information inter-enterprise nationally in advance as action to transform outcomes of illness.
Transporting business financial intra-enterprise regionally in real time as data to transform management of revenue.
Transporting personal health information inter-enterprise globally in personal lifetime as knowledge to transform quality
through error-prevention.
Transporting medical care information inter-enterprise nationally post-episode as data to transform knowledge application.
[to transform]
Transportation
[in/during/over]
[Transporting]
[information]
Figure 1: eHealth Ontology.
regulations, and (c) appointments scheduling
information, respectively. Multiple stakeholders are
responsible for the generation and dissipation of this
information. Thus transportation of the information
across the network of stakeholders is critical to the
success of health care.
4 TRANSPORTING
INFORMATION SPATIALLY,
TEMPORALLY, AND
SEMIOTICALLY
Transportation usually connotes spatial movement –
from one location to another. In addition, in eHealth
it is necessary to consider temporal and semiotic
transportation. In the following we discuss the three
transportation dimensions.
4.1 Spatial Transportation
Spatial transportation, as the name suggests, is the
movement of information over physical distances. It
is essential for eHealth because the individuals
receiving care, the providers, employers, insurers,
regulators, and suppliers are geographically
distributed. Today, with the internet there is a rising
expectation of services to be provided ‘anytime,
anywhere’. The spatial dimension addresses the
‘anywhere’ expectation of health care services.
Progression along the spatial dimension can be
viewed as local, regional, national, and global or
based on the enterprise as intra-enterprise and inter-
enterprise.
The broad presumption of movement along the
spatial dimension is to reduce the location
dependence of health care services(Ambrose,
Ramaprasad et al. 2003). Not only should the
consumer be able to avail of the services
‘anywhere’, but any health care facility in the
geographical domain should be able to deliver the
services ‘anywhere’. Moreover, broader geographic
domains can improve the effectiveness of sentinel
public health systems for recognizing epidemic
outbreaks or terror attacks. For example, RFID tags
are being used for injured soldiers during Iraq war as
a way of storing personal health information and
transporting the same to the military base hospital
(even before the soldiers are transported there)
(Chaiken 2004).
The key issues associated with spatial
transportation are of connectivity, interoperability,
security, and legality. They are a combination of
technological, organizational, and policy issues. The
emergence of HIEs (Health Information Exchange)
and RHIOs (Regional Health Information
Organization) is an example of the progression, at
least in concept, along the geographical domain. On
the other hand, countries such as the UK are
establishing a national domain.
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Another key component in the transformation of
health care is the shift in locus of care: where and
when the care is delivered. Homes, for example have
become significant locus of postoperative recovery
instead of extended hospital stays. They have also
become important locus of chronic disease
management and psychological counseling.
Shopping malls, on the other hand, are emerging has
locus of health checkups. The ability to transport
information over geographical domains – between
hospitals, clinics, laboratories, homes, pharmacies,
and employers – is a key catalyst of the changing
profile of the locus of health care. Thus consumers
may soon expect that the care be centered on them,
and that it be delivered wherever they are located,
whenever they desire, and by whomever they chose
based on performance – just as with travel services
and books stores.
4.2 Temporal Transportation
In spatial transportation time is a factor only in terms
of measuring the speed of the movement. In eHealth
it is not enough to consider time simply as the
denominator for measuring the rate of spatial
movement. It is necessary to consider temporal
transportation as a separate dimension to explicitly
incorporate the longitudinal characteristics of health
care and the associated transportation of information
over time. Personal history, family history, treatment
history, a disease epidemic, the presentation of a
disease, etc. are all longitudinal. They occur over
time and many subsequent events are likely to be
related to or dependent upon preceding events.
Without reliable, valid, and timely information about
the past the care of a person’s health can be
adversely affected.
Temporal transportation, as the label suggests, is
the movement of information over time. The
temporal dimension of the information may range
from advance information, real time information,
encounter information, post-encounter information,
personal lifetime information, to the family lifetime
information. In the near future it may stretch to
ancestral information. The problem of temporal
transportation is to continuously incorporate current
data in a life-cycle record, and to ensure that the
latter is always complete, accurate, and accessible.
The temporality of the information available at
the time of service can have a significant impact
upon its outcomes and quality. It is generally
assumed that ‘larger the temporal domain the better’,
both for prevention and treatment of serious
conditions. A paramedic at the scene of an accident
has information only about the current state; his
performance can be improved significantly if he or
she can access the patient’s history remotely from
the scene or by reading off a smart-card carried by
the victim.
4.3 Semiotic Transportation
Last, but not the least, the process of extracting
value from health care information (personal,
medical, and business) and using it to improve
health care is semiotic. It is the process of
discovering relationships, interpreting their meaning,
framing it in a particular context, and translating into
action. The transportation of information across the
semiotic layers (morphology, syntax, semantics, and
pragmatics) is semiotic transportation (Ramaprasad
and Rai 1996; Ramaprasad and Ambrose 1999;
Ambrose, Ramaprasad et al. 2003; Payne, Mendonca
et al. 2007).
Semiotic transportation is the movement of
information along the semiotic ladder to generate
knowledge and action based on the data. Such
transportation, for example, is embodied in the
processes of data mining, knowledge discovery,
clinical translation, and knowledge supply network
(Mak and Ramaprasad 2003). It is the method of
extracting knowledge- and action-value from data.
The progression along the semiotic domain can be
labeled as: (a) formalizing the data morphology, (b)
discovering the relationships within the data, (c)
interpreting the meaning of the relationships, (d)
framing the meaning in context to generate
knowledge, and (e) based on the knowledge
determining the appropriate action. Thus
information can be transported as data, analysis of
the data, the interpretation of the analysis,
conclusion based on the interpretation, or action
recommendations based on the conclusion. The
medium and the method of transporting at different
semiotic levels can vary considerably. A journal
article abstract may be sufficient to transport the
conclusions and action; a high speed network may
be needed to transport the raw data on medical
research or business finances.
The heavy emphasis on data-driven practices
such as evidence-based medicine, fact-based
management, and balanced score-cards to ensure the
quality of health care service have played a key role
in the emergence of the importance of semiotic
transportation. The availability of large volumes of
data and the ability to transport them over space and
time have also contributed to the increased value of
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347

semiotic transportation. Many business and business
units specialize in semiotic services.
Accompanying the shift in the locus of care
described under spatial transportation but different
from it is the shift in the locus of control. Control is
being shifted increasingly from the care-giver to the
care-receiver (Laine and Davidoff 1996; Bloche
2006). The physician, for example, has to help the
patient make an informed decision, and not make the
decision for the patient (Detmer, P.D.Singleton et al.
2003; Henwood, Wyatt et al. 2003; Elstein 2004).
While the responsibility for informing the patient in
the past rested primarily with the physician, patients
today are assuming the responsibility themselves,
and other stakeholders such as employers and payers
are actively increasing their role in doing so. Thus at
the core the locus of control is shifting from the
care-giver to the care-receiver, aided by the
concerted efforts of all the stakeholders to inform
the care-receiver and reinforce the shift in the locus
of control. They are being manifest in the Consumer
Driven Health Care (CDHC), Health Service
Accounts (HSAs), and patient empowerment. This
shift mirrors the shift in other service industries,
although not to the same extent – from ‘full-service’
to ‘self-service’ – you pump your own gas, conduct
your own banking transactions, and book you own
airline tickets. This shift has increased the
importance of semiotic transportation required to
inform the care-receivers about the problems, the
treatments, the risks, and the outcomes. The
emergence of web portals like WebMD to translate
medical research and terminology for the lay person
and to help them make decisions is an example of
the emerging role of semiotic transportation in
eHealth. Another example is the emergence of
personal health information management tools such
as Personal Health Records (PHRs) that enabled the
patients to access and track their health records and
be more informed about their diseases and
conditions (Pratt, Unruh et al. 2006).
5 TRANSFORMING HEALTH
CARE
Transforming the quality of care and the cost of care
have become the Yin and Yang of health care.
There is a symbiotic relationship between the two.
The success of both transformations is dependent
upon the efficient, effective, and error-free
transportation of information – albeit different
information spatially, temporally, and semiotically.
For quality, errors have to be eliminated,
detected, prevented, or corrected. To eliminate an
error is to design the system such that the error
cannot occur. To prevent an error it has to be
detected ahead of time; earlier the detection the
greater the chance of prevention. The occurrence of
an error is a failure of prevention. To correct an error
it is best to detect it soon after it occurs; later the
detection the lower the chance of correction. The
absence of an error, it must be noted, may reflect
effective prevention or ineffective detection.
To transform quality is to eliminate errors. Or, if
they cannot be eliminated they have to be prevented.
Further, if they cannot be prevented they have to be
detected and corrected with minimum delay. To
eliminate errors is also to learn from ones that have
been corrected and prevented in the past and to
eliminate them in the future. As with the other
aspects of the transformation of health care the
problem of transforming quality devolves to one of
systematically managing complex information in a
complex environment. One has to learn from the
past, discovering knowledge from ones experience
and others’, and apply it to the future.
To manage health care cost is to manage
information about the value of resources used to
provide the service. Today’s information systems
provide the ability to monitor and control costs at a
very micro level. The cost information also allows
one to analyze and reengineer health care processes
and therefore the cost structures. The transformation
in the cost of health care will be catalyzed by the
deep understanding of the micro cost structure and
the consequent reengineering of the macro policies,
procedures, and practices.
While the key components of the transformation
of health care costs are known, the paucity of data is
a significant barrier. Performance data on hospitals,
individual physicians and on other health care
providers are often unavailable in spite of the
evidence that such data could lead to quality
improvement (Marshall, Shekelle et al. 2000).
Hospital costs, for example, are easier to obtain than
ambulatory care costs. Employers, for example, have
difficulty obtaining data about their employees.
Consequently, acquisition of cost data at the greatest
level of detail and transporting them among the
entities and across the domains will be critical to
transforming the cost of health care.
Ultimately to transform health care outcomes an
organization has to be a learning organization –
discovering knowledge from its own experience and
others’ and applying it to transforming its practices.
This deliberate and conscious discovery and
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application of knowledge can only be possible if
there is an efficient and effective method for
transporting personal, medical, and business
information spatially, temporally, and semiotically.
That is the challenge of eHealth.
6 TRANSPORTING
INFORMATION TO
TRANSFORM HEALTH CARE
Consider the five illustrative combinations at the
bottom of Figure 1. They are natural language
descriptions of the functions of eHealth. Although a
little awkward grammatically, they make sense and
can be related to specific requirements of ehealth.
The first sentence relates to the need to obtain a
person’s health information in real time for
ambulatory preventive care; the second to the need
to disseminate medical research information on a
disease nationally to all stakeholders to manage the
outcomes of a potential epidemic; the third to
revenue management in real time through
collaboration between multiple branches of a health
care organization in a region; the fourth to a person
being able to obtain appropriate care globally
without fear of errors due to ignorance of a person’s
medical history; and the fifth to monitor the effects
of a new drug after it has been introduced in the
market. The operational needs of eHealth mentioned
above are not the only ones to which the five
sentences apply. A sentence can connote many
needs. There are 13,435 similar sentences which can
be constructed from the ontology. Each of these
sentences can connote a number of operational
needs. No one system is likely to fulfill all the
requirements connoted by all the sentences. On the
other hand, a selection of sentences can be a high
level description of the requirements of an eHealth
system.
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