Representing Organizational Conservation of Information - Enterprise Information Systems Design, Implementation and Management: Organizational Applications - page 139

(Bohr, 1955); between USAF combat fighter
jet pilots and topic-knowledge of air combat
maneuvering (Lawless et al., 2000); between
game-theory preferences and actual choices
made during games (Kelley, 1992); and to
capture the discrepancy between the views
of managers and the decisions made by their
organizations (Bloom et al., 2007).
2. Allow rotation vectors as a function of the
direction of rotation. Permit measurements
between vectors and rotations.
3. Enable a mathematics of interdependent ( ι )
bistability where measurements disturb or
collapse the ι states that occur during social-
psychological interactions in physical space.
4. Test the proposition that information in
organizational interactions can be modeled
by the conservation of information.

Medical care depends on physicians to collect
and process patient information. But increas-
ing knowledge requirements for patients and
doctors, the need to evaluate populations of
patients whether treated or not, unmet health-
care expectations, the costliness of fragmented
care, and the rising demand for chronic disease
care challenge traditional healthcare models that
refinements alone may not solve. Healthcare IT
is the best option for future medical progress. IT
includes computer-aided diagnosis and treatment
monitoring; telemedicine; and IT to inform the
public and physicians on health and healthcare.
But incorrect beliefs about IT pose a deterrent to
telemedicine. Even senior healthcare executives
hold beliefs inimical to the increased adoption of
IT in healthcare.
In our earlier paper (Stachura et al., 2009), we
also reviewed applications of Telemedicine and
eHealth in Georgia from an organizational perspec-
tive. To evaluate the role of COI in organizational
effectiveness, we reviewed organizational and
system theory along with past applications and
field and laboratory results, three case studies
using Telemedicine and eHealth, a model using
natural selection (machine learning), and a Monte
Carlo simulation of return on investments (ROI).
Theory provided us with the tools to analyze
tradeoffs based on COI in eHealth management
decision-making. In the three case studies, we
provided an overview of a Telemedicine and
eHealth network from the State of Georgia in the
United States that was operating in the Southeast
Public Health District (SEPHD), East Georgia
Health Cooperative (EGHC), and Island Health
Care (IHC)/The Healthcare Alternatives (THA)
Group. Next, we analyzed the case studies with
COI and the weaknesses and strengths of our
theory and approach. Finally, we close with a
review of Future Trends.
Overall, indicators pointed to good progress,
but a lack of uniformity in the organizational met-
rics exist to clearly indicate where effectiveness

teLeMedicine And eheALth.
bAckground And rAtionALe

background of prior Work

From our review (see Stachura et al., 2009), digital
technologies are transforming many areas of hu-
man endeavor from commerce and entertainment
to government and communications. Policymakers
are emphasizing Information Technology (IT) for
healthcare to improve service delivery, promote
efficiency, educate consumers, and increase satis-
faction. But other than gathering information from
websites, few people are using IT to communicate
online with health care personnel or to purchase
medical services. This digital divide has impeded
e-health's acceptance. Less well educated, lower
income individuals in rural areas use the web less
often for health care than better educated, higher
income urbanites. To gain the benefits of IT for
healthcare, it needs to become more widespread
and its benefits more evident to consumers of all
types across the country.