INTRODUCTION
An emerging vision for the future is that of
the LHS, which represents a paradigm shift
in the healthcare ecosystem within which
organizations operate. Within this vision,
the LHS will feel less like a collection of
interoperable systems and more like one
large virtual system providing appropriate
access to data where and when it is needed
– both for clinical as well as analytic purposes. Key outcomes of this LHS involve
changes not only to what data will be used,
but to how data will be used. Examples
include:
■ n Payment models are evolving rapidly
and will converge on a small number of
variations. Data will be key to evaluating
the success and effectiveness of these new
models. This evaluation will need to take
place at many levels within the LHS: the
individual site/facility, the organization, at
the Accountable Care Organization (ACO)/
system level, and even the community level.
■ n Integration of data will offer the most
value, both within healthcare and beyond.
This includes core clinical data, administrative data including claims, and clinical
quality data. Over time, more data from
other domains will become integrated with
core healthcare data. “Big data” will enable
not only a more accurate longitudinal view
of individual patients but also more robust
population health analyses as well.
■ n The flow of data – current and retrospective – will become more pervasive in
society as the demand for data will be constant and continuous. Over time, the LHS
will feel less like a collection of interoperable systems and more like one large
virtual system providing appropriate access to
data where and when it is needed.
■ n While data systems continue to differentiate themselves in the marketplace,
there is more consistent deployment of
standard interfaces for getting data in and
out of systems, including both the structure
and content of messages. This makes the
use of standards ever more important for
a successful LHS.
Many EHR vendors are putting up bar-
riers to access data that comes into the
EHR even if the data originates within an
organization which may lead to increased
monetization of healthcare data. While the
use by vendors of standards-based versus
proprietary approaches to data access can
help mitigate some of this “information
blocking,” the strict use of standards by
vendors does not guarantee that data will
be accessible and available to the organiza-
tions that have already paid to capture and
store it. While software vendors should be
appropriately compensated for the prod-
ucts and services they provide, they should
not control access to a provider’s data and
should not impose additional services or
fees on their customers to achieve this
access. This article will explore perspec-
tives around this issue.
EVOLUTION OF CLINICAL SYSTEMS
Clinical systems – especially those in hos-
pitals – have evolved over time. Academic
medical centers were at the forefront of
early system development as they had
the need and the emerging informatics
expertise to develop systems in-house,
Early approaches to hospital systems
were mostly “best of breed:” various units
within hospitals typically sought out the
best application for their particular special-
ties. The primary limitation was the repli-
cation of patient data across systems, and
the inability of many systems (at least in the
early days) to reliably exchange data with
each other. The alternative approach was a
single system which enabled a more inte-
grated view of patient data, but this often
required compromise on the functionality
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