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generate evidence and improve the quality of healthcare. Unfortunately the current
healthcare system is designed to enable the care of a single patient of the time and
not to focus on research or systematic learning. Without a fundamental paradigm
shift the challenges preventing advances in translational informatics will continue
unabated, and the necessary technical, organizational and cultural changes men-
tioned above will remain elusive, at best. Let us explore the basis for this shift.
10.3.2
Traditional Model
10.3.2.1
Unidirectional Translation of Knowledge
from Research into Practice (EBM)
The traditional research-practice paradigm upon which our healthcare system is
built defi nes research and practice as entirely distinct endeavors that share a unidi-
rectional relationship, with research fi ndings being applied to practice, ideally via an
Evidence Based Medicine (EBM) approach. While this prevailing paradigm is well
suited to individual healthcare delivery, it is at odds with and often frustrates the very
research and healthcare improvement initiatives in which we are investing. Guided
by this current research-practice paradigm, mal-aligned organizational, fi nancial,
and policy decisions impede the integration of research and practice, frustrating
ongoing efforts [
22
]. The prevailing paradigm even feeds into problematic percep-
tions at the individual level, such as the view by clinicians and patients alike that
engaging in research activities is not part of what should happen at the bedside.
10.3.2.2
Limited Feedback Between Activities
A major and signifi cant consequence of the prevailing paradigm as it relates to tran-
sitional informatics is the limited amount of information fl owing feedback between
clinical and research activities. Indeed, the challenges facing biomedical informat-
ics professionals working at translational junctures are evident on a daily basis, and
they expose the fl aws in the current paradigm. Unfortunately, the notion that simply
digitizing medical information will automatically enable downstream research and
evidence generation fl awed [
23
]. Well data collected at the point of Karen Tesdal
form is certainly more helpful than that collected otherwise such that are often
incomplete or inaccurate for the needs of researchers. Moreover current regulatory
and policy frameworks limit the feedback loops between the clinical and research
environments due to concerns such as those related to privacy and the reuse of data.
Groups are beginning to report on such concerns and suggest options for reconciling
the importance of privacy and advancing research simultaneously [
11
,
24
].
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