A Prototype of Translational Informatics in Action - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 26

New
Evidence

Inform

Inform

Public Information
Resources

Researchers

Delivers
Care To

Clinical
Science
Basic
Science

Train

Support

Records

Patient

clinician(s)

Educators

Family/Community

EHR

Influence
or Constrain

Characterize

Guidelines

Policies

Policy-Makers

Emergent Data Sources
(e.g., sensors)

Fig. 2.2 Traditional model of healthcare delivery, in which various activities occur within comple-
mentary but isolated silos relating to research, education, policy-making, and the variety of con-
structs and data sources that surround and characterize a given patient

￿ Simultaneous to the preceding unidirectional care delivery and knowledge prop-

agation paradigm, patients are also supported and characterized by a num-
ber of constructs and data sources , including:

1. Their family members and surrounding community entities that often provide
the bulk of both wellness promotion and healthcare delivery for individuals
while they are outside of the clinical environment;
2. Any number of sensors or other ubiquitous computing technologies (e.g.,
smartphones, etc.) that capture data that may be pertinent to measuring the
health status of individuals; and
3. Public data sources that both inform the socio-demographic aspects of an
individual's health, as well as provide access to health and wellness informa-
tion that may be acted upon by those individuals in a manner disparate and
independent from the care delivered by their clinical providers. Examples
include large public databases such as those associated with census or other
survey data, and/or data derived from prior research programs and made
available for reuse.

Unfortunately, models and mechanisms for bringing all of these items to the fore-
front of clinical decision-making are rare and in many cases, not well understood or
trusted by care providers.
In contrast to the issues and concerns noted above, the prototypical case described
in Sect. 2.2 provides a glimpse of what has been commonly referred to as a “Learning