Patient Engagement and Consumerism - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 152

implementation when faced with “real world” scenarios. By addressing such
challenges at the outset, the likelihood of success for such policy related activi-
ties can be greatly enhanced.

Providers and Healthcare Organizations

￿ Providers are often forced to make clinical decision based on incomplete evi-
dence and data, for example, not being able to adjust treatment plans based upon
a rigorous understanding of dietary or activity patterns that occur outside of the
care delivery environment. By incorporating patients and communities into
the data generation pipeline that supports / enables clinical decision making ,
more comprehensive and effi cacious clinical decision - making is made
possible .
￿ Much as is the case at an individual level, healthcare delivery organizations are
also increasingly concerned with managing populations to lower risk and
improve outcomes, especially when they are fi nancially “at risk” for the wellness
of those individuals. By creating a “ data fabric ” incorporating patients and
their communities , the ability to comprehensive and predictively model
such trends in an impactful manner becomes feasible , thus resulting in both
fi nancial and quality of care benefi ts to organizations and the patients they
serve .

Patients and Their Communities

￿ By providing patients with a “voice” in the knowledge-driven healthcare
environment, it is possible to catalyze a cultural change via which those indi-
vidual become active participants in healthcare delivery , rather than pas-
sive consumers . Ample evidence exists showing that such activist patients are
more likely to experience positive healthcare outcomes and greater overall
wellness.

￿ Finally, by making communities part of the same healthcare data “ dialogue ”,

trends that may impact entire populations ( either positively or negatively )
can be surfaced and acted upon , often through community-level advocacy
efforts and at much lower costs with improved benefi ts when compared to acute
or episodic care models.

9.4 Conclusion

We have described patient engagement around the process of a clinical trial, from
recruitment, consent, data collection, and providing results. At each point, patient
engagement can improve the specifi c research tasks, and improve translational
research. We have also identifi ed important innovations in each area that affect or
are affected by patient engagement. As the nation moves to a vision of a learning
health system, the importance of patient engagement, both as a facilitator of research