TITLE:
Translation in Data Mining to Advance Personalized Medicine for Health Equity
AUTHORS:
Estela A. Estape, Mary Helen Mays, Elizabeth A. Sternke
KEYWORDS:
Data Mining, Electronic Medical Records, Translation, Personalized Medicine, Biomedical Informatics, Heath Equity, Healthcare Workforce
JOURNAL NAME:
Intelligent Information Management,
Vol.8 No.1,
January
13,
2016
ABSTRACT: Personalized medicine is the development of
“tailored” therapies that reflect traditional medical approaches with the
incorporation of the patient’s unique genetic profile and the environmental
basis of the disease. These individualized strategies encompass disease
prevention and diagnosis, as well as treatment strategies. Today’s healthcare
workforce is faced with the availability of massive amounts of patient- and disease-related
data. When mined effectively, these data will help produce more efficient and
effective diagnoses and treatment, leading to better prognoses for patients at
both the individualand population level. Designing preventive and
therapeutic interventions for those patients who will benefit most while
minimizing side effects and controlling healthcare costs requires bringing
diverse data sources together in an analytic paradigm. A resource to
clinicians in the development and application of personalized medicine is
largely facilitated, perhaps even driven, by the analysis of “big data”. For
example, the availability of clinical data warehouses is a significant resource
for clinicians in practicing personalized medicine. These “big data” repositories
can be queried by clinicians, using specific questions, with data used to gain
an understanding of challenges in patient care and treatment. Health
informaticians are critical partners to data analytics including the use of
technological infrastructures and predictive data mining strategies to access
data from multiple sources, assisting clinicians’ interpretation of data and
development of personalized, targeted therapy recommendations. In this paper,
we look at the concept of personalized medicine, offering perspectives in four
important, influencing topics: 1) the availability of “big data” and the role
of biomedical informatics in personalized medicine, 2) the need for
interdisciplinary teams in the development and evaluation of personalized therapeutic
approaches, and 3) the impact of electronic medical record systems and clinical
data warehouses on the field of personalized medicine. In closing, we present
our fourth perspective, an overview to some of the ethical concerns related to
personalized medicine and health equity.