Statistical Analysis and Data Mining, An American Statistical Association Journal

Call for Papers
Special Issue on Observational Healthcare Data

Guest Editors: Patrick Ryan, J&J and Marc Suchard, UCLA

Due date: July 1, 2013

Data sciences is the rapidly evolving field that integrates
mathematical and statistical knowledge, software engineering and
large-scale data management skills, and domain expertise to tackle
difficult problems that typically cannot be solved by any one
discipline alone. Some of the most difficult, and arguably most
important, problems exist in healthcare. Knowledge about human
biology has exponentially advanced in the past two decades with
exciting progress in genetics, biophysics, and pharmacology. However,
substantial opportunities exist to extend the evidence base about
human disease, patient health and effects of medical interventions and
translate knowledge into actions that can directly impact clinical
care. The emerging availability of 'big data' in healthcare, ranging
from prospective research with aggregated genomics and clinical trials
to observational data from administrative claims and electronic health
records through social media, offer unprecedented opportunities for
data scientists to contribute to advancing healthcare through the
development, evaluation, and application of novel analytical solutions
to explore these data to generate evidence at both the patient and
population level. Statistical and computational challenges abound and
methodological progress will draw on fields such as data mining,
epidemiology, medical informatics, and biostatistics to name but a
few. This special issue of Statistical Analysis and Data Mining seeks
to capture the current state of the art in healthcare data sciences.
We welcome contributions that focus on methodology for healthcare data
and original research that demonstrates the application of data
sciences to problems in public health.