Search AMIA.org

(1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-world patient recruitment data for a diverse set of clinical trials in a pediatric emergency department; and (3) to identify directions for future studies in predicting patients' participation response.

The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM's vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science [...]

Cancer has been extensively characterized on the basis of genomics. The integration of genetic information about cancers with data on how the cancers respond to target based therapy to help to optimum cancer treatment.

The Information Systems Department at Memorial Sloan Kettering Cancer Center developed the DARWIN Cohort Management System (DCMS). The DCMS identifies and tracks cohorts of patients based on genotypic and clinical data. It assists researchers and treating physicians in enrolling patients to genotype-matched IRB-approved clinical trials. The DCMS sends automated, actionable, and secure email notifications to users with information about eligible or enrolled patients before their upcoming appointments. The system also [...]

In 2005, AMIA leaders and members concluded that certification of advanced health informatics professionals would offer value to individual practitioners, organizations that hire them, and society at large. AMIA's work to create advanced informatics certification began by leading a successful effort to create the clinical informatics subspecialty for American Board of Medical Specialties board-certified physicians. Since 2012, AMIA has been working to establish advanced health informatics certification (AHIC) for all [...]

This article offers suggested guidelines for graduate students who are embarking on informatics doctoral studies and anticipating the dissertation research and its documentation. Much of the guidance is pertinent for writing dissertations in other disciplines as well. The messages are largely directed at doctoral students, but some elements are also pertinent for master's students. All are relevant for faculty research advisors. The value of the dissertation is often underestimated. Too [...]

Since the launch of the clinical informatics subspecialty for physicians in 2013, over 1100 physicians have used the practice and education pathways to become board-certified in clinical informatics. Starting in 2018, only physicians who have completed a 2-year clinical informatics fellowship program accredited by the Accreditation Council on Graduate Medical Education will be eligible to take the board exam. The purpose of this viewpoint piece is to describe the collective [...]

Electronic medical records (EMRs) hold a tremendous amount of information about patients that is relevant to determining the optimal approach to patient care. As medicine becomes increasingly precise, a patient's electronic medical record phenotype will play an important role in triggering clinical decision support systems that can deliver personalized recommendations in real time. Learning with anchors presents a method of efficiently learning statistically driven phenotypes with minimal manual intervention.

Precision medicine approaches disease treatment and prevention by taking patients' individual variability in genes, environment, and lifestyle into account. Although the ideas underlying precision medicine are not new, opportunities for its more widespread use in practice have been enhanced by the development of large-scale databases, new methods for categorizing and representing patients, and computational tools for analyzing large datasets. New research methods may create uncertainty for both healthcare professionals and [...]

Currently, there is a disconnect between finding a patient's relevant molecular profile and predicting actionable therapeutics. Here we develop and implement the Integrating Molecular Profiles with Actionable Therapeutics (IMPACT) analysis pipeline, linking variants detected from whole-exome sequencing (WES) to actionable therapeutics.