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Standards requiring education in informatics in pharmacy curricula were introduced in the last 10 years by the Accreditation Council for Pharmacy Education. Mirroring difficulties faced by other health professions educators, implementation of these requirements remains fragmented and somewhat limited across colleges of pharmacy in the US. Clinical practice and workforce metrics underline a pronounced need for clinicians with varying competencies in health informatics. In response to these challenges, a multitiered [...]

AMIA is leading the effort to strengthen the health informatics profession by creating an advanced health informatics certification (AHIC) for individuals whose informatics work directly impacts the practice of health care, public health, or personal health. The AMIA Board of Directors has endorsed a set of proposed AHIC eligibility requirements that will be presented to the future AHIC certifying entity for adoption. These requirements specifically establish who will be eligible [...]

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 [...]

Informatics programs need assurance that their curricula prepare students for intended roles as well as ensuring that students have mastered the appropriate competencies. The objective of this study is to describe a method for using assessment data to identify areas for curriculum, student selection, and assessment improvement.

Identifying disease-mutation relationships is a significant challenge in the advancement of precision medicine. The aim of this work is to design a tool that automates the extraction of disease-related mutations from biomedical text to advance database curation for the support of precision medicine.

(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.

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.

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.