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Our primary objective is to provide the clinical informatics community with an introductory tutorial on calibration measurements and calibration models for predictive models using existing R packages and custom implemented code in R on real and simulated data. Clinical predictive model performance is commonly published based on discrimination measures, but use of models for individualized predictions requires adequate model calibration. This tutorial is intended for clinical researchers who want to [...]

The growth of digitized health data presents exciting opportunities to leverage the health information technology (IT) infrastructure for advancing biomedical and health services research. However, challenges impede use of those resources effectively and at scale to improve outcomes. The Office of the National Coordinator for Health Information Technology (ONC) led a collaborative effort to identify challenges, priorities, and actions to leverage health IT and electronic health data for research. Specifically [...]

To build a knowledge base of dietary supplement (DS) information, called the integrated DIetary Supplement Knowledge base (iDISK), which integrates and standardizes DS-related information from 4 existing resources.

The disjointed healthcare system and the nonexistence of a universal patient identifier across systems necessitates accurate record linkage (RL). We aim to describe the implementation and evaluation of a hybrid record linkage method in a statewide surveillance system for congenital heart disease.

Classifying whether concepts in an unstructured clinical text are negated is an important unsolved task. New domain adaptation and transfer learning methods can potentially address this issue.

The study sought to describe key features of clinical concepts and data required to implement clinical practice recommendations as clinical decision support (CDS) tools in electronic health record systems and to identify recommendation features that predict feasibility of implementation.

The study sought to determine the dependence of the Electronic Medical Records and Genomics (eMERGE) rheumatoid arthritis (RA) algorithm on both RA and electronic health record (EHR) duration.

Implementation of machine learning (ML) may be limited by patients' right to "meaningful information about the logic involved" when ML influences healthcare decisions. Given the complexity of healthcare decisions, it is likely that ML outputs will need to be understood and trusted by physicians, and then explained to patients. We therefore investigated the association between physician understanding of ML outputs, their ability to explain these to patients, and their willingness [...]

The biomedical research and healthcare delivery communities have increasingly come to focus their attention on the role of data and computation in order to improve the quality, safety, costs, and outcomes of both wellness promotion and care delivery. Depending on the scale of such efforts, and the environments in which they are situated, they are referred to variably as personalized or precision medicine, population health, clinical transformation, value-driven care, or [...]

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT [...]