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Medication reconciliation (MedRec) can improve patient safety by resolving medication discrepancies. Because information technology (IT) and patient engagement are promising approaches to optimizing MedRec, the SEAMPAT project aims to develop a MedRec IT platform based on two applications: the "patient app" and the "MedRec app." This study evaluates three dimensions of the usability (efficiency, satisfaction, and effectiveness) and usefulness of the patient app.

To facilitate high-quality inpatient care for stroke patients, we built a system within our electronic health record (EHR) to identify stroke patients while they are in the hospital; capture necessary data in the EHR to minimize the burden of manual abstraction for stroke performance measures, decreasing daily time requirement from 2 hours to 15 minutes; generate reports using an automated process; and electronically transmit data to third parties. Provider champions [...]

Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 [...]

To assess information sources that may elucidate errors related to radiologic diagnostic imaging, quantify the incidence of potential safety events from each source, and quantify the number of steps involved from diagnostic imaging chain and socio-technical factors.

Public health surveillance programs worldwide implement a variety of case-finding strategies, and many rely at least in part on International Classification of Diseases (ICD)-based diagnostic codes in administrative and clinical databases. Over time, state- and national-level hospital discharge databases have been expanding the number of reported diagnosis code fields. This study aimed to evaluate the impact of these expansions on frequencies and rates of major birth defects, and the classification [...]

To illustrate the need for wider implementation of the CancelRx message by quantifying and characterizing the inappropriate usage of new electronic prescription (NewRx) messages for communicating discontinuation instructions to pharmacies.

Development and maintenance of order sets is a knowledge-intensive task for off-the-shelf machine-learning algorithms alone. We hypothesize that integrating clinical knowledge with machine learning can facilitate effective development and maintenance of order sets while promoting best practices in ordering. To this end, we simulated the revision of an "AM Lab Order Set" under 6 revision approaches. Revisions included changes in the order set content or default settings through 1) population [...]

This study evaluated and compared a variety of active learning strategies, including a novel strategy we proposed, as applied to the task of filtering incorrect semantic predications in SemMedDB.

Appropriate management of attention-deficit/hyperactivity disorder (ADHD) involves parents, clinicians, and teachers. Fragmentation of interventions between different settings can lead to suboptimal care and outcomes. Electronic systems can bridge gaps across settings. Our institution developed an email-based software to collect ADHD information from parents and teachers, which delivered data directly to the clinician within the electronic health record (EHR).