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Clinical vocabularies allow for standard representation of clinical concepts, and can also contain knowledge structures, such as hierarchy, that facilitate the creation of maintainable and accurate clinical decision support (CDS). A key architectural feature of clinical hierarchies is how they handle parent-child relationships - specifically whether hierarchies are strict hierarchies (allowing a single parent per concept) or polyhierarchies (allowing multiple parents per concept). These structures handle subsumption relationships (ie, ancestor [...]

Online platforms have created a variety of opportunities for breast patients to discuss their hormonal therapy, a long-term adjuvant treatment to reduce the chance of breast cancer occurrence and mortality. The goal of this investigation is to ascertain the extent to which the messages breast cancer patients communicated through an online portal can indicate their potential for discontinuing hormonal therapy.

Investigating the molecular mechanisms of symptoms is a vital task in precision medicine to refine disease taxonomy and improve the personalized management of chronic diseases. Although there are abundant experimental studies and computational efforts to obtain the candidate genes of diseases, the identification of symptom genes is rarely addressed. We curated a high-quality benchmark dataset of symptom-gene associations and proposed a heterogeneous network embedding for identifying symptom genes.

Electronic health record (EHR) simulation with realistic test patients has improved recognition of safety concerns in test environments. We assessed if simulation affects EHR use patterns in real clinical settings.

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 [...]

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 [...]

Unintentional medication discrepancies contribute to preventable adverse drug events in patients. Patient engagement in medication safety beyond verbal participation in medication reconciliation is limited. We conducted a pilot study to determine whether patients' use of an electronic home medication review tool could improve medication safety during hospitalization.

Data derived from primary care electronic medical records (EMRs) are being used for research and surveillance. Case definitions are required to identify patients with specific conditions in EMR data with a degree of accuracy. The purpose of this study is to identify and provide a summary of case definitions that have been validated in primary care EMR data.

Clinical decision support (CDS) hard-stop alerts-those in which the user is either prevented from taking an action altogether or allowed to proceed only with the external override of a third party-are increasingly common but can be problematic. To understand their appropriate application, we asked 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and [...]