Alignment of American Association of Colleges of Nursing Graduate-Level Nursing Informatics Competencies With American Medical Informatics Association Health Informatics Core Competencies.

This study yielded a map of the alignment of American Association of Colleges of Nursing Graduate-Level Nursing Informatics Competencies with American Medical Informatics Association Health Informatics Core Competencies in an effort to understand graduate-level accreditation and certification opportunities in nursing informatics. Nursing Informatics Program Directors from the American Medical Informatics Association and a health informatics expert independently mapped the American Association of Colleges of Nursing competencies to the American Medical Informatics Association Health Informatics knowledge, skills, and attitudes. The Nursing Informatics Program Directors' map connected an average of 4.0 American Medical Informatics Association Core Competencies per American Association of Colleges of Nursing competency, whereas the health informatics expert's map connected an average of 5.0 American Medical Informatics Association Core Competencies per American Association of Colleges of Nursing competency. Agreement across the two maps ranged from 14% to 60% per American Association of Colleges of Nursing competency, revealing alignment between the two groups' competencies according to knowledge, skills, and attitudes. These findings suggest that graduates of master's degree programs in nursing, especially those specializing in nursing informatics, will likely be prepared to sit for the proposed Advanced Health Informatics Certification in addition to the American Nurses Credentialing Center bachelor's-level Informatics Nursing Certification. This preliminary map sets the stage for further in-depth mapping of nursing informatics curricula with American Medical Informatics Association Core Competencies and will enable interprofessional conversations around nursing informatics specialty program accreditation, nursing workforce preparation, and nursing informatics advanced certification. Nursing informaticists should examine their need for credentials as key contributors who will address critical health informatics needs.

AMIA Board White Paper: AMIA 2017 core competencies for applied health informatics education at the master's degree level.

This White Paper presents the foundational domains with examples of key aspects of competencies (knowledge, skills, and attitudes) that are intended for curriculum development and accreditation quality assessment for graduate (master's level) education in applied health informatics. Through a deliberative process, the AMIA Accreditation Committee refined the work of a task force of the Health Informatics Accreditation Council, establishing 10 foundational domains with accompanying example statements of knowledge, skills, and attitudes that are components of competencies by which graduates from applied health informatics programs can be assessed for competence at the time of graduation. The AMIA Accreditation Committee developed the domains for application across all the subdisciplines represented by AMIA, ranging from translational bioinformatics to clinical and public health informatics, spanning the spectrum from molecular to population levels of health and biomedicine. This document will be periodically updated, as part of the responsibility of the AMIA Accreditation Committee, through continued study, education, and surveys of market trends.

Telehealth Intensive Care Unit Nurse Surveillance of Sepsis.

The purpose of this article is to describe the usability and human factors engineering standards used in development of a sepsis alert known as the sepsis prompt. Sensory processing, cognitive processing, signal detection, criterion response, and user satisfaction were evaluated with controlled user testing and critical incident response techniques. Nurses reported that the sepsis prompt was visible and distinct, making it easily detectable. The prompt provided a clear response mechanism and adequately balanced the number of false alerts with the likelihood of misses. Designers were able to use a mental model approach as they designed the prompt because the nurses were already using a manual sepsis detection process. This may have predisposed the nurses to response bias, and as such, they were willing to accommodate more false alarms than nurses who are not familiar with sepsis screening (surveillance). Nurses not currently screening for sepsis may not place the same value on this alert and find it an annoyance. The sepsis prompt met usability standards, and the nurses reported that it improved efficiency over the manual screening method.

Ambient Findability: Developing a Flowsheet Ontology for i2B2.

The process of moving from the locally defined flowsheet ontology containing redundancy and jargon to one understandable by researchers is described. Over 250 million nursing flowsheet observations were imported into a data repository that uses the i2b2 framework. Focus groups were used to derive a new ontology model--18 templates were identified. One hundred measures, 50% of all patient observations over 36 months, were encoded in SNOMED CT(©). 78% of the concepts were mapped.

Expressing observations from electronic medical record flowsheets in an i2b2 based clinical data repository to support research and quality improvement.

While nursing documentation in electronic medical record (EMR) flowsheets may represent the largest investment of clinician time with information systems, organizations lack tools to visualize and repurpose this data for research and quality improvement. Incorporating flowsheet documentation into a clinical data repository and methods to reduce the flowsheet ontology's redundancy are described. 411 million flowsheet observations, derived from an EMR predominantly used in inpatient, outpatient oncology, and emergency room settings, were incorporated into a repository using the i2b2 framework. The local flowsheet ontology contained 720 "templates" employing 5,379 groups (2,678 distinct), 37,836 measures (13,659 distinct) containing 226,666 choices for a total size of 270,641. Aggressive pruning and clustering resulted in 150 templates, 743 groups (615 distinct), 6,950 measures (4,066 distinct) with 22,497 choices, and size of 30,371. Making nursing data accessible within i2b2 provides a new perspective for contributing clinical organizations and heightens collaboration between the academic and clinical activities.