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A terminology for nursing assessments does not exist to support exchange of information and research. A team of nurse informaticts collaborated to create a standard for medical/ surgical assessment terms coded in LOINC and SNOMED CT. Nursing assessments represented 106 observation (50% new LOINC), and 348 Values (20% New SNOMED CT) organized into fifteen panels (86% new LOINC). [ABSTRACT FROM AUTHOR]

Background: Secondary use of electronic health record (EHR) data can reduce costs of research and quality reporting. However, EHR data must be consistent within and across organizations. Flowsheet data provide a rich source of interprofessional data and represents a high volume of documentation; however, content is not standardized. Health care organizations design and implement customized content for different care areas creating duplicative data that is noncomparable. In a prior study, 10 information models (IMs) were derived from an EHR that included 2.4 million patients. There was a need to evaluate the generalizability of the models across organizations. The pain IM was selected for evaluation and refinement because pain is a commonly occurring problem associated with high costs for pain management., Objective: The purpose of our study was to validate and further refine a pain IM from EHR flowsheet data that standardizes pain concepts, definitions, and associated value sets for assessments, goals, interventions, and outcomes., Methods: A retrospective observational study was conducted using an iterative consensus-based approach to map, analyze, and evaluate data from 10 organizations., Results: The aggregated metadata from the EHRs of 8 large health care organizations and the design build in 2 additional organizations represented flowsheet data from 6.6 million patients, 27 million encounters, and 683 million observations. The final pain IM has 30 concepts, 4 panels (classes), and 396 value set items. Results are built on Logical Observation Identifiers Names and Codes (LOINC) pain assessment terms and extend the need for additional terms to support interoperability., Conclusion: The resulting pain IM is a consensus model based on actual EHR documentation in the participating health systems. The IM captures the most important concepts related to pain., Competing Interests: None., (Schattauer GmbH Stuttgart.)

The phenomenon of "data rich, information poor" in today's electronic health records (EHRs) is too often the reality for nursing. This article proposes the redesign of nursing documentation to leverage EHR data and clinical intelligence tools to support evidence-based, personalized nursing care across the continuum. The principles consider the need to optimize nurses' documentation efficiency while contributing to knowledge generation. The nursing process must be supported by EHRs through integration of best care practices: seamless workflows that display the right tools, evidence-based content, and information at the right time for optimal clinical decision making. Design of EHR documentation must attain a balance that ensures the capture of nursing's impact on safety, quality, highly reliable care, patient engagement, and satisfaction, yet minimizes "death by data entry." In 2014, a group of diverse informatics leaders from practice, academia, and the vendor community formed to address how best to transform electronic documentation to provide knowledge at the point of care and to deliver value to front line nurses and nurse leaders. As our health care system moves toward reimbursement on the basis of quality outcomes and prevention, the value of nursing data in this business proposition will become a key differentiator for health care organizations' economic success.