Standardizing Physiologic Assessment Data to Enable Big Data Analytics.

Disparate data must be represented in a common format to enable comparison across multiple institutions and facilitate Big Data science. Nursing assessments represent a rich source of information. However, a lack of agreement regarding essential concepts and standardized terminology prevent their use for Big Data science in the current state. The purpose of this study was to align a minimum set of physiological nursing assessment data elements with national standardized coding systems. Six institutions shared their 100 most common electronic health record nursing assessment data elements. From these, a set of distinct elements was mapped to nationally recognized Logical Observations Identifiers Names and Codes (LOINC®) and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT®) standards. We identified 137 observation names (55% new to LOINC), and 348 observation values (20% new to SNOMED CT) organized into 16 panels (72% new LOINC). This reference set can support the exchange of nursing information, facilitate multi-site research, and provide a framework for nursing data analysis.

Communicating Nursing Care Using the Health Level Seven Consolidated Clinical Document Architecture Release 2 Care Plan.

A care plan provides a patient, family, or community picture and outlines the care to be provided. The Health Level Seven Consolidated Clinical Document Architecture (C-CDA) Release 2 Care Plan Document is used to structure care plan data when sharing the care plan between systems and/or settings. The American Nurses Association has recommended the use of two terminologies, Logical Observation Identifiers Names and Codes (LOINC) for assessments and outcomes and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) for problems, procedures (interventions), outcomes, and observation findings within the C-CDA. This article describes C-CDA, introduces LOINC and SNOMED CT, discusses how the C-CDA Care Plan aligns with the nursing process, and illustrates how nursing care data can be structured and encoded within a C-CDA Care Plan.

Standardized mapping of nursing assessments across 59 U.S. military treatment facilities.

OBJECTIVE: Create an interoperable set of nursing flowsheet assessment measures within military treatment facility electronic health records using the 3M Healthcare Data Dictionary (HDD). DESIGN: The project comprised three phases: 1) discovery included an in-depth analysis of the Essentris data to be mapped in the HDD; 2) mapping encompassed the creation of standard operating procedures, mapping heuristics, and the development of mapping tools; and 3) quality assurance incorporated validation of mappings using inter-rater agreement. RESULTS: Of 569,073 flowsheet concepts, 92% were mapped to the HDD. Of these, 31.5% represented LOINC concepts, 15% represented SNOMED CT and 1% represented both. 52.5% were mapped to HDD concepts with no standardized terminology representations. CONCLUSIONS: Nursing flowsheet data can be mapped to standard terminologies but there is not the breadth of coverage necessary to represent nursing assessments. Future work is necessary to develop a standard information model for the nursing process.