title: Standardizing Physiologic Assessment Data to Enable Big Data Analytics.
abstract: 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.
authors.affiliation: 1 Intermountain Healthcare, Salt Lake City, UT, USA.|2 The University of Utah, Salt Lake City, UT, USA.
authors.forename: Susan A
authors.initials: SA
authors.lastname: Matney
authors.affiliation: 3 Cedars-Sinai Health System, Los Angeles, CA, USA.
authors.forename: Theresa Tess
authors.initials: TT
authors.lastname: Settergren
authors.affiliation: 4 The University of Arizona, Tucson, AZ, USA.
authors.forename: Jane M
authors.initials: JM
authors.lastname: Carrington
authors.affiliation: 5 Duke University School of Nursing, Durham, NC, USA.
authors.forename: Rachel L
authors.initials: RL
authors.lastname: Richesson
authors.affiliation: 2 The University of Utah, Salt Lake City, UT, USA.|6 3M Health Information Systems, Salt Lake City, UT, USA.
authors.forename: Amy
authors.initials: A
authors.lastname: Sheide
authors.affiliation: 7 University of Minnesota, Minneapolis, MN, USA.
authors.forename: Bonnie L
authors.initials: BL
authors.lastname: Westra
keywords: LOINC; SNOMED CT; data exchange standards; medical surgical nursing; multi-institutional research; nursing assessment; nursing informatics