Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar.

Purpose: The rapid implementation of electronic health records (EHRs) resulted in a lack of data standardization and created considerable difficulty for secondary use of EHR documentation data within and between organizations. While EHRs contain documentation data (input), nurses and healthcare organizations rarely have useable documentation data (output). The purpose of this article is to describe a method of standardizing EHR flowsheet documentation data using information models (IMs) to support exchange, quality improvement, and big data research.

Validation and Refinement of a Pain Information Model from EHR Flowsheet Data.

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.

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.

Developing Standardized Physiologic Assessments.

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).

EHR Documentation: The Hype and the Hope for Improving Nursing Satisfaction and Quality Outcomes.

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.