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. As an exemplar, EHR flowsheet metadata (input) from multiple organizations was used to validate a fall prevention IM. DESIGN: A consensus-based, qualitative, descriptive approach was used to identify a minimum set of essential fall prevention data concepts documented by staff nurses in acute care. The goal was to increase generalizable and comparable nurse-sensitive data on the prevention of falls across organizations for big data research. METHODS: The research team conducted a retrospective, observational study using an iterative, consensus-based approach to map, analyze, and evaluate nursing flowsheet metadata contributed by eight health systems. The team used FloMap software to aggregate flowsheet data across organizations for mapping and comparison of data to a reference IM. The FloMap analysis was refined with input from staff nurse subject matter experts, review of published evidence, current documentation standards, Magnet Recognition nursing standards, and informal fall prevention nursing use cases. FINDINGS: Flowsheet metadata analyzed from the EHR systems represented 6.6 million patients, 27 million encounters, and 683 million observations. Compared to the original reference IM, five new IM classes were added, concepts were reduced by 14 (from 57 to 43), and 157 value set items were added. The final fall prevention IM incorporated 11 condition or age-specific fall risk screening tools and a fall event details class with 14 concepts. CONCLUSION: The iterative, consensus-based refinement and validation of the fall prevention IM from actual EHR fall prevention flowsheet documentation contributes to the ability to semantically exchange and compare fall prevention data across multiple health systems and organizations. This method and approach provides a process for standardizing flowsheet data as coded data for information exchange and use in big data research. CLINICAL RELEVANCE: Opportunities exist to work with EHR vendors and the Office of the National Coordinator for Health Information Technology to implement standardized IMs within EHRs to expand interoperability of nurse-sensitive data.

On the scene at Children's Hospitals and Clinics of Minnesota.

Transformational nursing leadership requires innovation and best practice synthesis to engage and advance nursing practice and outcomes. Children's Hospital and Clinics of Minnesota is creating a sustainable culture of patient safety that expects collaborative practice involving families and all clinical disciplines. Leadership and practice structures are essential to ensure high-reliability processes and achieve breakthrough performance. Several infrastructural paths are described to illustrate how Children's Hospitals and Clinics of Minnesota integrates multiple approaches toward a common purpose of clinical excellence.

Characterizing Functional Health Status of Surgical Patients in Clinical Notes.

Functional health status is an important factor not only for determining overall health, but also for measuring risks of adverse events. Our hypothesis is that important functional status data is contained in clinical notes. We found that several categories of phrases related to functional status including diagnoses, activity and care assessments, physical exam, functional scores, assistive equipment, symptoms, and surgical history were important factors. Use of functional health status level terms from our chart review compared to National Surgical Quality Improvement Program determination had varying sensitivities for correct functional status category identification, with 96% for independent patients, 60% for partially dependent patients, and 44% for totally dependent patients. Inter-rater agreement assessing term relevance to functional health status was high at 91% (Kappa=0.74). Functional status-related terms in clinical notes show potential for use in future methodologies for automated detection of functional health status for quality improvement registries and other clinical assessments.

Assessing the adequacy of the HL7/LOINC Document Ontology Role axis.

The healthcare landscape is changing, driven by innovative care models and the emergence of new roles that are inter-professional in nature. Currently, the HL7/LOINC Document Ontology (DO) aids the use and exchange of clinical documents using a multi-axis structure of document attributes for Kind of Document, Setting, Role, Subject Matter Domain, and Type of Service. In this study, the adequacy of the Role axis for representing the type of author documenting care was assessed. Experts used a master list of 220 values created from seven resources and established mapping guidelines. Baseline certification, licensure, and didactic training were identified as key parameters that define roles and hence often need to be pre-coordinated. DO was inadequate in representing 82% of roles, and this gap was primarily due to lack of granularity in DO. Next steps include refinement of the proposed schema for the Role axis and dissemination within the larger standards community.

Sensitivity of the pediatric early warning score to identify patient deterioration.

OBJECTIVE: We evaluated the Pediatric Early Warning Score (PEWS) sensitivity as an early indicator of patients deterioration leading to a Rapid Response Team (RRT)/code event. We hypothesized that at least 80% of patients had a critical PEWS preceding the event. We determined staff awareness of deterioration in patient status prior to the event as evidenced by consults, addition of monitoring equipment or increased frequency of assessment. The timing of these events was compared to critical PEWS times. METHODS: One hundred and seventy non-ICU RRT and 16 code events were identified between October 2006 and February 2008. We completed retrospective PEWS at four-hour intervals or less for twenty-four hours preceding the event. The PEWS algorithm, guiding staff to consult at a critical score > or =4 or a single domain score equal to 3, was applied. RESULTS: For 85.5% of patients the earliest indicator of deterioration, evidenced by a critical PEWS, was a median of 11 hours 36 minutes and the earliest preceding the event was 30 minutes. For 97.1% of patients the earliest median time to a consult was 80 minutes. Oximetry was added 6.9 hours for 43.5% of patients. 7% of patients had increased nursing assessment. A sub-group of patients had 1) critical PEWS, 2) consult and 3) addition of a monitor. The median time for earliest critical PEWS for these was significant (P < 0.001). CONCLUSION: PEWS can potentially provide a forewarning time >11 hours, alerting the team to adapt the care plan and possibly averting an RRT or code.