A refined methodology for validation of information models derived from flowsheet data and applied to a genitourinary case

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism

Knowledge models inform organizational behavior through the logical association of documentation processes, definitions, data elements, and value sets. The development of a well-designed knowledge model allows for the reuse of electronic health record data to promote efficiency in practice, data interoperability, and the extensibility of data to new capabilities or functionality such as clinical decision support, quality improvement, and research. The purpose of this article is to describe the development and validation of a knowledge model for healthcare-associated venous thromboembolism prevention. The team used FloMap, an Internet-based survey resource, to compare metadata from six healthcare organizations to an initial draft model. The team used consensus decision-making over time to compare survey results. The resulting model included seven panels, 41 questions, and 231 values. A second validation step included completion of an Internet-based survey with 26 staff nurse respondents representing 15 healthcare organizations, two electronic health record vendors, and one academic institution. The final knowledge model contained nine Logical Observation Identifiers Names and Codes panels, 32 concepts, and 195 values representing an additional six panels (groupings), 15 concepts (questions), and the specification of 195 values (answers). The final model is useful for consistent documentation to demonstrate the contribution of nursing practice to the prevention of venous thromboembolism.

Identifying Reuse and Redundancies in Respiratory Flowsheet Documentation: Implications for Clinician Documentation Burden

Documentation burden is experienced by clinical end-users of the electronic health record. Flowsheet measure reuse and clinical concept redundancy are two contributors to documentation burden. In this paper, we described nursing flowsheet documentation hierarchy and frequency of use for one month from two hospitals in our health system. We examined respiratory care management documentation in greater detail. We found 59 instances of reuse of respiratory care flowsheet measure fields over two or more templates and groups, and 5 instances of clinical concept redundancy. Flowsheet measure fields for physical assessment observations and measurements were the most frequently documented and most reused, whereas respiratory intervention documentation was less frequently reused. Further research should investigate the relationship between flowsheet measure reuse and redundancy and EHR information overload and documentation burden.

A Methodology to Generate Longitudinally Updated Acute-On-Chronic Liver Failure Prognostication Scores From Electronic Health Record Data

Queries of electronic health record (EHR) data repositories allow for automated data collection. These techniques have not been used in hepatology due to the inability to capture hepatic encephalopathy (HE) grades, which are inputs for acute-on-chronic liver failure (ACLF) models. Here, we describe a methodology to use EHR data to calculate rolling ACLF scores. We examined 239 patient admissions with end-stage liver disease from July 2014 to June 2019. We mapped EHR flowsheet data to determine HE grades and calculated two longitudinally updated ACLF scores. We validated HE grades and ACLF diagnoses by chart review and calculated sensitivity, specificity, and Cohen's kappa. Of 239 patient admissions analyzed, 37% were women, 46% were non-Hispanic white, median age was 60 years, and the median Model for End-Stage Liver Disease-Na score at admission was 25. Of the 239, 7% were diagnosed with ACLF as defined by the North American Consortium for the Study of End-Stage Liver Disease (NACSELD) diagnostic criteria at admission, 27% during the hospitalization, and 9% at discharge. Forty percent were diagnosed with ACLF by the European Association for the Study of the Liver- Chronic Liver Failure Consortium (CLIF-C) diagnostic criteria at admission, 51% during the hospitalization, and 34% at discharge. From the chart review of 51 admissions, we found sensitivities and specificities for any HE (grades 1-4) were 92%-97% and 76%-95%, respectively; for severe HE (grades 3-4), sensitivities and specificities were 100% and 78%-98%, respectively. Cohen's kappa between flowsheet and chart review of HE grades ranged from 0.55 to 0.72. Sensitivities and specificities for NACSELD-ACLF diagnoses were 75%-100% and 96%-100%, respectively; for CLIF-C-ACLF diagnoses, these were 91%-100% and 96-100%, respectively. We generated approximately 28 unique ACLF scores per patient per admission day. Conclusion: We developed an informatics-based methodology to calculate longitudinally updated ACLF scores. This opens new analytic potentials, such as big data methods, to develop electronic phenotypes for patients with ACLF.

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.