James C. McClay

The SAGE Guideline Model: Achievements and Overview

The SAGE (Standards-Based Active Guideline Environment) project was formed to create a methodology and infrastructure required to demonstrate integration of decision-support technology for guideline-based care in commercial clinical information systems. This paper describes the development and innovative features of the SAGE Guideline Model and reports our experience encoding four guidelines. Innovations include methods for integrating guideline-based decision support with clinical workflow and employment of enterprise order sets. Using SAGE, a clinician informatician can encode computable guideline content as recommendation sets using only standard terminologies and standards-based patient information models. The SAGE Model supports encoding large portions of guideline knowledge as re-usable declarative evidence statements and supports querying external knowledge sources.

Modeling guidelines for integration into clinical workflow.

The success of clinical decision-support systems requires that they are seamlessly integrated into clinical workflow. In the SAGE project, which aims to create the technological infra-structure for implementing computable clinical practice guide-lines in enterprise settings, we created a deployment-driven methodology for developing guideline knowledge bases. It involves (1) identification of usage scenarios of guideline-based care in clinical workflow, (2) distillation and disambiguation of guideline knowledge relevant to these usage scenarios, (3) formalization of data elements and vocabulary used in the guideline, and (4) encoding of usage scenarios and guideline knowledge using an executable guideline model. This methodology makes explicit the points in the care process where guideline-based decision aids are appropriate and the roles of clinicians for whom the guideline-based assistance is intended. We have evaluated the methodology by simulating the deployment of an immunization guideline in a real clinical information system and by reconstructing the workflow context of a deployed decision-support system for guideline-based care. We discuss the implication of deployment-driven guideline encoding for sharability of executable guidelines.

Adoption of electronic health records: A qualitative study of academic and private physicians and health administrators

OBJECTIVE Less than 20% of hospitals in the US have an electronic health record (EHR). In this qualitative study, we examine the perspectives of both academic and private physicians and administrators as stakeholders, and their alignment, to explore their perspectives on the use of technology in the clinical environment. METHODS Focus groups were conducted with 74 participants who were asked a series of open-ended questions. Grounded theory was used to analyze the transcribed data and build convergent themes. The relevance and importance of themes was constructed by examining frequency, convergence, and intensity. A model was proposed that represents the interactions between themes. RESULTS Six major themes emerged, which include the impact of EHR systems on workflow, patient care, communication, research/outcomes/billing, education/learning, and institutional culture. Academic and private physicians were confident of the future benefits of EHR systems, yet cautious about the current implementations of EHR, and its impact on interactions with other members of the healthcare team and with patients, and the amount of time necessary to use EHRs. Private physicians differed on education and were uneasy about the steep learning curve necessary for use of new systems. In contrast to physicians, university and hospital administrators are optimistic, and value the availability of data for use in reporting. CONCLUSION The results of our study indicate that both private and academic physicians concur on the need for features that maintain and enhance the relationship with the patient and the healthcare team. Resistance to adoption is related to insufficient functionality and its potential negative impact on patient care. Integration of data collection into clinical workflows must consider the unexpected costs of data acquisition.

Delphi Consensus on the Feasibility of Translating the ACEP Clinical Policies Into Computerized Clinical Decision Support

Clinical practice guidelines are developed to reduce variations in clinical practice, with the goal of improving health care quality and cost. However, evidence-based practice guidelines face barriers to dissemination, implementation, usability, integration into practice, and use. The American College of Emergency Physicians (ACEP) clinical policies have been shown to be safe and effective and are even cited by other specialties. In spite of the benefits of the ACEP clinical policies, implementation of these clinical practice guidelines into physician practice continues to be a challenge. Translation of the ACEP clinical policies into real-time computerized clinical decision support systems could help address these barriers and improve clinician decision making at the point of care. The investigators convened an emergency medicine informatics expert panel and used a Delphi consensus process to assess the feasibility of translating the current ACEP clinical policies into clinical decision support content. This resulting consensus document will serve to identify limitations to implementation of the existing ACEP Clinical Policies so that future clinical practice guideline development will consider implementation into clinical decision support at all stages of guideline development.

Semantic analysis of SNOMED CT for a post-coordinated database of histopathology findings

Objective This research investigated the use of SNOMED CT to represent diagnostic tissue morphologies and notable tissue architectures typically found within a pathologists microscopic examination report to identify gaps in expressivity of SNOMED CT for use in anatomic pathology. Methods 24 breast biopsy cases were reviewed by two board certified surgical pathologists who independently described the diagnostically important tissue architectures and diagnostic morphologies observed by microscopic examination. In addition, diagnostic comments and details were extracted from the original diagnostic pathology report. 95 unique clinical statements were extracted from 13 malignant and 11 benign breast needle biopsy cases. Results 75% of the inventoried diagnostic terms and statements could be represented by valid SNOMED CT expressions. The expressions included one pre-coordinated expression and 73 post-coordinated expressions. No valid SNOMED CT expressions could be identified or developed to unambiguously assert the meaning of 21 statements (ie, 25% of inventoried clinical statements). Evaluation of the findings indicated that SNOMED CT lacked sufficient definitional expressions or the SNOMED CT concept model prohibited use of certain defined concepts needed to describe the numerous, diagnostically important tissue architectures and morphologic changes found within a surgical pathology microscopic examination. Conclusions Because information gathered during microscopic histopathology examination provides the basis of pathology diagnoses, additional concept definitions for tissue morphometries and modifications to the SNOMED CT concept model are needed and suggested to represent detailed histopathologic findings in computable fashion for purposes of patient information exchange and research. Trial registration number UNMC Institutional Review Board ID# 342-11-EP.

Standard for improving emergency information interoperability: the HL7 data elements for emergency department systems

BACKGROUND Emergency departments in the United States service over 130 million visits per year. The demands for information from these visits require interoperable data exchange standards. While multiple data exchange specifications are in use, none have undergone rigorous standards review. This paper describes the creation and balloting of the Health Level Seven (HL7) Data Elements for Emergency Department Systems (DEEDS). METHODS Existing data exchange specifications were collected and organized into categories reflecting the workflow of emergency care. The concepts were then mapped to existing standards for vocabulary, data types, and the HL7 information model. The HL7 community then processed the specification through the normal balloting process addressing all comments and concerns. The resulting specification was then submitted for publication as an HL7 informational standard. RESULTS The resulting specification contains 525 concepts related to emergency care required for operations and reporting to external agencies. An additional 200 of the most commonly ordered laboratory tests were included. Each concept was given a unique identifier and mapped to Logical Observation Identifiers, Names, and Codes (LOINC). HL7 standard data types were applied. DISCUSSION The HL7 DEEDS specification represents the first set of common ED related data elements to undergo rigorous standards development. The availability of this standard will contribute to improved interoperability of emergency care data.

The Impact of Domain Knowledge on Structured Data Collection and Templated Note Design

OBJECTIVE The objective of this case report is to evaluate the importance of specialized domain knowledge when designing and using structured templated notes in a clinical environment. METHODS To analyze the impact of specialization on structured note generation we compared notes generated for three scenarios: 1) We compared the templated history of present illness (HPI) for patients presenting with a dermatology concern to the dermatologist versus the emergency department. 2) We compared the evaluation of chest pain by ED physicians versus cardiologists. 3) Finally, we compared the data elements asked for in the evaluation of the gastrointestinal system between cardiologists and the liver transplant service (LTS). We used the SNOMED CT representation via BioPortal to evaluate specificity and grouping between data elements and specialized physician groups. RESULTS We found few similarities in structured data elements designed by and for the specific physician groups. The distinctness represented both differences in granularity as well as fundamental differences in data elements requested. When compared to ED physicians, dermatologists had different and more granular elements while cardiologists requested much more granular data. Comparing cardiologists and LTS, there were differences in the data elements requested. CONCLUSION This case study supports the importance of domain knowledge in EHR design and implementation. That different specialities should want and use different information is well supported by cognitive science literature. Despite this, it is rare for domain knowledge to be considered in EHR implementation. Physicians with correct domain knowledge should be involved in the design process of templated notes.

An alternative database approach for management of SNOMED CT and improved patient data queries

OBJECTIVE SNOMED CT is the international lingua franca of terminologies for human health. Based in Description Logics (DL), the terminology enables data queries that incorporate inferences between data elements, as well as, those relationships that are explicitly stated. However, the ontologic and polyhierarchical nature of the SNOMED CT concept model make it difficult to implement in its entirety within electronic health record systems that largely employ object oriented or relational database architectures. The result is a reduction of data richness, limitations of query capability and increased systems overhead. The hypothesis of this research was that a graph database (graph DB) architecture using SNOMED CT as the basis for the data model and subsequently modeling patient data upon the semantic core of SNOMED CT could exploit the full value of the terminology to enrich and support advanced data querying capability of patient data sets. METHODS The hypothesis was tested by instantiating a graph DB with the fully classified SNOMED CT concept model. The graph DB instance was tested for integrity by calculating the transitive closure table for the SNOMED CT hierarchy and comparing the results with transitive closure tables created using current, validated methods. The graph DB was then populated with 461,171 anonymized patient record fragments and over 2.1 million associated SNOMED CT clinical findings. Queries, including concept negation and disjunction, were then run against the graph database and an enterprise Oracle relational database (RDBMS) of the same patient data sets. The graph DB was then populated with laboratory data encoded using LOINC, as well as, medication data encoded with RxNorm and complex queries performed using LOINC, RxNorm and SNOMED CT to identify uniquely described patient populations. RESULTS A graph database instance was successfully created for two international releases of SNOMED CT and two US SNOMED CT editions. Transitive closure tables and descriptive statistics generated using the graph database were identical to those using validated methods. Patient queries produced identical patient count results to the Oracle RDBMS with comparable times. Database queries involving defining attributes of SNOMED CT concepts were possible with the graph DB. The same queries could not be directly performed with the Oracle RDBMS representation of the patient data and required the creation and use of external terminology services. Further, queries of undefined depth were successful in identifying unknown relationships between patient cohorts. CONCLUSION The results of this study supported the hypothesis that a patient database built upon and around the semantic model of SNOMED CT was possible. The model supported queries that leveraged all aspects of the SNOMED CT logical model to produce clinically relevant query results. Logical disjunction and negation queries were possible using the data model, as well as, queries that extended beyond the structural IS_A hierarchy of SNOMED CT to include queries that employed defining attribute-values of SNOMED CT concepts as search parameters. As medical terminologies, such as SNOMED CT, continue to expand, they will become more complex and model consistency will be more difficult to assure. Simultaneously, consumers of data will increasingly demand improvements to query functionality to accommodate additional granularity of clinical concepts without sacrificing speed. This new line of research provides an alternative approach to instantiating and querying patient data represented using advanced computable clinical terminologies.

Toward improved heuristic evaluation of EHRs

Electronic Health Records (EHRs) can improve the quality, safety, and efficiency of patient care. Migration to EHRs is progressing, but has been slowed by concerns related to interoperability, security, cost, patient safety, and usability. This paper focuses on EHR usability, specifically heuristic evaluation, or utilizing accepted guidelines for assessing EHR interface design. Health-care researchers initially applied industry-standard heuristics to EHRs, but subsequently health-care-specific groups have adapted and expanded these standard heuristics, calling for development and use of heuristics specific to EHRs. This paper first summarizes the evolution of heuristic evaluation of EHRs, then discusses the similarities and differences between these various approaches. This is an important step in developing community consensus on integrated heuristics, the basis of successful heuristic evaluation of EHRs. We then discuss the ‘Theory of Fit’ as a means of explaining the existence of these somewhat different heuristics, and close with suggestions for further research.

Comparing the German emergency department medical record with the US HL7 data elements for emergency department systems

Interoperability between emergency department (ED) information systems requires a shared data specification. In 2013 Health Level Seven International, an international standards body, approved a specification for Data Elements for Emergency Department Systems (DEEDS) for use in the United States. A similar specification was created in Germany for national employment, defining data elements and forms. This study presents the first step in the efforts to harmonize the two data definitions for International approval by comparing the meaning of the German Emergency Department Medical Record (GEDMR) data element definitions with the US DEEDS using a methodology for terminology mapping from ISO/TR 12300. The comparison between GEDMR and DEEDS did show significant differences in certain domains. The results support development of an international standard for ED data elements.