National health information network cost and structure.
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Information Services↗
Biomedical subjects
Robert H Dolin
Publications and source records attributed to Robert H Dolin.
HL7 Clinical Document Architecture, Release 2.
Clinical Document Architecture, Release One (CDA R1), became an American National Standards Institute (ANSI)-approved HL7 Standard in November 2000, representing the first specification derived from the Health Level 7 (HL7) Reference Information Model (RIM). CDA, Release Two (CDA R2), became an ANSI-approved HL7 Standard in May 2005 and is the subject of this article, where the focus is primarily on how the standard has evolved since CDA R1, particularly in the area of semantic representation of clinical events. CDA is a document markup standard that specifies the structure and semantics of a clinical document (such as a discharge summary or progress note) for the purpose of exchange. A CDA document is a defined and complete information object that can include text, images, sounds, and other multimedia content. It can be transferred within a message and can exist independently, outside the transferring message. CDA documents are encoded in Extensible Markup Language (XML), and they derive their machine processable meaning from the RIM, coupled with terminology. The CDA R2 model is richly expressive, enabling the formal representation of clinical statements (such as observations, medication administrations, and adverse events) such that they can be interpreted and acted upon by a computer. On the other hand, CDA R2 offers a low bar for adoption, providing a mechanism for simply wrapping a non-XML document with the CDA header or for creating a document with a structured header and sections containing only narrative content. The intent is to facilitate widespread adoption, while providing a mechanism for incremental semantic interoperability.
Computer Communication Networks↗
Kaiser Permanente's Convergent Medical Terminology.
This paper describes Kaiser Permanente's (KP) enterprise-wide medical terminology solution, referred to as our Convergent Medical Terminology (CMT). Initially developed to serve the needs of a regional electronic health record, CMT has evolved into a core KP asset, serving as the common terminology across all applications. CMT serves as the definitive source of concept definitions for the organization, provides a consistent structure and access method to all codes used by the organization, and is KP's language of interoperability, with cross-mappings to regional ancillary systems and administrative billing codes. The core of CMT is comprised of SNOMED CT, laboratory LOINC, and First DataBank drug terminology. These are integrated into a single poly-hierarchically structured knowledge base. Cross map sets provide bi-directional translations between CMT and ancillary applications and administrative billing codes. Context sets provide subsets of CMT for use in specific contexts. Our experience with CMT has lead us to conclude that a successful terminology solution requires that: (1) usability considerations are an organizational priority; (2) "interface" terminology is differentiated from "reference" terminology; (3) it be easy for clinicians to find the concepts they need; (4) the immediate value of coded data be apparent to clinician user; (5) there be a well defined approach to terminology extensions. Over the past several years, there has been substantial progress made in the domain coverage and standardization of medical terminology. KP has learned to exploit that terminology in ways that are clinician-acceptable and that provide powerful options for data analysis and reporting.
Health Maintenance Organizations↗
Managing the tensions between national standardization vs. regional localization of clinical content and templates.
The deployment of sophisticated software tools and electronic health records offers many new opportunities and challenges to support care delivery. One of the key opportunities is to enhance the quality of care with evidence-based medicine (EBM). One of the key challenges is to embed EBM in tools that directly facilitate the process of documentation and care delivery. Since clinicians typically have the option of using free text for most of their documentation, the tools that provide embedded EBM must be at least as efficient as free text. There are many requirements that must be met in order to effectively embed EBM within clinical content tools and enhance both the usability and the actual use of such tools and clinical content: (1) Facilitate the documentation process; (2) Facilitate the care delivery process, e.g. make order entry faster; (3) Contain recommendations that are highly relevant to the clinical context of an encounter; (4) Aid in the capture of discrete coded data. Support for local variation is often key to meeting these objectives and becomes a central factor in helping clinicians shift from unstructured free text, to the use of these tools, which support the delivery of EBM. This document describes the central tension between the objective of national standardization and delivery of EBM and the need for regional localization of clinical content. This tension must be thoughtfully managed to maximize the quality of care delivery and associated workflow practices. The key elements of legitimate local variation that must be recognized in order to achieve these goals are described in this document, and the key principles for managing the tensions between generalization and localization are identified.
Decision Support Systems, Clinical↗
Selective retrieval of pre- and post-coordinated SNOMED concepts.
In general, it is very straightforward to store concept identifiers in electronic medical records and represent them in messages. Information models typically specify the fields that can contain coded entries. For each of these fields there may be additional constraints governing exactly which concept identifiers are applicable. However, because modern terminologies such as SNOMED CT are compositional, allowing concept expressions to be pre-coordinated within the terminology or post-coordinated within the medical record, there remains the potential to express a concept in more than one way. Often times, the various representations are similar, but not equivalent. This paper describes an approach for retrieving these pre- and post-coordinated concept expressions: (1) Create concept expressions using a logically-well-structured terminology (e.g., SNOMED CT) according to the rules of a well-specified information model (in this paper we use the HL7 RIM); (2) Transform pre- and post-coordinated concept expressions into a normalized form; (3) Transform queries into the same normalized form. The normalized instances can then be directly compared to the query. Several implementation considerations have been identified. Transformations into a normal form and execution of queries that require traversal of hierarchies need to be optimized. A detailed understanding of the information model and the terminology model are prerequisites. Queries based on the semantic properties of concepts are only as complete as the semantic information contained in the terminology model. Despite these considerations, the approach appears powerful and will continue to be refined.
Information Storage and Retrieval↗