Extending the LOINC conceptual schema to support standardized assessment instruments.
OBJECTIVE: To extend the Clinical LOINC (Logical Observation Identifiers, Names, and Codes) semantic schema to support (1) the representation of common types of assessment instruments and (2) the disambiguation of versions and variants that may have differing reliability and validity. DESIGN: Psychometric theory and survey research framework, plus an existing tool for implementing many types of assessment instruments (Dialogix), were used to identify and model the attributes of instruments that affect reliability and validity. Four modifications to the LOINC semantic schema were proposed as a means for completely identifying, disambiguating, and operationalizing a broad range of assessment instruments. MEASUREMENTS: Assess the feasibility of modeling these attributes within LOINC, with and without the proposed extensions. RESULTS: The existing LOINC schema for supporting assessment instruments was unable to consistently meet either objective. In contrast, the proposed extensions were able to meet both objectives, because they are derived from the Dialogix schema, which already performs those tasks. CONCLUSION: These extensions to LOINC can facilitate the use, analysis, and improvement of assessment instruments and thereby may improve the detection and management of errors. (+info)
Information model and terminology model issues related to goals.
Goal statements are a significant component of structures that support the process of health care delivery such as practice guidelines, standards of care, critical pathways, disease management plans, patient education plans, and nursing care plans. Although these structures are increasingly computer-based, there has been little attention to the formal representation of goal statements. This is a necessary prerequisite for enabling semantic interoperability. Existing and evolving information model and terminology model standards offer some approaches that may be applicable to goal statements, however, a number of issues require resolution (+info)
Using LOINC to link an EMR to the pertinent paragraph in a structured reference knowledge base.
Intermountain Health Care has integrated the electronic medical record (EMR) with online information resources in order to create easy access to a knowledge base which practicing physicians can use at the point of care. When a user is reviewing problems/diagnosis, medications, or clinical laboratory test results, they can conveniently access a "pertinent paragraph" of reference literature that pertains to the clinical data in the EMR. Using terminology first coined by Cimino1, we call this application the "infobutton." We describe the architectural issues involved in linking our electronic medical record with a structured laboratory knowledge base. The application has been well received as noted by anecdotal comments made by physicians and usage of the application. (+info)
Introduction of a hierarchy to LOINC to facilitate public health reporting.
Public health reporting of laboratory results requires unambiguous identification of the test performed and the result observed. Some laboratories are currently using Logical Observation Identifier Names and Codes (LOINC) for the electronic reporting of laboratory tests and their results to public health departments. Initial use revealed inconsistent identification and use of LOINC concepts by laboratories and public health agencies and an inability to systematically extend, for public health use, the tables when adding new concepts. We applied simple, logical rules to existing LOINC concepts to facilitate the creation of a hierarchy of concepts and to allow the identification and specification of appropriate terms for public health reporting and subsequent data aggregation. The hierarchy also allows the systematic addition of new concepts further supporting public health reporting. Application of the hierarchy is illustrated by using all laboratory LOINC concepts assigned to the subset of microbiology test types (CLASS MICRO). (+info)
Contextualizing heterogeneous data for integration and inference.
Systems that attempt to integrate and analyze data from multiple data sources are greatly aided by the addition of specific semantic and metadata "context" that explicitly describes what a data value means. In this paper, we describe a systematic approach to constructing models of data and their context. Our approach provides a generic "template" for constructing such models. For each data source, a developer creates a customized model by filling in the tem-plate with predefined attributes and value. This approach facilitates model construction and provides consistent syntax and semantics among models created with the template. Systems that can process the template structure and attribute values can reason about any model so described. We used the template to create a detailed knowledge base for syndromic surveillance data integration and analysis. The knowledge base provided support for data integration, translation, and analysis methods. (+info)
Frequency of laboratory test utilization in the intensive care unit and its implications for large scale data collection efforts.
Mapping of local use names to standardized naming schemas such as LOINC" micro is a time consuming and difficult task when done retrospectively or during the configuration of new information systems. We found that a relatively small number of tests and profiles (106 to 205) represent 99% of all testing done in 3 ICUs studied. In addition, all of the lab studies needed for the most commonly used ICU scoring systems fell into the top 23 lab studies and profiles performed in each ICU studied. We have identified a subset of the LOINC database which, because of their frequency of use, should be the focus of efforts to bring naming uniformity to ICU information systems. (+info)
The map to LOINC project.
We describe a pilot project to standardize local laboratory test names to Logical Observation Identifier Names and Codes (LOINC) at five Indian Health Service (IHS) medical facilities. An automated mapping tool was developed to assign LOINC codes. The laboratory test names not mapped to LOINC by the mapping tool were assigned LOINC codes manually. The results achieved matched current benchmarks. (+info)
Development of an information model for solid organ transplantation.
Information required to manage transplant patients and donors is complex, voluminous and requires the reporting and use of one person's medical information within another person's record. One strategy using a vocabulary model (i.e., LOINC codes with *DONOR specified in the system axes) will lead to problems with combinatorial explosion. After evaluating workflow processes, data collection forms, decision support and functional requirements, we designed and implemented an extendable information model to support the process of care following liver transplantation. (+info)