OUTSTANDING PODIUM-RESEARCH: Coding Data Elements of Clinical Information Models for Interoperability

    loading  Checking for direct PDF access through Ovid

Abstract

Introduction/aims

Clinical information models are important and necessary to integrate clinical data within health information systems. Providing quality patient care requires continuity of communication between providers and across settings. Having universal, evidence-based, knowledge content that utilizes standard terminologies will help with consistency and meaning of data entered by clinicians. The goal of this study is to encode data elements of a specific skin assessment model using SNOMED-CT and LOINC.

Methods/process/procedures

A skin and wound assessment clinical data model was designed by a national group of nursing leaders. The data elements within the model were formed from evidence-based practice and expert clinicians of wound care. The model consisted of attributes (questions/observation) and values (findings) for skin assessment and wound assessment concepts. The data elements were matched to LOINC and the values to SNOMED-CT clinical concepts.

Results

The model contained five panels for skin assessment such as skin assessment class, Braden scale, wound bed, wound exudate, and dressing. Each panel had a set of questions that were assessed and was submitted to LOINC as a new panel. The questions (observations) were mapped to LOINC observation codes. Each question had a set of answers (values) that were mapped to SNOMED-CT findings. The concepts that could not be found within LOINC or SNOMED-CT were submitted to the standards for inclusion. The resulting model with the terminology bindings was released on the Internet for national use.

Discussion/outcomes

Encoded data elements within clinical information models will improve accuracy and increase efficiency for providers. Continuity of care from coded structured patient data is a direct benefit of incorporating standard models into the electronic health information systems for clinical care. Different types of data models can be incorporated into the various electronic health information systems and provide the framework for quality measures and improving evidence-based practice.

Related Topics

    loading  Loading Related Articles