Defining health data elements under the HL7 development framework for metadata management

Abstract

Background: Health data from different specialties or domains generallly have diverse formats and meanings, which can cause semantic communication barriers when these data are exchanged among heterogeneous systems. As such, this study is intended to develop a national health concept data model (HCDM) and develop a corresponding system to facilitate healthcare data standardization and centralized metadata management.

Methods: Based on 55 data sets (4640 data items) from 7 health business domains in China, a bottom-up approach was employed to build the structure and metadata for HCDM by referencing HL7 RIM. According to ISO/IEC 11179, a top-down approach was used to develop and standardize the data elements.

Results: HCDM adopted three-level architecture of class, attribute and data type, and consisted of 6 classes and 15 sub-classes. Each class had a set of descriptive attributes and every attribute was assigned a data type. 100 initial data elements (DEs) were extracted from HCDM and 144 general DEs were derived from corresponding initial DEs. Domain DEs were transformed by specializing general DEs using 12 controlled vocabularies which developed from HL7 vocabularies and actual health demands. A model-based system was successfully established to evaluate and manage the NHDD.

Conclusions: HCDM provided a unified metadata reference for multi-source data standardization and management. This approach of defining health data elements was a feasible solution in healthcare information standardization to enable healthcare interoperability in China.

Keywords: Data element; Health level seven; Metadata; RIM; Standards.

Fig. 1

Framework of HCDM. HCDM has 6 classes, 15 sub-classes,100 attributes and 100 data types. Each class has several attributes and data types to represent its semantics. The green rectangles represent parent classes and the blue ones represent sub-classes. Hollow arrows represent the inheritance relationship from parent class to child class

Fig. 2

Abstract process of initial data elements. The left side indicates the initial data elements abstract process, and the right side shows an example for initial data element person’s address, which is formed by constraining the object class “person”, the attribute “address” of person and data type “AD” in the Health Concept Data Model

Fig. 3

The relationship of general DE, controlled vocabulary and domain DE. “Entity name” of general DE can be constrained to the domain DE “doctor’s name” based on the term “doctor” and the domain DE “surgeon’s name” based on the term “surgeon” (subtype of “doctor”) in the vocabulary of “roleCode”, and to “operator’s name” based on the term “operator” in the vocabulary of “participationCodeType”. The “entity name” ofgeneral DE can also be constrained to the domain DE “operation doctor’s name” based on the vocabularies combination (pre-coordinated) of the “roleCode (term: doctor)” and “participationCodeType (term: operator)”

Fig. 4

A display interface of initial DE in the system, including initial DE’s Chinese name, English name, data type, edit and delete function

Fig. 5

The input and revise interface of domain DE in the system. Domain DEs are standardized through 22 metadata descriptions, including 14 data element attributes and 6 value code attributes. Among them, data element attributes reflect relationships among domain DEs, HCDM and NHDD. Value domain attributes reflect the relationship between domain DEs and controlled vocabularies

Fig. 6

The work process of HCDM, NHDD and its implementation. There are mainly 6 steps for our work process: step 1 establishes the HCDM, step 2 extracts the initial DE, step 3 constructs the general DE, step 4 develops controlled vocabularies and domain Des, step 5 develops the web-based system and step 6 evaluates and optimize HCDM and NHDD