International Journal of Medical Informatics
Volume 79, Issue 6 , Pages 450-458, June 2010

Harmonization of health data at national level: A pilot study in China

  • Danhong Liu

      Affiliations

    • Institute for Health Informatics, Fourth Military Medical University, Changle West Road 17#, Xi’an 710032, PR China
  • ,
  • Xia Wang

      Affiliations

    • Institute for Health Informatics, Fourth Military Medical University, Changle West Road 17#, Xi’an 710032, PR China
    • Co-first author.
  • ,
  • Feng Pan

      Affiliations

    • Institute for Health Informatics, Fourth Military Medical University, Changle West Road 17#, Xi’an 710032, PR China
  • ,
  • Peng Yang

      Affiliations

    • Institute for Health Informatics, Fourth Military Medical University, Changle West Road 17#, Xi’an 710032, PR China
  • ,
  • Yongyong Xu

      Affiliations

    • Institute for Health Informatics, Fourth Military Medical University, Changle West Road 17#, Xi’an 710032, PR China
    • Corresponding Author InformationCorresponding author. Tel.: +86 29 84774858; fax: +86 29 84774858.
  • ,
  • Xuejun Tang

      Affiliations

    • Center for Health Statistics and Information, Ministry of Health, People's Republic of China, Beijing 100044, PR China
  • ,
  • Jianping Hu

      Affiliations

    • Center for Health Statistics and Information, Ministry of Health, People's Republic of China, Beijing 100044, PR China
  • ,
  • Keqin Rao

      Affiliations

    • Center for Health Statistics and Information, Ministry of Health, People's Republic of China, Beijing 100044, PR China

Received 27 August 2009; received in revised form 26 November 2009; accepted 7 March 2010. published online 16 April 2010.

Abstract 

Objective

For the purpose of establishing electronic health record (EHR), business-oriented health data distributed in different systems should be integrated to focus on individuals. This study is aimed at collecting health data items that are now nationally available in various health information systems, and harmonizing them by modeling and defining the data elements.

Methods

This study followed a bottom-up strategy in data standard development. Health data items were identified and collected by referring to national health service regulations, consulting domain experts and performing field investigations. Data items were classified and modeled based on recognized domain knowledge, information standards and specifications developed by standard development organizations (SDOs) of other countries. Data elements were extracted from data items and defined according to ISO/IEC 11179 – Metadata registries (MDR) and confirmed needs.

Results

1588 data items were collected from 33 recording forms that have been used nationally in health services, and were classified with a conceptual data model that was composed of 7 super classes (healthcare clients, healthcare providers, birth registry, health event/act, healthcare process, death, and others) and 15 classes (person's identification, person's socio-demographic characteristics, address, communication, provider-organization, provider-individual, birth, health event/act, observation, procedure, drug and material administration, recommendation, evaluation, expenditure, death, others). By normalizing the concepts and representations of data items, data elements were derived and defined as the attributes of classes in the data model. Data items were specified as instances of corresponding data elements.

Conclusions

A large number of health data have been collected nationwide but person's life-long health record is incomplete and inconsistent now. To integrate such massive quantity of health data from various sources, a conceptual data model was established to organize data items, avoiding conflicts and duplications in between. For data consistency, data elements should be extracted from the data items and defined as attributes of classes in the data model by choosing essential metadata attributes. Treating data items as instances of well defined data elements might make data in different contexts manageable and agreeable. To be semantically unambiguous, further study should be performed to deal with the standardization of detailed medical information, and perfect the approach of data harmonization.

Keywords: Health data, Data model, Data element, Metadata, Electronic health record, Standard

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PII: S1386-5056(10)00061-4

doi:10.1016/j.ijmedinf.2010.03.002

International Journal of Medical Informatics
Volume 79, Issue 6 , Pages 450-458, June 2010