Document Type : Original Article
Authors
1 Assistant Professor of Health Information Management, Department of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran, Assistant Professor of Health Information Management, Student Research Committee, Abadan Faculty of Medical Sciences, Abadan, Iran
2 MSc of epidmiology, Department of public Health, Abadan Faculity of Medical Sciences, Abadan, Iran
Abstract
BACKGROUND: Direct transmission of notifiable disease information in a real‑time and reliable way
to public health decision‑makers is imperative for early identification of epidemiological trends as well
as proper response to potential pandemic like ongoing coronavirus disease 2019 crisis. Thus, this
research aimed to develop of semantic‑sharing and collaborative‑modeling to meet the information
exchange requirements of Iran’s notifiable diseases surveillance system.
MATERIALS AND METHODS: First, the Iran’s Notifiable diseases Minimum Data Set (INMDS)
was determined according to a literature review coupled with agreements of experts. Then the
INMDS was mapped to international terminologies and classification systems, and the Health Level
seven‑Clinical Document Architecture (HL7‑CDA) standard was leveraged to define the exchangeable
and machine‑readable data formats.
RESULTS: A core dataset consisting of 15 classes and 96 data fields was defined. Data
elements and response values were mapped to Systematized Nomenclature of Medicine‑Clinical
Terms (SNOMED‑CT) reference terminology. Then HL7‑CDA standard for interoperable data
exchange were defined.
CONCLUSION: The notifiable disease surveillance requires an integrative participation of
multidisciplinary team. In this field, data interoperability is more essential due to the heterogeneous
nature of health information systems. Developing of INMDS based on HL7‑CDA along with
SNOMED‑CT codes offers an inclusive and interoperable dataset that can help make notifiable
diseases data more comparable and reportable across studies and organizations. The proposed
data model will be further modifications in the future according probable changes in Iran’s notifiable
diseases list.
Keywords
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