Developing HL7 CDA-Based Data Warehouse for the Use of Electronic Health Record Data for Secondary Purposes

Autor: Fabrizio Pecoraro, Fabrizio L. Ricci, Daniela Luzi
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: ACI Open (2019): 44–62. doi:10.1055/s-0039-1688936
info:cnr-pdr/source/autori:Pecoraro F., Luzi D., Ricci F.L./titolo:Developing HL7 CDA-Based Data Warehouse for the Use of Electronic Health Record Data for Secondary Purposes/doi:10.1055%2Fs-0039-1688936/rivista:ACI Open/anno:2019/pagina_da:44/pagina_a:62/intervallo_pagine:44–62/volume
DOI: 10.1055/s-0039-1688936
Popis: Background The growing availability of clinical and administrative data collected in electronic health records (EHRs) have led researchers and policy makers to implement data warehouses to improve the reuse of EHR data for secondary purposes. This approach can take advantages from a unique source of information that collects data from providers across multiple organizations. Moreover, the development of a data warehouse benefits from the standards adopted to exchange data provided by heterogeneous systems. Objective This article aims to design and implement a conceptual framework that semiautomatically extracts information collected in Health Level 7 Clinical Document Architecture (CDA) documents stored in an EHR and transforms them to be loaded in a target data warehouse. Results The solution adopted in this article supports the integration of the EHR as an operational data store in a data warehouse infrastructure. Moreover, data structure of EHR clinical documents and the data warehouse modeling schemas are analyzed to define a semiautomatic framework that maps the primitives of the CDA with the concepts of the dimensional model. The case study successfully tests this approach. Conclusion The proposed solution guarantees data quality using structured documents already integrated in a large-scale infrastructure, with a timely updated information flow. It ensures data integrity and consistency and has the advantage to be based on a sample size that covers a broad target population. Moreover, the use of CDAs simplifies the definition of extract, transform, and load tools through the adoption of a conceptual framework that load the information stored in the CDA in the data warehouse.
Databáze: OpenAIRE