Conceptual design of the dual X-ray absorptiometry health informatics prediction system for osteoporosis care

Erjiang E, John J. Carey, Tingyan Wang, Lan Yang, Wing P. Chan, Bryan Whelan, Carmel Silke, Miriam O’Sullivan, Bridie Rooney, Aoife McPartland, Gráinne O’Malley, Attracta Brennan, Ming Yu, Mary Dempsey

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Osteoporotic fractures are a major and growing public health problem, which is strongly associated with other illnesses and multi-morbidity. Big data analytics has the potential to improve care for osteoporotic fractures and other non-communicable diseases (NCDs), reduces healthcare costs and improves healthcare decision-making for patients with multi-disorders. However, robust and comprehensive utilization of healthcare big data in osteoporosis care practice remains unsatisfactory. In this paper, we present a conceptual design of an intelligent analytics system, namely, the dual X-ray absorptiometry (DXA) health informatics prediction (HIP) system, for healthcare big data research and development. Comprising data source, extraction, transformation, loading, modelling and application, the DXA HIP system was applied in an osteoporosis healthcare context for fracture risk prediction and the investigation of multi-morbidity risk. Data was sourced from four DXA machines located in three healthcare centres in Ireland. The DXA HIP system is novel within the Irish context as it enables the study of fracture-related issues in a larger and more representative Irish population than previous studies. We propose this system is applicable to investigate other NCDs which have the potential to improve the overall quality of patient care and substantially reduce the burden and cost of all NCDs.

Original languageEnglish
JournalHealth Informatics Journal
Volume27
Issue number4
DOIs
Publication statusPublished - Dec 18 2021

Keywords

  • data analysis framework
  • disease prediction
  • health information prediction system
  • healthcare big data
  • osteoporosis

ASJC Scopus subject areas

  • Health Informatics

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