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Using big data from real-world Australian rheumatology encounters to enhance clinical care and research


1, 2, 3, 4

 

  1. Monash Rheumatology and Monash University, Clayton, VIC, Australia. geoff.littlejohn@monash.edu
  2. Canberra Rheumatology, Canberra, ACT, Australia.
  3. OPAL Rheumatology Ltd, Sydney, NSW, Australia.
  4. Barwon Rheumatology Service, Geelong, VIC, Australia.

CER12542
2020 Vol.38, N°5
PI 0874, PF 0880
Full Papers

purchase article

PMID: 31820719 [PubMed]

Received: 28/06/2019
Accepted : 30/09/2019
In Press: 16/11/2019
Published: 02/10/2020

Abstract

OBJECTIVES:
OPAL (Optimising Patient outcomes in Australian rheumatoLogy) Rheumatology is an independent not for profit Australian clinical research organisation which is the custodian of one of the largest datasets of patients with rheumatic diseases in the world, containing real-world clinical data from more than >175,000 unique patients collected over more than 900,000 clinical consultations. We describe the evolution and outcomes of the OPAL dataset, with particular reference to the use of big data derived from real-world clinical encounters to enhance clinical care and research.
METHODS:
De-identified data are regularly extracted and aggregated from the electronic medical records (EMR) of consenting patients treated by approximately 100 rheumatologists around Australia. The EMR shared by OPAL clinicians was specifically customised for rheumatology and collects comprehensive information on demographics, disease history, activity and severity, co-morbidities, pathology, and medication use. In addition, OPAL captures multifaceted outcomes data from the patient perspective through a novel electronic patient-reported outcome (ePRO) delivery system which allows for health-related quality of life measures to be matched with clinical indices.
RESULTS:
Since inception in 2009, OPAL has produced 35 publications and abstracts. OPAL also provides real-world data to determine drug utilisation, efficacy and safety, elucidate the natural history of disease, highlight areas of unmet need, guide medical affairs and commercial strategy, and to support regulatory and reimbursement submissions.
CONCLUSIONS:
The extensive, evolving and organic OPAL dataset reflects the complexities of clinical rheumatological practice. It provides unique opportunities to enhance clinical care and research.

Rheumatology Article