QUT ePrints

Linking ambulance, emergency department and hospital admissions data : understanding the emergency journey

Crilly, Julia L., O'Dwyer, John A., O"Dwyer, Marilla A., Lind, James F., Peters, Julia A., Tippett, Vivienne C., Wallis, Marianne, Bost, Neroli F., & Keijers, Gerben B. (2011) Linking ambulance, emergency department and hospital admissions data : understanding the emergency journey. Medical Journal of Australia, 194(4), S34-S37.

View at publisher

Abstract

Objective: to assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department setting.

Design: automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO. Match rate and quality of the linking were compared. Setting: 10, 835 patient presentations to a large, regional teaching hospital ED over a two month period (August-September 2007).

Results: comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%.

Conclusions: Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.

Impact and interest:

8 citations in Scopus
Search Google Scholar™
4 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 41216
Item Type: Journal Article
Keywords: data linkage, unique patient identifier
ISSN: 1326-5377 (online) 0025-729X (print)
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > PUBLIC HEALTH AND HEALTH SERVICES (111700)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Schools > School of Public Health & Social Work
Copyright Owner: Copyright 2011 Australasian Medical Publishing Company.
Deposited On: 12 Apr 2011 08:10
Last Modified: 15 Jul 2013 10:42

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page