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Quantification of NSW Ambulance Record Linkages with Multiple External Datasets.
Prehospital Emergency Care
|May 14, 2015
Summary
This study assessed the linkage rates between New South Wales (NSW) Ambulance data and external health records. High linkage rates were found, but potential biases related to age were identified, informing future research and policy.
Area of Science:
- Health Informatics
- Public Health Data Linkage
- Emergency Medical Services Research
Background:
- Accurate linkage of ambulance data with other health records is crucial for comprehensive patient care analysis.
- Previous studies have highlighted challenges in establishing robust data linkages across different healthcare datasets.
- Understanding linkage rates and potential biases is essential for the validity of research using linked health data.
Purpose of the Study:
- To quantify linkage rates between New South Wales (NSW) Ambulance records and four external health datasets.
- To identify and report systematic issues affecting data linkage accuracy for patient and episode-level data.
- To assess how patient and operational variables may introduce bias in subsequent studies using linked ambulance data.
Main Methods:
- Utilized data from NSW Ambulance for July 2006 to June 2009, linked with Emergency Department, Admitted Patient, NSW Registry of Births, Deaths and Marriages, and ABS mortality data.
- Employed the Centre for Health Record Linkage (CHeReL) in NSW for the linkage process.
- Analyzed linkage success based on 'expected' and 'not expected' links within 24 hours of paramedic attendance, and over a 3-year period for mortality.
Main Results:
- Achieved an overall episode-specific hospital linkage rate of 97.2% for 2,041,728 NSW Ambulance care episodes.
- 8.6% of episodes where patients were not transported to hospital resulted in an emergency department attendance within 24 hours.
- 5.2% of all care episodes linked to a death record within 3 years; 2.4% of death episodes occurred within 7 days of a paramedic encounter.
- Nonlinkage to hospital admission records decreased with increasing patient age; other linkage issues were less discriminatory.
Conclusions:
- The study provides a robust quantification of linkage rates and limitations for a large NSW Ambulance linked dataset.
- Identified age as a factor influencing linkage success, highlighting a potential source of bias.
- These findings are critical for the accurate interpretation of future research and the development of evidence-based clinical and operational policies for NSW Ambulance.

