International Journal of General Medicine (Jan 2022)
Linking Ambulance Records with Hospital and Death Index Data to Evaluate Patient Outcomes
Abstract
Emily Andrew,1,2,* Shelley Cox,1,2,* Karen Smith1– 3 1Centre for Research and Evaluation, Ambulance Victoria, Victoria, Australia; 2Department of Epidemiology and Preventive Medicine, Monash University, Victoria, Australia; 3Department of Paramedicine, Monash University, Victoria, Australia*These authors contributed equally to this workCorrespondence: Emily Andrew Email [email protected]: Linkage of electronic administrative datasets is becoming increasingly common, offering a powerful resource for research and analysis. However, routine linkage of prehospital data with emergency department (ED) presentation and hospital admission datasets is rare. We describe a methodology used to link ambulance data with hospital ED presentations, admissions, and death records, and examine potential biases between matched and unmatched patients.Methods: Iterative deterministic linkage methodologies were employed to link clinical, operational, and secondary triage ambulance data to ED presentations, hospital admissions, and death records in Victoria, Australia. Descriptive analyses and standardised differences were used to examine potential biases between matched and unmatched patients.Results: A total of 2,813,913 ambulance records were available for linkage. Of the patients that were transported to a public ED (n=1,753,268), 83.3% matched with an ED record. Only small differences were observed between matched and unmatched patients for sex, year, time of day and attending crew type. The data elements with the largest standardised differences were patient age (0.25) and paramedic diagnosis (0.25). Matched patients were older (mean ± standard deviation: 55.6± 25.7 vs 49.0± 26.0 years) and more likely to have a paramedic-suspected cardiac, respiratory, neurological, or gastrointestinal/genitourinary condition, suspected infection/sepsis, or pain.Conclusion: This linked dataset will facilitate a large body of research into prehospital care and patient outcomes. Although future analysis of matched patients should acknowledge the linkage error rate, our findings suggest that results are likely to be generalisable to the broader ambulance population.Keywords: ambulance, prehospital, data linkage, outcomes
