Jane Wu1, Steven G Faux1, Ian Harris2, Christopher J Poulos3, Tara Alexander4. 1. St. Vincent's Hospital, New South Wales. 2. Liverpool Hospital, New South Wales. 3. School of Public Health and Community Medicine, University of New South Wales. 4. Australian Health Services Research Institute, University of Wollongong, New South Wales.
Abstract
OBJECTIVES: 1) Describe probabilistic linkage (PL) for road trauma and rehabilitation records in New South Wales (NSW) Australia. 2) Determine the accuracy of linkage for these records. METHODS: Data were extracted from the NSW Trauma Registry for all road trauma admissions for the years 2009-2012 and from Australasian Rehabilitation Outcomes Centre for January 2009 to June 2013. PL was performed using: age; sex; residential postcode; and date of acute discharge = date of admission to rehabilitation. False matches were cases that linked but were not true matches; they were determined by manual review. Reasons for incomplete linkages were explored. The benefits and limitations of the linked study dataset are described. RESULTS: Of 3,256 road trauma records, 683 were matched to rehabilitation records. Using the field of 'discharge destination' from the trauma records, 265 patients with unmatched records were discharged to inpatient rehabilitation (missed matches). This gave an overall 72% linkage rate (or sensitivity) using PL. There were 16 cases of false matches, giving a specificity of 99%. CONCLUSION: It was feasible to use PL to link road trauma and rehabilitation datasets in the absence of identifiers. However, this needed to be combined with careful manual review before the linked dataset could be used to make inferences on trauma rehabilitation outcomes. IMPLICATION: PL may be a cost-effective way to capture inpatient rehabilitation outcomes of multi-trauma patients.
OBJECTIVES: 1) Describe probabilistic linkage (PL) for road trauma and rehabilitation records in New South Wales (NSW) Australia. 2) Determine the accuracy of linkage for these records. METHODS: Data were extracted from the NSW Trauma Registry for all road trauma admissions for the years 2009-2012 and from Australasian Rehabilitation Outcomes Centre for January 2009 to June 2013. PL was performed using: age; sex; residential postcode; and date of acute discharge = date of admission to rehabilitation. False matches were cases that linked but were not true matches; they were determined by manual review. Reasons for incomplete linkages were explored. The benefits and limitations of the linked study dataset are described. RESULTS: Of 3,256 road trauma records, 683 were matched to rehabilitation records. Using the field of 'discharge destination' from the trauma records, 265 patients with unmatched records were discharged to inpatient rehabilitation (missed matches). This gave an overall 72% linkage rate (or sensitivity) using PL. There were 16 cases of false matches, giving a specificity of 99%. CONCLUSION: It was feasible to use PL to link road trauma and rehabilitation datasets in the absence of identifiers. However, this needed to be combined with careful manual review before the linked dataset could be used to make inferences on trauma rehabilitation outcomes. IMPLICATION: PL may be a cost-effective way to capture inpatient rehabilitation outcomes of multi-traumapatients.