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A Probabilistic Matching Approach to Link De-identified Data from a Trauma Registry and a Traumatic Brain Injury Model System Center
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Jan 2017
Source: Am J Phys Med Rehabil. 96(1):17-24.
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Alternative Title:Am J Phys Med Rehabil
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Description:Objective
There is no civilian TBI database that captures patients in all settings of the care-continuum. The linkage of such databases would yield valuable insight into possible care interventions. Thus, the objective of this article is to describe the creation of an algorithm used to link the Traumatic Brain Injury Model Systems (TBIMS) to trauma data in state and national trauma databases.
Design
The TBIMS data from a single center was randomly divided into two sets. One subset was used to generate a probabilistic linking algorithm to link the TBIMS data to the center’s trauma registry. The other subset was used to validate the algorithm. Medical record numbers were obtained and used as unique identifiers to measure the quality of the linkage. Novel methods were used to maximize the positive predictive value (PPV).
Results
The algorithm generation subset had 121 patients. It had a sensitivity of 88% and a PPV of 99%. The validation subset consisted of 120 patients, and had a sensitivity of 83% and a PPV of 99%.
Conclusions
The probabilistic linkage algorithm can accurately link TBIMS data across systems of trauma care. Future studies can utilize this database to answer meaningful research questions regarding the long-term impact of acute trauma complex on healthcare utilization and recovery across the care-continuum in TBI populations.
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Pubmed ID:27088479
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Pubmed Central ID:PMC5065730
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