A Bayesian Multi-Layered Record Linkage Procedure to Analyze Functional Status of Medicare Patients with Traumatic Brain Injury

Understanding associations between injury severity and the potential for post-acute care recovery for patients with traumatic brain injury (TBI) is crucial to improving care. Estimating this association requires information on patients' injury severity, demographics, and healthcare utilization, which are dispersed across different datasets. Because of privacy regulations, unique identifiers are not available to link records across datasets. Record linkage methods identify records that represent the same entity across datasets in the absence of unique identifiers. With large number of records, these methods are computationally intensive and may result in many false links. Blocking is a technique to reduce the number of possible links that should be considered by ensuring records representing the same entity only if they agree on key variables. In healthcare applications, health providers constitute a blocking scheme for patients. Specifically, only record pairs represent the same entity if they are receiving care from the same provider. In some cases, providers are uniquely defined within each dataset, but they cannot be uniquely identified across files. We propose a Bayesian record linkage procedure that simultaneously links health providers and records. This procedure improves the quality of links compared to current methods. We use this procedure to merge a trauma registry with Medicare claims to estimate the relationship between injury severity and TBI patients' recovery. After linkage, we did not find significant associations between injury severity and the propensity of TBI patients to be discharged home after admissions to skilled nursing facilities. These findings highlight that in a population of older adults with TBI commonly used severity indices have limited ability to predict post–acute care outcomes. Further research is needed to identify levels of functional impairments and cognitive deficits that are associated with successful discharge from skilled nursing facility among older patients with TBI.

Record Linkage

Post-acute care

Bayesian

Multiple Imputation

Error propagation