Expanding transplant outcomes research opportunities through the use of a common data model

The volume of solid organ transplant in the United States is increasing, providing improved quality of life and survival for patients with organ failure. The growth of transplant requires a systematized management of transplant outcomes assessment, especially with the movement toward value-based care. However, there are several challenges to analyzing outcomes in the current registry-based, transplant reporting system: (1) longitudinal data points are difficult to capture in outcomes models; (2) data elements are restricted to those that already exist in the registry data; and (3) there is a delay in the release of outcomes report. In this article, we propose an informatics approach to solve these problems by using a “common data model” to integrate disparate data sources, data elements, and temporal data points. Adopting such a framework can enable multicenter outcomes analyses among transplant centers, nationally and internationally. The volume of solid organ transplant in the United States is increasing, providing improved quality of life and survival for patients with organ failure. The growth of transplant requires a systematized management of transplant outcomes assessment, especially with the movement toward value-based care. However, there are several challenges to analyzing outcomes in the current registry-based, transplant reporting system: (1) longitudinal data points are difficult to capture in outcomes models; (2) data elements are restricted to those that already exist in the registry data; and (3) there is a delay in the release of outcomes report. In this article, we propose an informatics approach to solve these problems by using a “common data model” to integrate disparate data sources, data elements, and temporal data points. Adopting such a framework can enable multicenter outcomes analyses among transplant centers, nationally and internationally.