Dynamic prediction of work status for workers with occupational injuries: assessing the value of longitudinal observations.
Occupational injuries (OIs) cause an immense burden on the US population. Prediction models help focus resources on those at greatest risk of a delayed return to work (RTW). RTW depends on factors that develop over time; however, existing methods only utilize information collected at the time of injury. We investigate the performance benefits of dynamically estimating RTW, using longitudinal observations of diagnoses and treatments collected beyond the time of initial [...]
Author(s): Ötleş, Erkin, Seymour, Jon, Wang, Haozhu, Denton, Brian T
DOI: 10.1093/jamia/ocac130