Description
Information on specific sequence of healthcare utilization events in heart failure patients may be useful for identifying distinct subpopulations of patients with HF. Knowledge of patient trajectories may help to improve prediction of future readmission which can be used to tailor management to the individual needs of the patient.
This research introduces a new approach to mining administrative and clinical datasets by incorporating graph networks to identify & visualize the trajectories of sequences of events.
Included in
Clinical Epidemiology Commons, Computational Engineering Commons, Health Services Research Commons
Using graph visualization to look at the trajectories of events that lead to readmission
Information on specific sequence of healthcare utilization events in heart failure patients may be useful for identifying distinct subpopulations of patients with HF. Knowledge of patient trajectories may help to improve prediction of future readmission which can be used to tailor management to the individual needs of the patient.
This research introduces a new approach to mining administrative and clinical datasets by incorporating graph networks to identify & visualize the trajectories of sequences of events.