Multi-Trajectory Modeling to Predict Acute Kidney Injury in Chronic Kidney Disease Patients.

Risk-stratifying chronic disease patients in real time has the potential to facilitate targeted interventions and improve disease management and outcomes. We apply group-based multi-trajectory modeling to risk stratify patients with chronic kidney disease (CKD) and its major complications into distinct trajectories of disease development and predict acute kidney injury (AKI), a serious, under-diagnosed outcome of CKD that is both preventable and treatable with early detection. Utilizing Electronic Health Record data of 1,947 patients, we identify eight risk groups with distinct trajectories and profiles.

deidentify.

The increased adoption of Electronic Health Record (EHR) systems offers new opportunities for clinical research. The Health Insurance Portability and Accountability Act (HIPAA) mandates that medical records need to be stripped of personal identifiers in order to be shared. One particular challenge is how to handle free-text medical records.

Multi-Trajectory Models of Chronic Kidney Disease Progression.

An ever increasing number of people are affected by chronic kidney disease (CKD). A better understanding of the progression ofCKD and its complications is needed to address what is becoming a major burden for health-care systems worldwide. Utilizing a rich data set consisting of the Electronic Health Records (EHRs) of more than patients from a leading community nephrology practice in Western Pennsylvania, we applied group-based trajectory modeling (GBTM) in order to detect patient risk groups and uncover typical progressions of CKD and related comorbidities and complications.

Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space.

The Internet has emerged as a popular source for health-related information. More than eighty percent of American Internet users have searched for health topics online. Millions of patients use self-help online forums to exchange information and support.