Findings on Managed Care Detailed by Researchers at Renal Research Institute (AI-Driven Interventions for Imminent Hospital Admissions in Patients with End-Stage Kidney Disease: A Medicare and EMR-Based Analysis): Managed Care

2026 JUL 21 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Managed Care is the subject of a report. According to news reporting from Waltham, Massachusetts, by NewsRx journalists, research stated, “Patients with end-stage kidney disease (ESKD) have a high rate of hospitalizations related to fluid overload and infections. Artificial intelligence (AI)-driven models may improve patient care by predicting the risk of hospitalization.”

The news correspondents obtained a quote from the research from Renal Research Institute, “The authors conducted a retrospective, observational matched cohort study of adult patients with ESKD who were receiving value-based hemodialysis at integrated kidney care clinics across the United States in 2023. Two AI-powered machine learning models calculated risk scores (range: 0-1) and the models identified patients with a risk score of 0.64 or above who were at risk for hospitalization within 7 days in relation to infections or fluid status abnormalities. To prevent avoidable hospitalizations, case reviews and interventions were conducted for the patients identified by the models. The AI models generated scores for all patients, but only high-risk scores triggered case review and possible intervention. The authors linked electronic medical records and Medicare claims data and conducted multivariate logistic regression analyses to examine the impact of AI-driven interventions on the odds of all-cause hospitalization in patients with ESKD. A total of 10,294 patients representing 83,928 risk scores were included in the analysis. AI-driven intervention was associated with an 8% reduction in the odds of hospitalization within 7 days (odds ratio=0.92; P=0.025). These interventions were most effective for high-risk patients with scores between 0.64 and 0.85, but had no statistically significant effect for patients with scores above 0.85. Factors that were independently associated with higher rates of hospital admission included a higher risk score (>0.75), chronic high-risk scores, older age, and a higher number of hospital admissions in the year prior. AI-driven interventions were associated with a reduction in the odds of hospitalization among patients with ESKD receiving managed kidney care.”

According to the news reporters, the research concluded: “These findings underscore AI’s potential to assist health care providers with targeted risk interventions for patients with ESKD.”

This research has been peer-reviewed.

For more information on this research see: AI-Driven Interventions for Imminent Hospital Admissions in Patients with End-Stage Kidney Disease: A Medicare and EMR-Based Analysis. NEJM Catalyst Innovations In Care Delivery, 2026;7(3).

Our news journalists report that additional information may be obtained by contacting Joanna Willetts, Senior Principal Data Analyst, Renal Research Institute, Waltham, MA, United States. Additional authors for this research include Sheetal Chaudhuri, Tina Chen, Caitlin Monaghan, Hao Han, Adriana Lindsey, Susan Marsh, Greg Garza, Dinesh Chatoth, Michelle Carver and Len Usvyat.

(Our reports deliver fact-based news of research and discoveries from around the world.)