Algorithm-Based Intervention Fails to Reduce Hospitalization in Patients with Chronic Conditions

Study finds that an algorithm based on electronic health records does not reduce hospitalization rates in patients with kidney dysfunction.

A study published in the New England Journal of Medicine has revealed that using an electronic health record-based algorithm did not result in reduced hospitalization for patients with chronic kidney disease, type 2 diabetes, and hypertension, even after one year. The study, conducted by Miguel A. Vazquez and colleagues from the University of Texas Southwestern Medical Center, involved 11,182 patients treated at 141 primary care clinics.

Patients were either assigned to receive an intervention using a personalized algorithm or to receive usual care. Seventy-one practices with 5,690 patients were assigned to the intervention group, while 70 practices with 5,492 patients were assigned to the usual care group. The hospitalization rate at one year was 20.7% in the intervention group and 21.1% in the usual care group. Both groups had similar risks for emergency department visits, readmissions, cardiovascular events, dialysis or death from any cause. However, there was a higher risk of acute kidney injury among patients in the intervention group compared to those receiving usual care.

The authors concluded that despite using an electronic health record-based algorithm at one year there was no better disease control or reduction of hospitalization compared to usual care. This study was conducted as an open-label cluster-randomized trial and its results were published in the New England Journal of Medicine. Readers interested in learning more about this research can refer to Miguel A. Vazquez et al.’s article found in the journal article section of the publication.

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