International Journal of Medical Informatics

Machine learning directed interventions associate with decreased hospitalization rates in hemodialysis patients

Sheetal Chaudhuri, Hao Han, Len Usvyat, Yue Jiao, David Sweet, Allison Vinson, Stephanie Johnstone Steinberg, Dugan Maddux, Kathleen Belmonte, Jane Brzozowski, Brad Bucci, Peter Kotanko, Yuedong Wang, Jeroen P. Kooman, Dr. Frank Maddux, John W. Larkin

Background: An integrated kidney disease company uses machine learning (ML) models that predict the 12-month risk of an outpatient hemodialysis (HD) patient having multiple hospitalizations to assist with directing personalized interdisciplinary interventions in a Dialysis Hospitalization Reduction Program (DHRP). We investigated the impact of risk directed interventions in the DHRP on clinic-wide hospitalization rates.

Methods: We compared the hospital admission and day rates per-patient-year (ppy) from all hemodialysis patients in 54 DHRP and 54 control clinics identified by propensity score matching at baseline in 2015 and at the end of the pilot in 2018. We also used paired T test to compare the between group difference of annual hospitalization rate and hospitalization days rates at baseline and end of the pilot.

Results: The between group difference in annual hospital admission and day rates was similar at baseline (2015) with a mean difference between DHRP versus control clinics of -0.008 ± 0.09 ppy and -0.05 ± 0.96 ppy respectively. The between group difference in hospital admission and day rates became more distinct at the end of follow up (2018) favoring DHRP clinics with the mean difference being -0.155 ± 0.38 ppy and -0.97 ± 2.78 ppy respectively. A paired t-test showed the change in the between group difference in hospital admission and day rates from baseline to the end of the follow up was statistically significant (t-value = 2.73, p-value < 0.01) and (t-value = 2.29, p-value = 0.02) respectively.

Conclusions: These findings suggest ML model-based risk-directed interdisciplinary team interventions associate with lower hospitalization rates and hospital day rate in HD patients, compared to controls.

About the Author

Dr. Peter Kotanko, MD

RRI Research Director

SVP, Corporate Research & Development

Peter Kotanko, MD, is Research Director at the Renal Research Institute (RRI), New York. Prior to joining RRI, from 1997 to 2007 he served as vice chair of a department of internal medicine at an academic teaching hospital in Graz, Austria. Prior to moving to Graz in 1989, he worked from 1982 to 1989 in the Department of Physiology and the University Clinic of Internal Medicine in Innsbruck, Austria. From 1995 to 1996 he trained in nephrology at the Hammersmith Hospital, London, United Kingdom.