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

التفاصيل البيبلوغرافية
العنوان: Machine learning directed interventions associate with decreased hospitalization rates in hemodialysis patients
المؤلفون: Len A. Usvyat, Franklin W. Maddux, Dugan W. Maddux, David Sweet, Yuedong Wang, Allison Vinson, Hao Han, Yue Jiao, Sheetal Chaudhuri, Jane Brzozowski, Kathleen Belmonte, John W. Larkin, Jeroen P. Kooman, Peter Kotanko, Brad Bucci, Stephanie Johnstone Steinberg
المساهمون: Interne Geneeskunde, MUMC+: MA Nefrologie (9), RS: NUTRIM - R3 - Respiratory & Age-related Health
المصدر: International Journal of Medical Informatics, 153:104541. Elsevier Ireland Ltd
بيانات النشر: Elsevier Ireland Ltd, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Interdisciplinary teams, medicine.medical_treatment, Psychological intervention, Health Informatics, Machine learning, computer.software_genre, Ambulatory Care Facilities, Mean difference, Hospitalization rate, Machine Learning, Renal Dialysis, MANAGEMENT, Medicine, Humans, Dialysis, Retrospective Studies, Nutrition, RISK, business.industry, Personalized care, End stage kidney disease, Behavioral health, medicine.disease, Social worker, DIALYSIS PATIENTS, Hospitalization, Propensity score matching, Hospital admission, Psychosocial factors, Mental health, Hemodialysis, Artificial intelligence, business, computer, Kidney disease
الوصف: 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.
اللغة: English
تدمد: 1872-8243
1386-5056
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31006206301e8b9b6d4a7a9556d881a1
https://doi.org/10.1016/j.ijmedinf.2021.104541
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....31006206301e8b9b6d4a7a9556d881a1
قاعدة البيانات: OpenAIRE
الوصف
تدمد:18728243
13865056